Citation statistics by hand (also see Google Scholar Citations)
Cited publications: 42
Citations: 1701
h-index: 22

Brembs B (2018): Prestigious Science Journals Struggle to Reach Even Average Reliability. Frontiers in Human Neuroscience. 12(37). DOI: 10.3389/fnhum.2018.00037
Citations:

  1. Wass MN, Ray L, Michaelis M (2018): Researcher Conduct Determines Data Reliability. MDPI AG. DOI: 10.20944/preprints201804.0068.v1

Benjamin DJ, Berger JO, Johannesson M, Nosek BA, Wagenmakers E-J, Berk R, Bollen KA, Brembs B, Brown L, Camerer C, et al. (2017): Redefine statistical significance. Nature Human Behaviour. 2:6–10. DOI: 10.1038/s41562-017-0189-z

Citations:

  1. Lebis A, Lefevre M, Luengo V, Guin N (2018): Capitalisation of analysis processes. Proceedings of the 8th International Conference on Learning Analytics and Knowledge – LAK ’18. Presented at the the 8th International Conference, ACM Press. DOI: 10.1145/3170358.3170408
  2. Ioannidis JPA (2018): The Proposal to Lower P Value Thresholds to .005. JAMA. 319(4):1429-1430. DOI: 10.1001/jama.2018.1536.
  3. Itescu Y, Schwarz R, Donihue CM, Slavenko A, Roussos SA, Sagonas K, Valakos ED, et al. (2018): Inconsistent patterns of body size evolution in co-occurring island reptiles. In: McGill B (Ed.): Global Ecology and Biogeography. Wiley-Blackwell. DOI: 10.1111/geb.12716
  4. Krueger J, Heck P (2018): Putting the P Value in its Place. PsyArXiv. https://psyarxiv.com/y49mp/
  5. Holbert RL, Hardy BW, Park E, Robinson NW, Jung H, Zeng C, Drouin E, et al. (2018): Addressing a statistical power-alpha level blind spot in political- and health-related media research: discontinuous criterion power analyses. Annals of the International Communication Association, 1–18. DOI: 10.1080/23808985.2018.1459198
  6. Lazic SE (2018): Four simple ways to increase power without increasing the sample size. Laboratory Animals, 2367721876747. DOI: 10.1177/0023677218767478
  7. Segal BD (2018): Exceedance probability for parameter estimates. arXiv:1803.03356. http://arxiv.org/abs/1803.03356
  8. Rouder J, Haaf JM, Snyder HK (2018): Minimizing Mistakes In Psychological Science. PsyArXiv. https://psyarxiv.com/gxcy5/
  9. De la Guardia FH, Grant S, Miguel E (2018): Why We Need Open Policy Analysis. Open Science Framework. https://osf.io/jquwz/
  10. Dragos D, Gilca M (2018): Taste of Phytocompounds: A Better Predictor for Ethnopharmacological Activities of Medicinal Plants Than The Phytochemical Class? Journal of Ethnopharmacology. DOI: 10.1016/j.jep.2018.03.034
  11. Lorca-Puls DL, Gajardo-Vidal A, White J, Seghier ML, Leff AP, Green DW, Crinion JT, et al. (2018): The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings. Neuropsychologia. DOI: 10.1016/j.neuropsychologia.2018.03.014
  12. Fowlie A (2018): DAMPE squib? Significance of the 1.4 TeV DAMPE excess. Physics Letters B. 780: 181–184. DOI: 10.1016/j.physletb.2018.03.006
  13. Shadbolt RP, Ellis AW (2018): 1000 Differential Temperature Trends across Elevation within the „Warming Hole“ of the Southeast United States. Presented at the 98th American Meteorological Society Annual Meeting, https://ams.confex.com/ams/98Annual/webprogram/Paper328864.html
  14. Plavén-Sigray P, Matheson GJ, Gustavsson P, Stenkrona P, Halldin C, Farde L, Cervenka S (2018): Is dopamine D1 receptor availability related to social behavior? A positron emission tomography replication study. PLOS ONE. 13(3):e0193770. DOI: 10.1371/journal.pone.0193770
  15. Nosek BA, Ebersole CR, DeHaven AC, Mellor DT (2018): The preregistration revolution. Proceedings of the National Academy of Sciences. 115(11):2600–2606. DOI: 10.1073/pnas.1708274114
  16. Brown MJ (2018): Science and Moral Imagination: A new Ideal for Values in Science. http://www.matthewjbrown.net/research/science-and-moral-imagination/
  17. Abadie A (2018): On Statistical Non-Significance. arXiv:1803.00609. http://arxiv.org/abs/1803.00609
  18. Gannon M, Pereira CADB (2018): Letter to the Editor: Abandon fixed significance levels, not P-values! Unpublished. DOI: 10.13140/RG.2.2.20178.86725
  19. Voelkl B, Vogt L, Sena ES, Würbel H (2018): Reproducibility of preclinical animal research improves with heterogeneity of study samples. PLOS Biology. 16(2): e2003693. DOI: 10.1371/journal.pbio.2003693
  20. Distefano A, Jackson F, Levinson AR, Infantolino ZP, Jarcho JM, Nelson BD (2018): A comparison of the electrocortical response to monetary and social reward. Social Cognitive and Affective Neuroscience. 13(3): 247–255. DOI: 10.1093/scan/nsy006
  21. Abadie A (2018): Statistical Non-Significance in Empirical Economics. NBER Working Paper No. 24403. https://ssrn.com/abstract=3138353
  22. Van Calster B, Steyerberg EW, Collins GS, Smits T (2018): Consequences of relying on statistical significance: Some illustrations. European Journal of Clinical Investigation. e DOI: 10.1111/eci.12912
  23. Ruiz-Ruano AM, López J (2018): Deciding on Null Hypotheses using P-values or Bayesian alternatives: A simulation study. Psicothema. 30(1):110–115. DOI: 10.7334/psicothema2017.308
  24. Lakens D, Adolfi FG, Albers CJ, Anvari F, Apps MAJ, Argamon SE, Baguley T, et al. (2018): Justify your alpha. Nature Human Behaviour. 2(3):168–171. DOI: 10.1038/s41562-018-0311-x
  25. Perezgonzalez JD, Frías-Navarro MD (2018): Retract p < 0.005 and propose using JASP, instead. F1000Research. 6:2122. DOI: 10.12688/f1000research.13389.2
  26. Schirmer A, Ng T, Ebstein RP (2018): Vicarious Social Touch Biases Gazing at Faces and Facial Emotions. Emotion. American Psychological Association. DOI: 10.1037/emo0000393
  27. Matthews RAJ (2018): Beyond “significance”: principles and practice of the Analysis of Credibility. Royal Society Open Science. 5(1):171047. DOI: 10.1098/rsos.171047
  28. Kruschke J (2018): Rejecting or accepting parameter values in Bayesian estimation. Open Science Framework. DOI: 17605/OSF.IO/S5VDY
  29. Van Der Ende MY, Hendriks T, Van Veldhuisen DJ, Snieder H, Verweij N, Van Der Harst P (2018): Causal Pathways from Blood Pressure to Larger Qrs Amplitudes a Mendelian Randomization Study. Scientific Reports. 8. DOI: 10.1038/s41598-018-24002-0
  30. Cova F, Strickland B, Abatista A, Allard A, Andow J, Attie M, Beebe J, Berniūnas R, Boudesseul J, Colombo M, et al. (2018): Estimating the Reproducibility of Experimental Philosophy. PsyArXiv. DOI: 17605/OSF.IO/SXDAH
  31. Cox NJ, Below JE (2018): Critical Evaluation of Data Requires Rigorous but Broadly Based Statistical Inference Response by Lem Moyé and Michelle Cohen. Circulation Research. 122:1049–1051. DOI: 10.1161/CIRCRESAHA.118.312530
  32. Heino MTJ, Vuorre M, Hankonen N (2018): Bayesian evaluation of behavior change interventions: a brief introduction and a practical example. Health Psychology and Behavioral Medicine. 6:49–78. DOI: 10.1080/21642850.2018.1428102
  33. Krefeld-Schwalb A, Witte EH, Zenker F (2018): Hypothesis-Testing Demands Trustworthy Data—A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy. Frontiers in Psychology. 9. DOI: 10.3389/fpsyg.2018.00460
  34. Cursan A (2018): Un chercheur sachant chercher: de l’importance scientifique des résultats « nuls » et négatifs en psychologie. Pratiques Psychologiques. DOI: 10.1016/j.prps.2018.03.001
  35. Fang L, Gao P, Bao H, Tang X, Wang B, Feng Y, Cong S, Juan J, Fan J, Lu K, et al. (2018): Chronic obstructive pulmonary disease in China: a nationwide prevalence study. The Lancet Respiratory Medicine. DOI: 10.1016/S2213-2600(18)30103-6
  36. Consonni G, Fouskakis D, Liseo B, Ntzoufras I (2018): Prior Distributions for Objective Bayesian Analysis. Bayesian Analysis. DOI: 10.1214/18-BA1103
  37. Trafimow D, Amrhein V, Areshenkoff CN, et. al. (2018): Manipulating the Alpha Level Cannot Cure Significance Testing. Unpublished. DOI: 7287/peerj.preprints.3411v2
  38. Jäncke L, Leipold S, Burkhard A (2018): The neural underpinnings of music listening under different attention conditions. NeuroReport . 29: 594–604. DOI: 10.1097/WNR.0000000000001019
  39. Moyé L, Cohen M (2018): Liberation From thePValue’s Tyranny. Circulation Research. 122:1046–1048. DOI: 10.1161/CIRCRESAHA.117.312227
  40. Lash TL, Collin LJ, Van Dyke ME (2018): The Replication Crisis in Epidemiology: Snowball, Snow Job, or Winter Solstice? Current Epidemiology Reports. DOI: 10.1007/s40471-018-0148-x
  41. Bradley MT, Brand A (2017): Out with .05, in with Replication and Measurement: Isolating and Working with the Particular Effect Sizes that are Troublesome for Inferential Statistics. The Journal of General Psychology. 144(4):309–316. DOI: 10.1080/00221309.2017.1381496
  42. Pereira C, Nakano E, Fossaluza V, Esteves L, Gannon M, Polpo A (2017): Hypothesis Tests for Bernoulli Experiments: Ordering the Sample Space by Bayes Factors and Using Adaptive Significance Levels for Decisions. Entropy. 19(12):696. DOI: 10.3390/e19120696
  43. Tracy DK, Joyce DW, Shergill SS (2017): Kaleidoscope. British Journal of Psychiatry. 211(4):256–257. DOI: 10.1192/bjp.211.4.256
  44. Liu D, Jiang X, Zheng HJ, Xie B, Wang H, He T, Hu X (2017): The modularity of microbial interaction network in healthy human saliva: Stability and specificity. Presented at the 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE. DOI: 10.1109/BIBM.2017.8217976
  45. Liu Fm Yang J, Han L, Guo S (2017): Biocontrol Activity of Three Endolichenic Fungi from Peltigera. Advances in Microbiology. 6(4): 91–97. DOI: 10.12677/amb.2017.64012
  46. Meade BJ, DeVries PMR, Faller J, Viegas F, Wattenberg M (2017): What Is Better Than Coulomb Failure Stress? A Ranking of Scalar Static Stress Triggering Mechanisms from 105 Mainshock-Aftershock Pairs. Geophysical Research Letters. 44(22):11,409-11,416. DOI: 10.1002/2017GL075875
  47. Pernet C (2017): Null hypothesis significance testing: a guide to commonly misunderstood concepts and recommendations for good practice. F1000Research. 4:621. DOI: 10.12688/f1000research.6963.4

Brembs B (2017): Operant Behavior in Model Systems. In: Learning and Memory: A Comprehensive Reference. Elsevier, 505–516. DOI: 10.1016/b978-0-12-809324-5.21032-8.
Citations:

  1. Edelman S, Moyal R (2017): Fundamental computational constraints on the time course of perception and action. In: Progress in Brain Research. Elsevier, 121–141. DOI: 10.1016/bs.pbr.2017.05.006.
  2. Verasztó C, Ueda N, Bezares-Calderón LA, Panzera A, Williams EA, Shahidi R & Jékely G (2017): Ciliomotor circuitry underlying whole-body coordination of ciliary activity in the Platynereis larva. eLife. 6. DOI: 10.7554/eLife.26000

Gorostiza EA, Colomb J, Brembs B (2016): A decision underlies phototaxis in an insect. Open Biology
Citations:

  1. Hall H, Medina P, Cooper DA, Escobedo SE, Rounds J, Brennan KJ, Vincent C, et al. (2017): Transcriptome profiling of aging Drosophila photoreceptors reveals gene expression trends that correlate with visual senescence. BMC Genomics. 18(1). DOI: 10.1186/s12864-017-4304-3
  2. Vorontsov DD, Dyakonova VE (2017): Light-dark decision making in snails: Do preceding light conditions matter? Communicative & Integrative Biology. 10(5–6): e1356515. DOI: 10.1080/19420889.2017.1356515
  3. Adler J (2016): A Search for The Boss: The Thing Inside Each Organism That is in It could be a Phospholipid Derivative. Anatomy Physiology & Biochemistry International Journal. 1(1). DOI: 10.19080/APBIJ.2016.01.555555
  4. Bosch DS (2016): Analysing visual behaviour in Drosophila Dscam2 mutants using optimised optomotor and operant control assays. PhD Dissertation, University of Queensland

Colomb J, Brembs B (2016): PKC in motorneurons underlies self-learning, a form of motor learning in Drosophila. PeerJ. 4:e1971. DOI: 10.7717/peerj.1971
Citations:

  1. Lehmann FO, Bartussek J (2016): Neural control and precision of flight muscle activation in Drosophila. J Comp Physiol A. 203(1):1–14. DOI: 10.1007/s00359-016-1133-9
  2. Lehmann FO (2017): Neural Control and Precision of Spike Phasing in Flight Muscles. Journal of Neurology and Neuromedicine. 2(9):15–19. DOI: 1007/s00359-016-1133-9
  3. Denton-Edmundson M (2017): The Animal Life. Thesis. Virginia Tech. https://vtechworks.lib.vt.edu/handle/10919/78391

Rahman R, Chirn G, Kanodia A, Sytnikova YA, Brembs B, Bergman CM, Lau NC (2015): Unique transposon landscapes are pervasive across Drosophila melanogaster genomes. Nucleic Acids Res, 43: 10655–10672, DOI: 10.1093/nar/gkv1193
Citations:

  1. Disdero E, Filée J (2017): LoRTE: Detecting transposon-induced genomic variants using low coverage PacBio long read sequences. Mobile DNA. 8(1). DOI: 10.1186/s13100-017-0088-x
  2. Luo S, Lu J (2017): Silencing of Transposable Elements by piRNAs in Drosophila: An Evolutionary Perspective. Genomics, Proteomics & Bioinformatics. 15(3):164–176. DOI: 10.1016/j.gpb.2017.01.006
  3. Horváth V, Merenciano M, González J (2017): Revisiting the Relationship between Transposable Elements and the Eukaryotic Stress Response. Trends in Genetics. 33(11):832–841. DOI: 10.1016/j.tig.2017.08.007
  4. Clark JP, Rahman R, Yang N, Yang LH, Lau NC (2017): Drosophila PAF1 Modulates PIWI/piRNA Silencing Capacity. Current Biology. 27(17):2718–2726. DOI: 10.1016/j.cub.2017.07.052
  5. Lee YCG, Karpen GH (2017): Pervasive epigenetic effects of Drosophila euchromatic transposable elements impact their evolution. eLife. 6. DOI: 10.7554/eLife.25762
  6. Bergman CM, Han S, Nelson MG, Bondarenko V, Kozeretska I (2017): Genomic analysis of P elements in natural populations of Drosophila melanogaster. PeerJ. 5: e3824. DOI: 10.7717/peerj.3824
  7. Kelleher ES (2016): Reexamining the P -Element Invasion of Drosophila melanogaster Through the Lens of piRNA Silencing. Genetics. 203(4):1513–1531. DOI: 10.1534/genetics.115.184119
  8. Zhang S, Kelleher ES (2017): Targeted identification of TE insertions in a Drosophila genome through hemi-specific PCR. Mobile DANN. 8(1). DOI: 10.1186/s13100-017-0092-1
  9. Srivastav SP, Kelleher ES (2017): Paternal Induction of Hybrid Dysgenesis in Drosophila melanogaster Is Weakly Correlated with Both P -Element and hobo Element Dosage. Genes|Genomes|Genetics. 7(5):1487–1497. DOI: 10.1534/g3.117.040634
  10. Nelson MG, Linheiro RS, Bergman CM (2017): McClintock: An Integrated Pipeline for Detecting Transposable Element Insertions in Whole-Genome Shotgun Sequencing Data. Genes|Genomes|Genetics. 7(8):2763–2778. DOI: 10.1534/g3.117.043893
  11. Ninova M, Griffiths-Jones S, Ronshaugen M (2017): Abundant expression of somatic transposon-derived piRNAs throughout Tribolium castaneum embryogenesis. Genome Biology. 18(1). DOI: 10.1186/s13059-017-1304-1
  12. Quadrana L, Bortolini Silveira A, Mayhew GF, LeBlanc C, Martienssen RA, Jeddeloh JA, Colot V (2016): The Arabidopsis thaliana mobilome and its impact at the species level. eLife. 5. DOI: 10.7554/eLife.15716
  13. Penke TJR, McKay DJ, Strahl BD, Matera AG, Duronio RJ (2016): Direct interrogation of the role of H3K9 in metazoan heterochromatin function. Genes & Development. 30(16):1866–1880. DOI: 10.1101/gad.286278.116
  14. Kofler R, Gomez-Sanchez D, Schloetterer C (2016): PoPoolationTE2: comparative population genomics of transposable elements using Pool-Seq

Mendoza E, Colomb J, Rybak J, Pflüger H-J, Zars T, Scharff C, Brembs B (2014): Drosophila FoxP Mutants Are Deficient in Operant Self-Learning. PLoS ONE 9(6): e100648. doi:10.1371/journal.pone.0100648
Citations:

  1. Schatton A, Mendoza E, Grube K, Scharff C (2018): FoxP in bees: A comparative study on the developmental and adult expression pattern in three bee species considering isoforms and circuitry. Journal of Comparative Neurology. 526:1589–1610. DOI: 10.1002/cne.24430
  2. Mendoza E, Ezequiel C, Scharff C (2017): Protein-Protein Interaction Among the FoxP Family Members and their Regulation of Two Target Genes, VLDLR and CNTNAP2 in the Zebra Finch Song System. Frontiers in Molecular Neuroscience. 10. DOI: 10.3389/fnmol.2017.00112
  3. Foley BR, Marjoram P, Nuzhdin SV (2017): Basic reversal-learning capacity in flies suggests rudiments of complex cognition. PLOS ONE. 12(8): e0181749. DOI: 10.1371/journal.pone.0181749
  4. Schatton A, Scharff C (2017): FoxP expression identifies a Kenyon cell subtype in the honeybee mushroom bodies linking them to fruit fly αβc neurons. European Journal of Neuroscience. 46(9):2534–2541. DOI: 10.1111/ejn.13713
  5. Widmann A, Eichler K, Selcho M, Thum AS, Pauls D (2017): Odor-taste learning in Drosophila larvae. Journal of Insect Physiology. DOI: 10.1016/j.jinsphys.2017.08.004
  6. Mills I (2017): The Evolution of Fear Ecology: A Fruit Fly (Drosophila melanogaster) Perspective. Master thesis, University of Missouri-St. Louis. https://irl.umsl.edu/thesis/304
  7. Schatton A, Scharff C (2016): Next stop: Language. The “FOXP2” gene’s journey through time. Mètode Revista de difusió de la investigació. 0(7). DOI: 10.7203/metode.7.7248
  8. Ostrowski D, Kahsai L, Kramer EF, Knutson P, Zars T (2015) Place memory retention in Drosophila. Neurobiol Learn Mem 123: 217–224. DOI: 10.1016/j.nlm.2015.06.015
  9. Sperling K (2015): The Nature-Culture-Border in the Light of the Human Genome Project. Med. Gen. 27(1): 7-17, DOI: 10.1007/s11825-015-0037-3
  10. Boeckx C, Theofanopoulou C (2014): A multidimensional interdisciplinary framework for linguistics: the lexicon as a case study. J. Cogn. Sci. 15: 403–420
  11. Weiss SJ, Rosales-Ruiz J (2014): Operant/Classical Conditioning: Comparisons, Intersections and Interactions: The 2014 Winter Conference on Animal Learning and Behavior Focus and Research Seminar Sessions. International Journal of Comparative Psychology. 27(4). https://escholarship.org/uc/item/4c46c9gg

Colomb J, Brembs B (2014): Sub-strains of Drosophila Canton-S differ markedly in their locomotor behavior. F1000Res, 10.12688/f1000research.4263.1
Citations:

  1. Pomatto LCD, Wong S, Tower J, Davies KJA (2018): Sex-specific adaptive homeostasis in D. melanogaster depends on increased proteolysis by the 20S Proteasome: Data-in-Brief. Data in Brief. 17:653–661. DOI: 10.1016/j.dib.2018.01.044
  2. Piwowar M, Jurkowski W (2018): Missing data in open-data era – a barrier to multiomics integration. Bio-Algorithms and Med-Systems. 0(0). DOI: 10.1515/bams-2017-0026
  3. Qiao B, Li C, Allen VW, Shirasu-Hiza M, Syed S (2018): Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier. eLife. 7. DOI: 10.7554/eLife.34497
  4. Signor SA, Abbasi M, Marjoram P, Nuzhdin SV (2017): Conservation of social effects (Ψ) between two species of Drosophila despite reversal of sexual dimorphism. Ecology and Evolution. 7(23):10031–10041. DOI: 10.1002/ece3.3523
  5. Qiu S, Xiao C, Meldrum Robertson R (2017): Different age-dependent performance in Drosophila wild-type Canton-S and the white mutant w1118 flies. In: Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology. 206:17–23. Elsevier BV. DOI: 10.1016/j.cbpa.2017.01.003
  6. Velazquez-Ulloa NA (2017): A Drosophila model for developmental nicotine exposure. PLOS ONE. 12(5): e0177710. DOI: 10.1371/journal.pone.0177710
  7. Morgan SL, Seggio JA, Nascimento NF, Huh DD, Hicks JA, Sharp KA, Axelrod JD, et al. (2016): The Phenotypic Effects of Royal Jelly on Wild-Type D. melanogaster Are Strain-Specific. PLOS ONE. 11(8): e0159456. DOI: 10.1371/journal.pone.0159456
  8. Hampel S, Seeds AM (2016): Targeted manipulation of neuronal activity in behaving adult flies. PeerJ. DOI: 10.7287/peerj.preprints.2354v2
  9. Bosch DS (2016): Analysing visual behaviour in Drosophila Dscam2 mutants using optimised optomotor and operant control assays. PhD Dissertation, University of Queensland
  10. Tennant JP, Waldner F, Jacques DC, Masuzzo P, Collister LB, Hartgerink CHJ (2016): The academic, economic and societal impacts of Open Access: an evidence-based review [version 1; referees: 2 approved, 1 approved with reservations]. F1000Research 5:632 (doi: 10.12688/f1000research.8460.1)
  11. Haddaway NR, Hedlund K, Jackson LE, Kätterer T, Lugato E, Thomsen IK, Jørgensen HB, Söderström B (2015): What are the effects of agricultural management on soil organic carbon in boreo-temperate systems? Env Evid, 4:23, DOI: 10.1186/s13750-015-0049-0
  12. West RJ, Elliott CJ, Wade AR (2015): Classification of Parkinson’s Disease Genotypes in Drosophila Using Spatiotemporal Profiling of Vision. Sci Rep. 5: 16933, DOI: 10.1038/srep16933
  13. Pinfield S (2015): Making Open Access work. Online Inf Rev. 39: 604–636, DOI: 10.1108/OIR-05-2015-0167
  14. Xiao C, Robertson RM (2015): Locomotion Induced by Spatial Restriction in Adult Drosophila. PLOS ONE 10(9):e0135825, DOI: 10.1371/journal.pone.0135825
  15. Zalucki O, Day R, Kottler B, Karunanithi S, van Swinderen B (2015): Behavioral and electrophysiological analysis of general anesthesia in 3 background strains of Drosophila melanogaster. Fly, 9: 7–15, DOI: 10.1080/19336934.2015.1072663
  16. Watson M (2015): When will “open science” become simply “science”? Genome Biol, 16:101, DOI: 10.1186/s13059-015-0669-2

Brembs,B. (2014) Aplysia operant conditioning. Scholarpedia, 9, 4097.
Citations:

  1. Sakurai A, Katz PS (2015): Phylogenetic and individual variation in gastropod central pattern generators. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 201: 829–839, DOI: 10.1007/s00359-015-1007-6

Brembs B (2013): Invertebrate behavior—actions or responses? Frontiers in Neuroscience 7, Article 221
Citations:

  1. Rodrigues AS, Botina L, Nascimento CP, Gontijo LM, Torres JB, Guedes RNC (2016): Ontogenic behavioral consistency, individual variation and fitness consequences among lady beetles. Behav Proc. 131:32–39. DOI: 10.1016/j.beproc.2016.08.003
  2. Shah SN (2017): Effects of sleep-deprivation on decision-making and action selection. Thesis, University of San Diego
  3. Avila-Núñez JL, Naya M, Otero LD, Alonso-Amelot ME (2017): Sticky trap predation in the Neotropical resin bug Heniartes stali (Wygodzinsky) (Hemiptera: Reduviidae: Harpactorinae). Journal of Ethology. 35(2):213–219. DOI: 10.1007/s10164-017-0512-1
  4. Kralj-Fišer S, Schuett W (2014): Studying personality variation in invertebrates: why bother? Anim Behav. 91:41–52

Brembs B, Button K, Munafò M (2013): Deep Impact: unintended consequences of journal rank. Front Hum Neurosci. 7:Article 291
Citations:

  1. Cuschieri S (2018): WASP: Is open access publishing the way forward? A review of the different ways in which research papers can be published. Early Human Development. DOI: 10.1016/j.earlhumdev.2018.02.017
  2. Forest C (2018): PubPeer contre “fake news” en Sciences? Ethics, Medicine and Public Health. DOI: 10.1016/j.jemep.2018.01.009
  3. Heise C (2018): Von Open Access zu Open Science. Lüneburg: meson press. ISBN: 978-3-95796-131-0
  4. Moher D, Naudet F, Cristea IA, Miedema F, Ioannidis JPA, Goodman SN (2018): Assessing scientists for hiring, promotion, and tenure. PLOS Biology. 16(3): e2004089. DOI: 10.1371/journal.pbio.2004089
  5. Brueckner M, Spencer R, Paull M (2018): Teaching for Tomorrow: Preparing Responsible Citizens. In: CSR, Sustainability, Ethics & Governance (pp 1–18). Springer International Publishing. DOI: 10.1007/978-3-319-71449-3_1
  6. Polonioli A (2017): A plea for minimally biased naturalistic philosophy. Springer Nature. DOI: 10.1007/s11229-017-1628-0
  7. Campbell H, & Gustafson P (2018): The world of research has gone berserk: modeling the consequences of requiring „greater statistical stringency“ for scientific publication. University of British Columbia. arXiv:1803.06053
  8. Daston L (2017): Science in the Archives: Pasts, Presents, Futures. University of Chicago Press
  9. Leydesdorff L, Wagner CS, Bornmann L (2018): Discontinuities in Citation Relations among Journals: Self-organized Criticality as a Model of Scientific Revolutions and Change. Scientometrics. 1-22. DOI:1007/s11192-018-2734-6
  10. Smith PL, Little DR (2018): Small is beautiful: In defense of the small-N design. Psychonomic Bulletin & Review. DOI: 10.3758/s13423-018-1451-8
  11. Brembs B (2018): Prestigious Science Journals Struggle to Reach Even Average Reliability. Frontiers in Human Neuroscience. 12. DOI: 10.3389/fnhum.2018.00037
  12. Are C, Yanala U, Malhotra G, Hall B, Smith L, Cummings C, Lecoq C, et al. (2018): Global curriculum in research literacy for the surgical oncologist. European Journal of Surgical Oncology. 44(1):31–42. DOI: 10.1016/j.ejso.2017.07.017
  13. Matlin SA, Metha G, Krief A, Hopf H, et al. (2017): The Scientific publishing conundrum: A perspective from chemistry. Beilstein Magazine. DOI: 10.3762/bmag.9
  14. Copenhaver A, Mitrofan O, Ferguson CJ (2017): For Video Games, Bad News Is Good News: News Reporting of Violent Video Game Studies. Cyberpsychology, Behavior, and Social Networking. 20(12): 735–739. DOI: 10.1089/cyber.2017.0364
  15. Campos LA, Feres Júnior J, Guarnieri F (2017): 50 Anos da Revista DADOS: Uma Análise Bibliométrica do seu Perfil Disciplinar e Temático. Dados. 60(3): 623–661. DOI: 10.1590/001152582017131
  16. Meggs SM, Greer AG., Bian H, Gustina C (2017): Identification of Academic Value for Interior Design Scholarship: A Survey of Journal Ranking. The International Journal of Design Education. 11(4):1–16. DOI: 10.18848/2325-128X/CGP/v11i04/1-16
  17. Buttliere B & Buder J (2017): Personalizing papers using Altmetrics: comparing paper “Quality” or “Impact” to person “Intelligence” or “Personality.” Scientometrics. 111(1):219–239. DOI: 10.1007/s11192-017-2246-9
  18. Meyer AD & Starbuck WH (2017): Mahalo: Sustaining JMI’s Positive Spirit. Journal of Management Inquiry. 27(2):154–157. DOI: 10.1177/1056492617726272
  19. Dumas-Mallet E (2017): Recherche Biomedicale et Journalisme en Situation d‘Incertitude – Validité des résultats de la recherche biomédicale et couverture médiatique. PhD thesis, Université de Bordeaux
  20. Wall T, Bellamy L, Evans V, Hopkins S (2017): Revisiting impact in the context of workplace research: a review and possible directions. Journal of Work-Applied Management. 9(2):95–109. DOI: 10.1108/JWAM-07-2017-0018
  21. Armstrong JS & Green KC (2017): Guidelines for Science: Evidence and Checklists. SSRN Electronic Journal. DOI: 10.2139/ssrn.3055874
  22. McKiernan EC (2017): Imagining the “open” university: Sharing scholarship to improve research and education. PLOS Biology. 15(10): e1002614. DOI: 10.1371/journal.pbio.1002614
  23. Chambers C (2017): The Seven Deadly Sins of Psychology: A Manifesto for Reforming the Culture of Scientific Practice. Princeton University Press. ISBN: 9781400884940
  24. Arsène S (2017): China Perspectives Amidst Scientific Change and Digitalisation. China Perspectives. 3:3-5. http://chinaperspectives.revues.org/7373
  25. Peters GJY, Kok G, Crutzen R, Sanderman R (2017): Health Psychology Bulletin: Improving Publication Practices to Accelerate Scientific Progress. Health Psychology Bulletin. 1(1):1–6. DOI: 10.5334/hpb.2
  26. Peters GJY (2017): Why not to use the journal impact factor as a criterion for the selection of junior researchers: A comment on Bornmann and Williams (2017). Journal of Informetrics. 11(3): 888–891. DOI: 10.1016/j.joi.2017.08.001
  27. Reider B (2017): Brace for Impact. The American Journal of Sports Medicine. 45(10): 2213–2216. DOI: 10.1177/0363546517721707
  28. Eve MP & Priego E (2017): Who is Actually Harmed by Predatory Publishers? tripleC: Communication, Capitalism & Critique. Open Access Journal for a Global Sustainable Information Society. 15(2): 755–770
  29. Greenblatt DJ & Shader RI (2017): The Impact Non-Factor. Journal of Clinical Psychopharmacology. 37(4): 389–390. DOI: 10.1097/JCP.0000000000000743
  30. Katz Y, Matter U (2017): On the Biomedical Elite: Inequality and Stasis in Scientific Knowledge Production. Berkman Klein Center for Internet & Society Research Publication. https://dash.harvard.edu/handle/1/33373356
  31. Tsimilli-Michael M & Haldimann P (2017): Sustainability of photosynthesis research–when research is impeded by the cults of audit and management. Photosynthetica. 55(2): 391–400. DOI: 10.1007/s11099-017-0686-3
  32. Laman JD, Kooistra SM, Clausen BE (2017): Reproducibility Issues: Avoiding Pitfalls in Animal Inflammation Models. Inflammation (pp. 1–17). Springer New York. DOI: 10.1007/978-1-4939-6786-5_1
  33. Siler K, Strang D (2016): Peer Review and Scholarly Originality. Science, Technology & Human Values. 42(1):29–61. DOI: 10.1177/0162243916656919
  34. Fernandez-Rios L (2016): The rate of impact and the future of academic journals. The risk of pathologization. Innovacion educativa. 16(72).
  35. Carey RM (2016): Quantifying Scientific Merit. Circulation Research. 119(12): 1273–1275. DOI: 10.1161/CIRCRESAHA.116.309883
  36. Hassmén P, Keegan R, Piggott D (2016): Planning a Post-revolutionary World. In: Rethinking Sport and Exercise Psychology Research (pp. 243–276). Palgrave Macmillan, London. DOI: 10.1057/978-1-137-48338-6_10
  37. Abele-Brehm AE, Bühner M (2016): Wer soll die Professur bekommen? Psychologische Rundschau. 67(4):250–261. DOI: 10.1026/0033-3042/a000335
  38. Wolf B, Szerencsits M, Heß J, Gaus H, Müller C, Stockmann R (2016): Weiterentwicklung und Erprobung eines Konzeptes zur Dokumentation und Evaluierung von Leistungen der Agrarforschung für Praxis und Gesellschaft. Project report. Center for evaluation
  39. Grigston J & Mudrak B (2016): The State of Authorship: Maximizing Impact with the Time and Money You Spend. American Journal Experts. https://www.aje.com/en/arc/dist/docs/AJE-State-of-Authorship.pdf
  40. Kliegl R (2016): A Vision of Scientific Communication. In: Weingart P & Taubert N (Eds.): Wissenschaftliches Publizieren. Berlin, Boston: De Gruyter. https://www.degruyter.com/view/books/9783110448115/9783110448115-011/9783110448115-011.x
  41. Bambey D (2016): Fachliche Publikationskulturen und Open Access. Fächerübergreifende Entwicklungstendenzen und Spezifika der Erziehungswissenschaft und Bildungsforschung. PhD Thesis. Technical University Darmstadt. http://tuprints.ulb.tu-darmstadt.de/5603/
  42. Herb U (2016): Altmetrics zwischen Revolution und Dienstleistung: Eine methodische und konzeptionelle Kritik. Scinoptica. https://www.scinoptica.com/2016/11/altmetrics-zwischen-revolution-und-dienstleistung%e2%80%af-eine-methodische-und-konzeptionelle-kritik/
  43. Jessie D & Polly T (2016): Being a Scholar in the Digital Era: Transforming Scholarly Practice for the Public Good. Policy Press. ISBN: 978144732968
  44. Wimmer EN, Rethlefsen ML, Jarvis C, Shipman JP (2016): Understanding Research Impact: A Review of Existing and Emerging Tools for Nursing. Journal of Professional Nursing. 32(6): 401–411. DOI: 10.1016/j.profnurs.2016.05.005
  45. McKiernan EC, Bourne PE, Brown CT, Buck S, Kenall A, Lin J, McDougall D, et al. (2016): How open science helps researchers succeed. eLife, 5. DOI 10.7554/eLife.16800
  46. Lazic SE (2016): Experimental Design for Laboratory Biologists: Maximising Information and Improving Reproducibility. Cambridge University Press. ISBN: 978-1107424883
  47. Gent DH, Esker PD, Kriss AB (2018): Statistical Power in Plant Pathology Research. Phytopathology. 108(1): 15–22. DOI: 10.1094/PHYTO-03-17-0098-LE
  48. Maizey L (2016): Controlling for non-inhibitory processes in response inhibition research. PhD Thesis, Cardiff University
  49. Poirazi P, Belin D, Gräff J, Hanganu-Opatz IL, López-Bendito G (2016): Balancing family with a successful career in neuroscience. Eu J Neurosci. 44(2): 1797–1803. DOI: 10.1111/ejn.13280
  50. Meadows M, Dietz T, Vandermotten C (2016): A perspective on problems and prospects for academic publishing in Geography. Geo: Geography and Environment. 3(1): e00016. 10.1002/geo2.16
  51. Spezi V, Wakeling S, Pinfield S, Creaser C, Fry J, Willett P (2017): Open-access mega-journals. Journal of Documentation. 73(2): 263–283. DOI: 10.1108/JD-06-2016-0082
  52. Kulczycki E & Rozkosz EA (2017): Does an expert-based evaluation allow us to go beyond the Impact Factor? Experiences from building a ranking of national journals in Poland. Scientometrics. 111(1): 417–442. DOI: 10.1007/s11192-017-2261-x
  53. Taylor L & Willett P (2017): Comparison of US and UK rankings of LIS journals. Aslib Journal of Information Management. 69(3): 354–367. DOI: 10.1108/AJIM-08-2016-0136
  54. Amrhein V, Korner-Nievergelt F, Roth T (2017): The earth is flat (p > 0.05): significance thresholds and the crisis of unreplicable research. PeerJ. 5: e3544. DOI: 10.7717/peerj.3544
  55. Munafò MR (2017): Promoting reproducibility in addiction research. Addiction. 112(9): 1519–1520. DOI: 10.1111/add.13853
  56. Hanel PHP, Haase J (2017): Predictors of Citation Rate in Psychology: Inconclusive Influence of Effect and Sample Size. Frontiers in Psychology, 8. DOI: 10.3389/fpsyg.2017.01160
  57. Song M, Kim S & Lee K (2017): Ensemble analysis of topical journal ranking in bioinformatics. Journal of the Association for Information Science and Technology. 68(6): 1564–1583. DOI: 10.1002/asi.23840
  58. van Mil JWF, Green J (2017): Citations and science. International Journal of Clinical Pharmacy. 39(5): 977–979. DOI: 10.1007/s11096-017-0539-y
  59. Molchanovа A, Chunikhina N, Strielkowski W (2017): Innovations and academic publishing: who will cast the first stone? Marketing and Management of Innovations. 4: 40–48. DOI: 10.21272/mmi.2017.4-03
  60. Are C, Yanala U, Malhotra G, Hall B, Smith L, Wyld L, Cummings C, et al. (2017): Global Curriculum in Research Literacy for the Surgical Oncologist. Annals of Surgical Oncology. 25(3): 604–616. DOI: 10.1245/s10434-017-6277-5
  61. Vogl S, Scherndl T, Kühberger A (2018): #Psychology: a bibliometric analysis of psychological literature in the online media. Scientometrics. DOI: 10.1007/s11192-018-2727-5
  62. Polonioli A (2016): New Issues for New Methods: Ethical and Editorial Challenges for an Experimental Philosophy. Science and Engineering Ethics. 23(4): 1009–1034. DOI: 10.1007/s11948-016-9838-2
  63. Contreras FG, Buzeta LP, Pedraja-Rejas L (2015): Importancia de las publicaciones académicas: algunos problemas y recomendaciones a tener en cuenta. Idesia (Arica). 33(4): 111–119. DOI: 10.4067/S0718-34292015000400014
  64. Moore S, Neylon C, Paul Eve M, Paul O’Donnell D, Pattinson D (2017): “Excellence R Us”: university research and the fetishisation of excellence. Palgrave Communications. 3:16105. DOI: 10.1057/palcomms.2016.105
  65. Brueckner M, Spencer R, Paull M, Girardi A, Klom S (2017): Journeying towards responsible citizenship and sustainability. In: Arevalo JA, Mitchell SF (Eds): Handbook of Sustainability in Management Education. Edward Elgar Publishing. DOI: 10.4337/9781785361241.00026
  66. Smaldino PE, McElrath R (2016): The Natural Selection of Bad Science. arXiv:1605.09511 [physics.soc-ph]
  67. Reinhart A (2016): Statistics Done Wrong: The Woefully Complete Guide. No Starch Press, 176p, ISBN-13: 978-1593276201
  68. Poirazi P, Belin D, Gräff J, Hanganu-Opatz I, López-Bendito G (2016): Balancing family with a successful career in neuroscience. Eur J Neurosci. 2016 May 21. doi: 10.1111/ejn.13280
  69. Branch TA, Linnell AE (2016): What makes some fisheries references highly cited? Fish and Fisheries. doi: 10.1111/faf.12160
  70. Wimmer EN, Rethlefsen ML, Jarvis C, Shipman JP (2016): Understanding Research Impact: A Review of Existing and Emerging Tools for Nursing. J Prof Nurs. doi: 10.1016/j.profnurs.2016.05.005
  71. Schmidt N (2016): Tackling complexity in an interdisciplinary scholarly network: Requirements for semantic publishing. First Monday, 21(5). doi: 10.5210/fm.v21i5.6102
  72. Rentier B (2016): Open Science: a revolution in sight? Interlending & Document Supply. http://hdl.handle.net/2268/198865
  73. Huber WD (2016): Deep Impact: Impact Factors and Accounting Research. Int J Crit Acc 8(1), 56-67
  74. Polonioli, A. (2016): Metrics, flawed indicators, and the case of philosophy journals. Scientometrics 106 (1): 253–261 doi: 10.1007/s11192-016-1941-2
  75. Shanahan DR (2016): Auto-correlation of journal impact factor for consensus research reporting statements: a cohort study. PeerJ 4:e1887 doi: 10.7717/peerj.1887
  76. Meadows M, Dietz T, Vandermotten C (2016): A perspective on problems and prospects for academic publishing in Geography. Geo: Geography and Environment, 3(1): e00016, DOI: 10.1002/geo2.16
  77. Ralph P (2016): Practical Suggestions for Improving Scholarly Peer Review Quality and Reducing Cycle Times, Communications of the AIS, Volume 38, Article 13
  78. Tracz V, Lawrence R (2016): Towards an open science publishing platform. F1000Research, 5:130, DOI: 10.12688/f1000research.7968.1
  79. Carrier JG (2016): After the Crisis: Anthropological Thought, Neoliberalism and the Aftermath, (Routledge Studies in Anthropology), ISBN: 978-1138100855
  80. Starbuck WH (2016): 60th Anniversary Essay: How Journals Could Improve Research Practices in Social Science. Administrative Science Quarterly, DOI: 10.1177/0001839216629644
  81. Salager-Meyer F (2015): Peripheral scholarly journals: From locality to globality. Ibérica 30: 15-36
  82. Margraf J (2015): Zur Lage der Psychologie. Psychologische Rundschau. 66(1): 1–30. DOI: 10.1026/0033-3042/a000247
  83. Erikson MG, Erlandson P, Erikson M (2015): Academic misconduct in teaching portfolios. Int. J Acad Dev. 20(4): 345-354
  84. Jones RT (2015): Presidential address: Truth and error in scientific publishing. Journal of the Southern African Institute of Mining and Metallurgy, 115(9): 799-816
  85. Contreras FG, Buzeta LP, Pedraja-Rejas L (2015): Importancia de las publicaciones académicas: algunos problemas y recomendaciones a tener en cuenta. Idesia (Arica), 33: 111–119, DOI: 10.4067/S0718-34292015000400014
  86. Hernandez-Alvarez M, Gomez JM (2015): Citation Impact Categorization: For Scientific Literature. 2015 IEEE 18th International Conference on Computational Science and Engineering, DOI: 10.1109/cse.2015.21
  87. Nieminen P, Abass K, Vähäkanga K, Rautio A (2015): Statistically non-significant papers in environmental health studies included more outcome variables, Biomed Environ Sci, 28(9): 666-673, DOI: 10.3967/bes2015.093
  88. Casadevall A, Fang FC (2015): Impacted Science: Impact Is Not Importance. mBio, 6(5): e01593-15, DOI: 10.1128/mBio.01593-15
  89. Herb U (2015): Open Science in der Soziologie: Eine interdisziplinäre Bestandsaufnahme zur offenen Wissenschaft und eine Untersuchung ihrer Verbreitung in der Soziologie. Verlag Werner Hülsbusch, ISBN: 978-3-86488-083-4
  90. Bowen A, Casadevall A (2015): Increasing disparities between resource inputs and outcomes, as measured by certain health deliverables, in biomedical research. Proc Natl Acad Sci U S A, 112: 11335–11340, DOI: 10.1073/pnas.1504955112
  91. Probst TM, Hagger MS (2015): Advancing the Rigour and Integrity of Our Science: The Registered Reports Initiative. Stress Health, 31: 177–179, DOI: 10.1002/smi.2645
  92. Van Hezewijk R (2015): Old socks and the end of theory, ISTP 30th Biennual Conference, Coventry (UK)
  93. Eve MP (2015): Open Access publishing and scholarly communications in non-scientific disciplines. Online Inf Rev, 39: 717–732, DOI: 10.1108/OIR-04-2015-0103
  94. Louys J (2015): Palaeontologia Electronica in an increasingly open-access world, Palaeontologia Electronica, 18.2.2E
  95. Hunter P (2015): Web 2.0 and academic debate: Social media challenges traditions in scientific publishing. EMBO rep. 16: 787–790, DOI: 10.15252/embr.201540721
  96. Teixeira da Silva JA (2015): Issues in Science Publishing. What’s Hot and What’s not? KOME – An International Journal of Pure Communication Inquiry, 3(1): 81-88
  97. LeHuray A (2015): In response to Bales (2014). Integr Environ Assess Manag, 11: 185–187, DOI: 10.1002/ieam.1619
  98. Fahrenberg J (2015): Theoretische Psychologie: Eine Systematik der Kontroversen, Pabst Science Publ, ISBN: 978-3-95853-077-5, 832pp
  99. Wolf BM, Häring AM, Heß J (2015): Strategies towards Evaluation beyond Scientific Impact. Pathways not only for Agricultural Research. Organic Farming, 1(1): 3-18 , DOI: 10.12924/of2015.01010003
  100. Génova G, Astudillo H, Fraga A (2015): The Scientometric Bubble Considered Harmful. Sci Eng Ethics, 22: 227–235, DOI: 10.1007/s11948-015-9632-6
  101. Hery L, Weill C, Macé B, Benoist D, Boutet A, Defaux H, Nguyen C, Piñol-Domenech N, Fontaine-Martinelli F, Legendre O (2015): Médecins, bibliothécaires : pourquoi travailler ensemble? <hal-01115703>
  102. Margraf J (2015): Zur Lage der Psychologie. Psychologische Rundschau, 66: 1–30, DOI: 10.1026/0033-3042/a000247
  103. Jane EA (2015): Flaming? What flaming? The pitfalls and potentials of researching online hostility. Ethics Inf Technol. 17(1): 65-87, DOI: 10.1007/s10676-015-9362-0
  104. Madan CR (2015): Every scientist is a memory researcher: Suggestions for making research more memorable. F1000Research, 4:19, DOI: 10.12688/f1000research.6053.1
  105. Eslami M, Rickman A, Vaccaro K, Aleyasen A, Vuong A, Karahalios K, Hamilton K, Sandvig C (2015): “I always assumed that I wasn’t really that close to [her].”: Reasoning about Invisible Algorithms in News Feeds. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems – CHI ’15, DOI: 10.1145/2702123.2702556.
  106. Wolf B, Heß J (2015): Veränderungen der Forschungsevaluierung–Chancen für eine ökologische Agrarforschung mit gesellschaftlicher Wirkung. In: Häring AM, Hörning B, Hoffmann-Bahnsen R, Luley H, Luthardt V, Pape J, Trei G (eds.): Am Mut hängt der Erfolg – Rückblicke und Ausblicke auf die ökologische Landbewirtschaftung. Beiträge zur 13. Wissenschaftstagung Ökologischer Landbau, Hochschule für nachhaltige Entwicklung Eberswalde, 17.-20. März 2015, Verlag Dr. Köster, Berlin
  107. Campanario JM (2014): Analysis of the distribution of cited journals according to their positions in the h-core of citing journal listed in Journal Citation Reports. J Informetrics, 8: 534–545, DOI: 10.1016/j.joi.2014.04.007
  108. Engler JO, Husemann M (2014): Data constraints, bias and the (mis-)use of scientometrics for predicting academic success: A comment on van Dijk et al. Proceedings of Peerage of Science, DOI: 10.14726/procpos.2014.e8
  109. Black KJ (2014): F1000Research: Tics welcomes you to 21st century biomedical publishing. F1000Res. 3:272, DOI: 10.12688/f1000research.5664.1
  110. Liao H, Xiao R, Cimini G, Medo M (2014): Network-Driven Reputation in Online Scientific Communities. PLoS ONE 9(12):e112022, DOI: 10.1371/journal.pone.0112022
  111. Knudson D (2014): What is a kinesiology journal? 1 . Comprehensive Psychology, 3, Article 20, DOI: 10.2466/03.CP.3.20
  112. Coates H (2014): Ensuring research integrity: The role of data management in current crises, College & Research Libraries News, 75(11): 598-601
  113. Wáng YX, Arora R, Choi Y, Chung HW, Egorov VI, Frahm J, Kudo H, Kuyumcu S, Laurent S, Loffroy R, Maurea S, Morcos SK, Ni Y, Oei EH, Sabarudin A, Yu X (2014): Implications of Web of Science journal impact factor for scientific output evaluation in 16 institutions and investigators’ opinion, Quant Imaging Med Surg. 4(6):453-61. DOI : 10.3978/j.issn.2223-4292.2014.11.16.
  114. Fraley RC, Vazire S (2014): The N-Pact Factor: Evaluating the Quality of Empirical Journals with Respect to Sample Size and Statistical Power. PLoS ONE 9(10):e109019, DOI: 10.1371/journal.pone.0109019
  115. Hamilton K, Karahalios K, Sandvig C, Eslami M (2014): A path to understanding the effects of algorithm awareness. Proceedings of the extended abstracts of the 32nd annual ACM conference on Human factors in computing systems – CHI EA ’14
  116. Arlinghaus R (2014): Are Current Research Evaluation Metrics Causing a Tragedy of the Scientific Commons and the Extinction of University-Based Fisheries Programs? Fisheries 39(5): 212-215
  117. Gasparyan AY, Ayvazyan L, Akazhanov NA, Kitas GD (2014): Self-correction in biomedical publications and the scientific impact. Croat Med J. 55(1):61-72.
  118. Casadevall A, Fang FC (2014): Causes for the persistence of impact factor mania. MBio. 5(2):e00064-14
  119. Schmidt N (2014): Der Goldene Weg des Open Access zum funktionalen Publikationswesen. Handlungsoptionen für die Universität Wien, http://phaidra.univie.ac.at/o:337723
  120. Moustafa K (2014): The Disaster of the Impact Factor. Sci Eng Ethics doi: 10.1007/s11948-014-9517-0
  121. Jawaid SA (2014): Striving for improved visibility and increased citation through coverage by PubMed Central (PMC). Pak J Med Sci 30(1):1-2
  122. Casadevall A, Fang FC (2014): Specialized Science. Infect Immun DOI: 10.1128/IAI.01530-13
  123. Schreiber M (2014): Is it Possible to Measure Scientific Performance with the h-Index or with Another Variant from the Hirsch Index Zoo? JUnQ, 4, 1, 5–10
  124. Chinamasa E (2014): Journal impact factor: expired prescription for academics research output. International Journal of Advanced Research in Management and Social Sciences. 3(8): 1-16
  125. Ware JJ, Munafò MR (2014) Significance chasing in research practice: causes, consequences and possible solutions. Addiction, 110: 4–8, DOI: 10.1111/add.12673
  126. Chambers CD, Feredoes E, Muthukumaraswamy SD, Etchells P (2014): Instead of “playing the game” it is time to change the rules: Registered Reports at AIMS Neuroscience and beyond. AIMS Neuroscience 1(1): 4-17, DOI: 10.3934/Neuroscience2014.1.4
  127. Lidén K, & Eriksson G (2013): Archaeology vs. archaeological science: Do we have a case? Current Swedish Archaeology. 21:11–20.
  128. Larsson ÅM (2013): Science and prehistory: Are we mature enough to handle it? Curr Swed Arch. 21: 27-33
  129. Vaudano E (2013): The innovative medicines initiative: a public private partnership model to foster drug discovery. Comput Struct Biotechnol J, 6: 1–7, DOI: 10.5936/csbj.201303017
  130. Fear KM (2013): Measuring and anticipating the impact of data reuse. PhD thesis, University of Michigan
  131. Mani J, Makarevic J, Juengel E, Ackermann H, Nelson K, et al. (2013): I Publish in I Edit? – Do Editorial Board Members of Urologic Journals Preferentially Publish Their Own Scientific Work? PLoS ONE 8(12): e83709
  132. Park I-U, Peacey MW, Munafò MR (2013): Modelling the effects of subjective and objective decision making in scientific peer review. Nature 506(7486):93-96
  133. Vessuri H, Guedon J-C, Cetto AM (2013): Excellence or quality? Impact of the current competition regime on science and scientific publishing in Latin America and its implications for development. Current Sociology doi: 10.1177/0011392113512839
  134. Eisen JA, MacCallum CJ, Neylon C (2013): Expert Failure: Re-evaluating Research Assessment. PLoS Biol 11(10): e1001677
  135. Wellen R (2013): Open Access, Megajournals, and MOOCs: On the Political Economy of Academic Unbundling. SAGE Open 3
  136. Sproat R (2013): TALIP Perspectives. ACM Transactions on Asian Language Information Processing 12: 1–2
  137. Fabry, Götz, Fischer, Martin R. (2013): Die ZMA und der Impact Factor. GMS Z Med Ausbild 30(3):Doc39, doi: 10.3205/zma000882
  138. Herb U, Beucke D (2013): Die Zukunft der Impact-Messung. Social Media, Nutzung und Zitate im World Wide Web. Wissenschaftsmanagement. Zeitschrift für Innovation 19(4), 22–25

Colomb J, Reiter L, Blaszkiewicz J, Wessnitzer J, Brembs B. (2012): Open source tracking and analysis of adult Drosophila locomotion in Buridan’s paradigm with and without visual targets. PLoS One 7(8):e42247
Citations:

  1. Fuenzalida-Uribe N, Campusano JM (2018): Unveiling the Dual Role of the Dopaminergic System on Locomotion and the Innate Value for an Aversive Olfactory Stimulus in Drosophila. Neuroscience. 371:433–444. DOI: 10.1016/j.neuroscience.2017.12.032
  2. Karunanithi S, Troup M, van Swinderen B (2018): Using Drosophila to Understand General Anesthesia: From Synapses to Behavior. In: Eckenhoff RG, Dmochowski IJ (Eds.): Methods in Enzymology (pp. 153–176). Elsevier. DOI: 10.1016/bs.mie.2018.02.003
  3. Gilad T, Koren R, Moalem Y, Subach A, Scharf I (2018): Effect of continuous and alternating episodes of starvation on behavior and reproduction in the red flour beetle. Journal of Zoology. DOI: 10.1111/jzo.12556
  4. Rohde PD, Østergaard S, Kristensen TN, Sørensen P, Loeschcke V, Mackay TFC, Sarup P (2018): Functional Validation of Candidate Genes Detected by Genomic Feature Models. Genes|Genomes|Genetics. 3.200082.2018. DOI: 10.1534/g3.118.200082
  5. Xiao C, Qiu S, Robertson RM (2017): Persistent One-Way Walking in a Circular Arena in Drosophila melanogaster Canton-S Strain. Behavior Genetics. 48(1):80–93. DOI: 10.1007/s10519-017-9881-z
  6. Ferguson L, Petty A, Rohrscheib C, Troup M, Kirszenblat L, Eyles DW, van Swinderen B (2017): Transient Dysregulation of Dopamine Signaling in a Developing Drosophila Arousal Circuit Permanently Impairs Behavioral Responsiveness in Adults. Frontiers in Psychiatry. 8. DOI: 10.3389/fpsyt.2017.00022
  7. Rose J, Cullen DA, Simpson SJ, Stevenson PA (2017): Born to win or bred to lose: aggressive and submissive behavioural profiles in crickets. Animal Behaviour. 123:441–450. DOI: 10.1016/j.anbehav.2016.11.021
  8. Kimura T (2017): Development of automatic tracking methods for the analysis of animal behaviors. PhD thesis, University of Hyogo
  9. Wexler Y, Scharf I (2017): Distinct effects of two separately applied stressors on behavior in the red flour beetle. Behavioural Processes. 145:86–92. DOI: 10.1016/j.beproc.2017.10.008
  10. Gris KV, Coutu J-P, Gris D (2017): Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior. Frontiers in Behavioral Neuroscience. 11. DOI: http://dx.doi.org/10.3389/fnbeh.2017.00141
  11. Qiu S, Xiao C, Meldrum Robertson R (2017): Different age-dependent performance in Drosophila wild-type Canton-S and the white mutant w1118 flies. In: Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology. 206:17–23. Elsevier BV. DOI: 10.1016/j.cbpa.2017.01.003
  12. Hidalgo S, Molina-Mateo D, Escobedo P, Zárate RV, Fritz E, Fierro A, Perez EG, et al. (2017): Characterization of a Novel Drosophila SERT Mutant: Insights on the Contribution of the Serotonin Neural System to Behaviors. ACS Chemical Neuroscience. 8(10):2168–2179. DOI: 10.1021/acschemneuro.7b00089
  13. Scharf I, Wertheimer KO, Xin JL, Gilad T, Goldenberg I, Subach A (2017): Context-dependent effects of cold stress on behavioral, physiological, and life-history traits of the red flour beetle. Insect Science. DOI: 10.1111/1744-7917.12497
  14. Corthals K, Heukamp AS, Kossen R, Großhennig I, Hahn N, Gras H, Göpfert MC, et al. (2017): Neuroligins Nlg2 and Nlg4 Affect Social Behavior in Drosophila melanogaster. Frontiers in Psychiatry. 8. DOI: 10.3389/fpsyt.2017.00113
  15. Geissmann Q, Garcia-Rodriguez L, Beckwith EJ, French AS, Jamasb AR, Gilestro GF (2017): Ethoscopes: An open platform for high-throughput ethomics. PLOS Biology. 15(10): e2003026. DOI: 10.1371/journal.pbio.2003026
  16. Wexler Y, Wertheimer KO, Subach A, Pruitt JN, Scharf I (2017): Mating alters the link between movement activity and pattern in the red flour beetle. Physiological Entomology: 42(4):299–306. DOI: 10.1111/phen.12195
  17. Molina-Mateo D, Fuenzalida-Uribe N, Hidalgo S, Molina-Fernández C, Abarca J, Zárate RV, Escandón M, et al. (2017): Characterization of a presymptomatic stage in a Drosophila Parkinson’s disease model: Unveiling dopaminergic compensatory mechanisms. Biochimica et Biophysica Acta (BBA) – Molecular Basis of Disease. 1863(11):2882–2890. DOI: 10.1016/j.bbadis.2017.07.013
  18. Ehaideb SN, Wignall EA, Kasuya J, Evans WH, Iyengar A, Koerselman HL, Lilienthal AJ, et al. (2016): Mutation of orthologous prickle genes causes a similar epilepsy syndrome in flies and humans. Annals of Clinical and Translational Neurology. 3(9):695–707. DOI: 10.1002/acn3.334
  19. Wexler Y, Subach A, Pruitt JN, Scharf I (2016): Behavioral repeatability of flour beetles before and after metamorphosis and throughout aging. Behav Ecol Sociobiol. DOI: 10.1007/s00265-016-2098-y
  20. Xiao C, Robertson RM (2015): Locomotion Induced by Spatial Restriction in Adult Drosophila. PLOS ONE 10(9):e0135825, DOI: 10.1371/journal.pone.0135825
  21. Girdhar K, Gruebele M, Chemla YR (2015): The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog. PLOS ONE 10(7):e0128668, DOI: 10.1371/journal.pone.0128668
  22. Freeman AAH, Dai H, Sanyal S (2015): Use of Drosophila to Study Restless Legs Syndrome. In: LeDoux MS (ed.): Movement Disorders: Genetics and Models, DOI: 10.1016/B978-0-12-405195-9.00078-0
  23. Giannoni-Guzmán MA, Avalos A, Marrero Perez J, Otero Loperena EJ, Kayim M, Medina JA, Massey SE, Kence M, Kence A, Giray T, Agosto-Rivera JL (2014): Measuring individual locomotor rhythms in honey bees, paper wasps and other similar-sized insects. J Exp Biol. 217: 1307–1315, DOI: 10.1242/jeb.096180
  24. Zenger B, Wetzel S, Duncan J (2014): Acquisition of High-Quality Digital Video of Drosophila Larval and Adult Behaviors from a Lateral Perspective. J Vis Exp. (92):e51981, DOI: 10.3791/51981.
  25. Kodama N, Kimura T, Yonemura S, Kaneda S, Ohashi M, Ikeno H (2014): Automated Analysis of Two-Dimensional Positions and Body Lengths of Earthworms (Oligochaeta); MimizuTrack. PLoS ONE 9(6):e97986, DOI: 10.1371/journal.pone.0097986
  26. Risse B, Berh D, Tao J, Jiang X, Klette R, Klämbt C (2013): Comparison of two 3D tracking paradigms for freely flying insects. EURASIP J Image Vid Proc 57
  27. Timmerman C, Suppiah S, Gurudatta BV, Yang J, Banerjee C, Sandstrom DJ, Corces VG, Sanyal S (2013): The Drosophila Transcription Factor Adf-1 (nalyot) Regulates Dendrite Growth by Controlling FasII and Staufen Expression Downstream of CaMKII and Neural Activity. J Neurosci. 33(29):11916-11931
  28. Raja S (2013): The neuronal basis of spontaneous flight behavior in Drosophila. PhD dissertation, FU Berlin

Pauly D, Chacana PA, Calzado EG, Brembs B, Schade R (2011): IgY technology: extraction of chicken antibodies from egg yolk by polyethylene glycol (PEG) precipitation. J Vis Exp. (51), e3084, DOI: 10.3791/3084
Citations:

  1. Sheng L, He Z, Liu Y, Ma M, Cai Z (2018): Mass spectrometry characterization for N -glycosylation of immunoglobulin Y from hen egg yolk. International Journal of Biological Macromolecules. 108:277–283. DOI: 10.1016/j.ijbiomac.2017.12.012
  2. Kruse T, Biedenkopf N, Hertz EPT, Dietzel E, Stalmann G, López-Méndez B, Davey NE, et al. (2018): The Ebola Virus Nucleoprotein Recruits the Host PP2A-B56 Phosphatase to Activate Transcriptional Support Activity of VP30. Molecular Cell. 69(1):136–145. DOI: 10.1016/j.molcel.2017.11.034
  3. Akbari MR, Ahmadi A, Mirkalantari S, Salimian J (2018): Anti- Vibrio cholerae IgY Antibody Inhibits Mortality in Suckling Mice Model. Journal of the National Medical Association. 110(1): 84–87. DOI: 10.1016/j.jnma.2017.04.001
  4. Sheng L, He Z, Chen J, Liu Y, Ma M, Cai Z (2017): The impact of N-glycosylation on conformation and stability of immunoglobulin Y from egg yolk. International Journal of Biological Macromolecules. 96: 129–136. DOI: 10.1016/j.ijbiomac.2016.12.043
  5. Nagaraj S, Ramlal S, Kingston J, Batra HV (2016): Development of IgY based sandwich ELISA for the detection of staphylococcal enterotoxin G (SEG), an egc toxin. International Journal of Food Microbiology. 237:136–141. DOI: 10.1016/j.ijfoodmicro.2016.08.009
  6. Zhai Y, Qu X, Pang B (2017): Preparation of high immunity yolk antibody against Vibrio parahemolyticus and comparison of effectiveness between different extraction methods. Journal of Jilin University Medicine Edition. 43(2): 441-445. DOI:13481/j.1671-587x.20170245
  7. da Rocha DG, Fernandez JH, de Almeida CMC, da Silva CL, Magnoli FC, da Silva OÉ, da Silva WD (2017): Development of IgY antibodies against anti-snake toxins endowed with highly lethal neutralizing activity. European Journal of Pharmaceutical Sciences. 106:404–412. DOI: 10.1016/j.ejps.2017.05.069
  8. Kousted TM, Kalliokoski O, Christensen SK, Winther JR, Hau J (2017): Exploring the antigenic response to multiplexed immunizations in a chicken model of antibody production. Heliyon. 3(3): e00267. DOI: 10.1016/j.heliyon.2017.e00267
  9. Ma, O’Kennedy (n.d.): Generation and optimisation of antibodies for biosensor applications. In: Pranjal C, Ester S: Nanobiosensors for Personalized and Onsite Biomedical Diagnosis (pp. 209–230). Institution of Engineering and Technology. DOI: 10.1049/PBHE001E_ch11
  10. Wang N, Xu Q, Liu Y, Jin Y, Harlina PW, Ma M (2018): Highly efficient extraction and purification of low-density lipoprotein from hen egg yolk. Poultry Science. DOI: 10.3382/ps/pey059
  11. Song D, Qu X, Liu Y, Li L, Yin D, Li J, Xu K, et al. (2017): A Rapid Detection Method of Brucella with Quantum Dots and Magnetic Beads Conjugated with Different Polyclonal Antibodies. Nanoscale Research Letters. 12(1). DOI: 10.1186/s11671-017-1941-z
  12. Liu Y, Zhao C, Fu K, Song X, Xu K, Wang J, Li J (2017): Selective turn-on fluorescence detection of Vibrio parahaemolyticus in food based on charge-transfer between CdSe/ZnS quantum dots and gold nanoparticles. Food Control. 80: 380–387. DOI: 10.1016/j.foodcont.2017.05.032
  13. Shetty P, D’Souza A, CP G (2017): Conjugation of Peroxidase from Brassica oleracea gongylodes for Use as a Label- Prospect of a Novel Enzyme Tag for Immunoassay Systems. International Journal of Applied Sciences and Biotechnology. 5(1): 59. DOI: 10.3126/ijasbt.v5i1.17009
  14. Hussain CNB (2017): Isolation and Estimation of Chicken Immunoglobulins (IgY) from Egg Yolk by Optimizing Polyethylene Glycol (PEG) Precipitation Method. Sch J Agric Vet Sci. 4(7):286-292. DOI: 10.21276/sjavs
  15. Hussain CNB, Rahman MC (2017): Comparative Study on Genetic Variations in Maternal Antibody (IgY) Transfer from Dam to Egg-yolk in Different Meat Lines of Chickens. American Scientific Research Journal for Engineering, Technology, and Sciences. 36(1):357-369
  16. Amro WA, Al-Qaisi W, Al-Razem F (2017): Production and purification of IgY antibodies from chicken egg yolk. Journal of Genetic Engineering and Biotechnology. DOI: 10.1016/j.jgeb.2017.10.003
  17. Lee W, Syed Atif A, Tan SC, Leow CH (2017): Insights into the chicken IgY with emphasis on the generation and applications of chicken recombinant monoclonal antibodies. Journal of Immunological Methods: 447: 71–85. DOI: 10.1016/j.jim.2017.05.001
  18. Cahyaningsih T, Hasmi Pasaribu F, Indrawati A (2017): Production of Specific IgY Staphylococcus aureus Origin from Staphylococcosis Case in Rabbits. Jurnal Ilmu Pertanian Indonesia. 22(1):1–5. DOI: 10.18343/jipi.22.1.1
  19. Li C, Ren H, Schade R, Zhang X (2017): A novel and efficient immunoglobulin Y extraction method using poloxamer-polyethylene glycol. Preparative Biochemistry and Biotechnology. 47(7):739–743. DOI: 10.1080/10826068.2017.1315598
  20. Solhi R, Alebouyeh M, Khafri A, Rezaeifard M, Aminian M (2017): In vitro evaluation of cross-strain inhibitory effects of IgY polyclonal antibody against H. pylori. Microbial Pathogenesis. 110: 682–687. DOI: 10.1016/j.micpath.2017.03.025
  21. Gaetani C, Ambrosi E, Ugo P, Moretto L (2017): Electrochemical Immunosensor for Detection of IgY in Food and Food Supplements. Chemosensors. 5(1): 10. DOI: 10.3390/chemosensors5010010
  22. Budama-Kilinc Y, Cakir-Koc R, Ozgun Eren G (2017): Synthesis and Characterization of Gold Nanoparticles-Antibody Enzyme Conjugate for use in Influenza a Spesific Nano-ELISA. Presented at the The 3rd World Congress on New Technologies. DOI: 10.11159/icnfa17.140
  23. Júnior AF, Santos JP, Bassi PB, Bittar JFF, Bittar ER (2017): IgY-Technology Applied to Studies of Toxoplasma gondii Infection. In: Toxoplasmosis. DOI: 10.5772/67997
  24. Li C, Zhang Y, Eremin SA, Yakup O, Yao G, Zhang X (2017): Detection of kanamycin and gentamicin residues in animal-derived food using IgY antibody based ic-ELISA and FPIA. Food Chemistry. 227:48–54. DOI: 10.1016/j.foodchem.2017.01.058
  25. Sert M, Cakir Koc R, Budama Kilinc Y (2017): Novel Fitc-Labeled Igy Antibody: Fluorescence Imaging Toxoplasma Gondii In Vitro. Scientific Reports. 7(1). DOI: 10.1038/s41598-017-00930-1
  26. Łupicka-Słowik A, Psurski M, Grzywa R, Bobrek K, Smok P, Walczak M, Gaweł A, et al. (2017): Development of Adenosine Deaminase-Specific IgY Antibodies: Diagnostic and Inhibitory Application. Applied Biochemistry and Biotechnology. 184(4): 1358–1374. DOI: 10.1007/s12010-017-2626-x
  27. Toso RE, Neher BD, Alvarez Rubianes NJM, Toribio MS, Boeris MA, Gastaldo MF, et al. (2016): Obtaining, purification and characterization of specific immunoglobulin Y with diagnostic and prophylactic aims. Ciencia Veterinaria. 18(1): 49–58. DOI: 10.19137/cienvet2016-1814
  28. Brown CD (2016): Treatment and Prevention of Human Rotavirus (HRV) in Developing Countries: The Potential of Avian Immunoglobulin Y. Senior thesis, Liberty University
  29. Murilla G, Karanja W, Arusei J, Mdachi R (2016): Development of Immunoassays for Selected Antibiotics for the Detection and Monitoring of the Drug Residues in Livestock and Livestock Products. http://inis.iaea.org/Search/search.aspx?orig_q=RN:48018547
  30. Petrec O, Cătana N, Ghișe A, Stancu A (2016): Using of Pappenheim stain for highlighting the reovirus pathological lesions. Universitatea de Stiinte Agricole a Banatului Timisoara, Medicina Veterinara. 49(3):123–128. https://www.cabdirect.org/cabdirect/abstract/20163322213
  31. Borhani K, Mohabati Mobarez A, Khabiri AR, Behmanesh M, Khoramabadi N (2016): Inhibitory effects of rHP-NAP IgY against Helicobacter pylori attachment to AGS cell line. Microb Pathog. 97:231-235. doi: 10.1016/j.micpath.2016.06.004
  32. Teimoori S, Arimatsu Y, Laha T, Kaewkes S, Sereerak P, Sripa M, Tangkawattana S, Brindley PJ, Sripa B (2016): Chicken IgY-based coproantigen capture ELISA for diagnosis of human opisthorchiasis. Parasitol Int. pii: S1383-5769(16)30093-9. doi: 10.1016/j.parint.2015.10.011
  33. Agrawal R, Hirpurkar SD, Sannat C, Gupta AK (2016): Comparative study on immunoglobulin Y transfer from breeding hens to egg yolk and progeny chicks in different breeds of poultry. Vet World. 9(4):425-431. doi: 10.14202/vetworld.2016.425-431
  34. Korzyukov Y, Hetzel U, Kipar A, Vapalahti O, Hepojoki J (2016): Generation of Anti-Boa Immunoglobulin Antibodies for Serodiagnostic Applications, and Their Use to Detect Anti-Reptarenavirus Antibodies in Boa Constrictor. PLoS ONE 11(6): e0158417. doi:10.1371/journal.pone.0158417
  35. Dietzel E, Schudt G, Krähling V, Matrosovich M, Becker S (2016): Functional Characterization of Adaptive Mutations during the West African Ebola Virus Outbreak. Journal of Virology. 91(2): e01913-16. DOI: 10.1128/JVI.01913-16
  36. Börstler J, Engel D, Petersen M, Poggensee C, Jansen S, Schmidt-Chanasit J, Lühken R (2016): Surveillance of maternal antibodies against West Nile virus in chicken eggs in South-West Germany. Trop Med Int Health. 21(5): 687-690. doi: 10.1111/tmi.12676
  37. Zhang X, Diraviyam T, Li X, Yao G, Michael A (2016): Preparation of chicken IgY against recombinant E2 protein of bovine viral diarrhea virus (BVDV) and development of ELISA and ICA for BVDV detection. Bioscience, Biotechnology, and Biochemistry. 80(12):2467–2472. DOI: 10.1080/09168451.2016.1217144
  38. Cakir-Koc R (2016): Production of anti-SAG1 IgY antibody against Toxoplasma gondii parasites and evaluation of antibody activity by ELISA method. Parasitol Res. [Epub ahead of print] PMID: 27079459
  39. Pauly D, Hanack K (2015): How to avoid pitfalls in antibody use. F1000Res. 4:691. doi: 10.12688/f1000research.6894.1
  40. Brandon DL, Korn AM (2015): Immunosorbent analysis of toxin contamination in milk and ground beef using IgY-based ELISA, Food and Agricultural Immunology. DOI: 10.1080/09540105.2015.1126809
  41. Krähling V, Becker D, Rohde C, Eickmann M, Eroglu Y, Herwig A, Kerber R, Kowalski K, Vergara-Alert J, Becker S; European Mobile Laboratory consortium (2015): Development of an antibody capture ELISA using inactivated Ebola Zaire Makona virus. Med Microbiol Immunol, DOI: 10.1007/s00430-015-0438-6
  42. Gandhimathi C, Sentila R, Michael A (2015): Protection against experimental dental caries in rats with chicken egg yolk antibodies (IgY) generated against Streptococcus mutans. World Journal of Pharmaceutical Research, 4(6): 1564-1581, ISSN 2277– 7105
  43. Mudili V, Makam SS, Sundararaj N, Siddaiah C, Gupta VK, Rao PV (2015): A novel IgY-Aptamer hybrid system for cost-effective detection of SEB and its evaluation on food and clinical samples. Sci Rep 5:15151, DOI: 10.1038/srep15151
  44. Müller S, Schubert A, Zajac J, Dyck T, Oelkrug C (2015) IgY antibodies in human nutrition for disease prevention. Nutr J. 14: 109, DOI: 10.1186/s12937-015-0067-3
  45. Borhani K, Mobarez AM, Khabiri AR, Behmanesh M, Khoramabadi N (2015): Production of specific IgY Helicobacter pylori recombinant OipA protein and assessment of its inhibitory effects towards attachment of H. pylori to AGS cell line . Clin Exp Vaccine Res, 4: 177, DOI: 10.7774/cevr.2015.4.2.177
  46. Júnior WF, Cano R, Totola AH, Carvalho LM, Cerri MO, Coimbra JS, Carvalho GG, Carvalho BM (2015): Adsorption of immunoglobulin Y in supermacroporous continuous cryogel with immobilized Cu2+ ions. J Chromatography A, 1395: 16–22, DOI: 10.1016/j.chroma.2015.03.052
  47. Sampaio LC, Baldissera MD, Grando TH, Gressler LT, Capeleto Dde M, de Sa MF, de Jesus FP, dos Santos AG Jr, Anciuti AN, Colonetti K, Stainki DR, Monteiro SG (2014): Production, purification and therapeutic potential of egg yolk antibodies for treating Trypanosoma evansi infection. Vet Parasitol. 204: 96–103, DOI: 10.1016/j.vetpar.2014.05.032
  48. Tong C, Geng F, He Z, Cai Z, Ma M (2014): A simple method for isolating chicken egg yolk immunoglobulin using effective delipidation solution and ammonium sulfate. Poult Sci. 94: 104–110, DOI: 10.3382/ps/peu005
  49. Gabriel F, Accoceberry I, Bessoule JJ, Salin B, Lucas-Guérin M, Manon S, Dementhon K, Noël T (2014): A Fox2-Dependent Fatty Acid ß-Oxidation Pathway Coexists Both in Peroxisomes and Mitochondria of the Ascomycete Yeast Candida lusitaniae. PLoS ONE 9(12):e114531, DOI: 10.1371/journal.pone.0114531
  50. Winkelbach A, Günzel D, Schulz C, Wuertz S (2015): Differences in IgY gut absorption in gastric rainbow trout (Oncorhynchus mykiss) and agastric common carp (Cyprinus carpio) assessed in vivo and in vitro. Comp Biochem Physiol C Toxicol Pharmacol, 167: 58–64, DOI: 10.1016/j.cbpc.2014.09.001
  51. Gandhimathi C, Michael A (2014): In vitro neutralization of virulence properties of Streptococcus mutans using chicken eggyolk antibodies (IgY). Int J Pharm Bio Sci, 5(2): 498-508
  52. Winkelbach A, Schade R, Schulz C, Wuertz S (2014): Comparison of oral, rectal and intraperitoneal administration of IgY antibodies in passive immunization of rainbow trout (Oncorhynchus mykiss). Aquacult Int 23: 427–438, DOI: 10.1007/s10499-014-9823-1
  53. Lee HY, Abeyrathne ED, Choi I, Suh JW, Ahn DU (2014): Sequential separation of immunoglobulin Y and phosvitin from chicken egg yolk without using organic solvents. Poult Sci. 93: 2668–2677, DOI: 10.3382/ps.2014-04093
  54. Dai YC, Zhang XF, Tan M, Huang P, Lei W, Fang H, Zhong W, Jiang X (2013): A dual chicken IgY against rotavirus and norovirus. Antiviral Res. 97: 293–300, DOI: 10.1016/j.antiviral.2012.12.011
  55. Santos FN, Brum BC, Cruz PB, Molinaro CM, Silva VL, Chaves SA de M (2014): Production and characterization of IgY against canine IgG: prospect of a new tool for the immunodiagnostic of canine diseases. Braz Arch Biol Tech, 57(4): 523-531
  56. Sampaio LCL, Baldissera MD, Sagrillo MB, Heres TDS, Oliveira CB, Stainki DR, Monteiro SG (2014): In vitro cytotoxicity and genotxicity of chicken egg yolk antibodies (IgY) against Trypanosoma evansi in human lymphocytes. Int J Pharm Pharm Sci, 6(3): 167-170
  57. Priyanka BS, Abhijith KS, Rastogi NK, Raghavarao KSMS, Thakur MS (2014): Integrated Approach for the Extraction and Purification of IgY from Chicken Egg Yolk. Sep Sci Techn 49:562–568
  58. Diraviyam T, Menaka M, Mahenthiran R, Michael A (2013): Generation and physicochemical characterization of chicken egg yolk antibodies (IgY) against Salmonella typhimurium. Int J Pharm Bio Sci 4(4): B343-B350
  59. Asemota H, Curtello S, Vaillant AAJ, Mohammed W, Vuma S, Rao AV C, Kurhade A, Kissoon S, Smikle M, Wisdom B, Kurhade G (2013): Purification of Avian IgY with Trichloroacetic Acid (TCA). J Chromat Separ Tech 04
  60. Reddy PK, Shekar A, Kingston JJ, Sripathy MH, Batra H. (2013): Evaluation of IgY capture ELISA for sensitive detection of Alpha hemolysin of Staphylococcus aureus without staphylococcal protein A interference. J Immunol Meth 391(1-2):31-38
  61. Bellingeri RV, Busso L, Alustiza FE, Picco NY, Molinero DP, Grosso MC, Motta CE, Vivas AB (2013): Characterization of egg yolk immunoglobulin (IgY) against enterotoxigenic Escherichia coli and evaluation of its effects on bovine intestinal cells. Afr J Microbiol Res 7(5): 398-405
  62. Heinrich D (2012): Substitution humaner Seren auf Basis der IgY-Technologie für die immunologische in vitro-Diagnostik. PhD Thesis, Hamburg University. http://ediss.sub.uni-hamburg.de/volltexte/2013/6315/
  63. Dai YC, Zhang XF, Tan M, Huang P, Lei W, Fang H, Zhong W, Jiang X (2012): A dual chicken IgY against rotavirus and norovirus. Antiviral Res. doi:pii: S0166-3542(12)00291-4. 10.1016/j.antiviral.2012.12.011. [Epub ahead of print]
  64. Tan SH, Mohamedali A, Kapur A, Baker MS (2012): Ultradepletion of Human Plasma using Chicken Antibodies: A Proof of Concept study. J Proteome Res. DOI: 10.1021/pr3007182
  65. Niederstadt L, Hohn O, Dorner BG, Schade R, Bannert N. (2012): Stimulation of IgY responses in gene gun immunized laying hens by combined administration of vector DNA coding for the target antigen Botulinum toxin A1 and for avian cytokine adjuvants. J Immunol Methods. 382(1-2):58-67
  66. Niederstadt L, Schade R (2012): IgY technology: What are polyclonal avian antibodies and what can they do? BioSpektrum 18(2): 174-177
  67. Tan SH, Mohamedali A, Kapur A, Lukjanenko L, Baker MS (2012): A novel, cost-effective and efficient chicken egg IgY purification procedure. J Immunol Methods. 380(1-2):73-76
  68. Niederstadt L (2012): Herstellung von DNA induzierten mono-/polyklonalen Antikörpern, zur Schnelldetektion von hochpathogenen viralen Erregern und bioterroristisch relevanten Toxinen. PhD thesis, Freie Universität Berlin, http://www.diss.fu-berlin.de/diss/servlets/MCRFileNodeServlet/FUDISS_derivate_000000011103/Dissertation_Lars_Niederstadt.pdf
Brembs, B. (2011): Spontaneous decisions and operant conditioning in fruit flies. Behav Processes 87: 157-164
Citations:
  1. Shahsavari H, Zare Z, Parsa-Yekta Z, Griffiths P, Vaismoradi M (2018): Learning Situations in Nursing Education: A Concept Analysis. Research and Theory for Nursing Practice. 32(1):23–45. DOI: 10.1891/0000-000Y.32.1.23
  2. Waller BN (2017): The Injustice of Punishment. Routledge Research in Applied Ethics. 8. ISBN: 978-1138506398
  3. Eilam D (2015): The cognitive roles of behavioral variability: idiosyncratic acts as the foundation of identity and as transitional, preparatory, and confirmatory phases. Neurosci Biobehav Rev. 49:55-70. doi: 10.1016/j.neubiorev.2014.11.023
  4. Schultheiss P, Buatois A, Avarguès-Weber A, Giurfa M (2017): Using virtual reality to study visual performances of honeybees. Current Opinion in Insect Science. 24:43–50. DOI: 10.1016/j.cois.2017.08.003
  5. Bartumeus F, Campos D, Ryu WS, Lloret-Cabot R, Méndez V, Catalan J (2016): Foraging success under uncertainty: search tradeoffs and optimal space use. Ecology Letters. 19(11):1299–1313. DOI: 10.1111/ele.12660
  6. Peckmezian T, Taylor PW (2015): A virtual reality paradigm for the study of visually mediated behaviour and cognition in spiders. Anim Behav, 107: 87–95, DOI: 10.1016/j.anbehav.2015.06.018
  7. Weiss SJ & Rosales-Ruiz J (2014): Operant/Classical Conditioning: Comparisons, Intersections and Interactions: The 2014 Winter Conference on Animal Learning and Behavior Focus and Research Seminar Sessions. International Journal of Comparative Psychology. 27(4). https://escholarship.org/uc/item/4c46c9gg
  8. Bell HC (2014): Behavioral Variability in the Service of Constancy, International Journal of Comparative Psychology, 27(2): 338-360
  9. Yapici N, Zimmer M, Domingos AI (2014): Cellular and molecular basis of decision-making. EMBO Rep 15: 1023–1035. DOI: 10.15252/embr.201438993
  10. Haggard P (2014): “Free Will” In: Mele A (ed.): Surrounding Free Will, Philosophy, Psychology, Neuroscience, Oxford University Press. 145. ISBN: 9780199333950
  11. Burgos JE, García-Leal Ó (2015): Autoshaped choice in artificial neural networks: Implications for behavioral economics and neuroeconomics. Behav Processes 114: 63–71. DOI:10.1016/j.beproc.2015.01.010
  12. Cyr A, Boukadoum M, Thériault F (2014): Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot’s controller. Front Neurorobot. 8:21 DOI: 10.3389/fnbot.2014.00021
  13. Méndez V, Campos D, Bartumeus F (2013): Biological Searches and Random Animal Motility. In: Stochastic Foundations in Movement Ecology. Springer Series in Synergetics, DOI: 10.1007/978-3-642-39010-4_9
  14. Nargeot R, Simmers J (2012): Functional Organization and Adaptability of a Decision-Making Network in Aplysia. Front Neurosci. 6:113
  15. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058
Brembs, B. (2011): Towards a scientific concept of free will as a biological trait: spontaneous actions and decision-making in invertebrates. Proc. Roy. Soc. B. 278(1707): 930-939
Citations:
  1. Turri J (2018): Exceptionalist naturalism: Human agency and the causal order. Quarterly Journal of Experimental Psychology. 71(2):396–410. DOI: 10.1080/17470218.2016.1251472
  2. Hadley M (2018): A Deterministic Model of the Free Will Phenomenon. Journal of Consciousness Exploration & Research. 9(1): 19. http://wrap.warwick.ac.uk/98581/
  3. Meincke AS (2018): Bio-Agency and the Possibility of Artificial Agents. In: Christian A, Hommen D, Retzlaff N (Eds.): Philosophy of Science (pp. 65–93). Springer International Publishing. DOI: 10.1007/978-3-319-72577-2_5
  4. Lemos J (2018): A Pragmatic Approach to Libertarian Free Will. Routledge. ISBN: 9781351017251
  5. Cao Y, Li YH, Zou WJ, Li ZP, Shen Q, Liao SK, Ren JG, et al. (2018): Bell Test over Extremely High-Loss Channels: Towards Distributing Entangled Photon Pairs between Earth and the Moon. Physical Review Letters. 120(14). DOI: 10.1103/PhysRevLett.120.140405
  6. Palacios AG, Escobar MJ, Céspedes E (2017): Authors’ Response: Is a Weak Notion of Representation not Compatible with a Contextualist and Enactivist Account of Perception? Constructivist Foundations. 13(1): 135–140.
  7. Chang C, Teo HY, Norma-Rashid Y, Li D (2017): Predator personality and prey behavioural predictability jointly determine foraging performance. Scientific Reports. 7: e40734. DOI: 10.1038/srep40734
  8. Westphal KR (2017): Kant, Causal Judgment & Locating The Purloined Letter. https://www.con-textoskantianos.net/index.php/revista/article/view/268
  9. Quellet J (2017): Le scepticisme à propos du libre arbitre. [Internet]. https://dokupdf.com/download/le-scepticisme-a-propos-du-libre-arbitre-_5a03479dd64ab2b9bdf836db_pdf
  10. Westphal K (2017): Grounds of Pragmatic Realism: Hegel’s Internal Critique and Reconstruction of Kant’s Critical Philosophy. BRILL. ISBN: 9789004360174
  11. Deli E (2017): Consciousness inspired AI system. http://aisb.org.uk/publications/aisbq/AISBQ145.pdf#page=6
  12. Feldman G (2017): Making sense of agency: Belief in free will as a unique and important construct. Social and Personality Psychology Compass. 11(1): e12293. DOI: 10.1111/spc3.12293
  13. Larrosa PNF, Ojea A, Ojea I, Molina VA, Zorrilla-Zubilete MA, Delorenzi A (2017): Retrieval under stress decreases the long-term expression of a human declarative memory via reconsolidation. Neurobiology of Learning and Memory. 142: 135–145. DOI: 10.1016/j.nlm.2017.03.005
  14. Edelman S (2017): Language and other complex behaviors: Unifying characteristics, computational models, neural mechanisms. Language Sciences. 62:91–123. DOI: 10.1016/j.langsci.2017.04.003
  15. Kiroy VN, Bakhtin OM, Minyaeva N, Shaposhnikov D, Aslanyan EV, Lazurenko D (2017): Contingent negative variation during prospective activity. DOI: 7868/S00444677I7020083
  16. éli E, Tozzi A, Peters JF (2017): Relationships between short and fast brain timescales. Cognitive Neurodynamics. 11(6):539–552. DOI: 10.1007/s11571-017-9450-4
  17. Fukutomi M, Ogawa H (2017): Crickets alter wind-elicited escape strategies depending on acoustic context. Scientific Reports. 7(1). DOI: 10.1038/s41598-017-15276-x
  18. Perry CJ, Barron AB, Chittka L (2017): The frontiers of insect cognition. Current Opinion in Behavioral Sciences. 16:111–118. DOI: 10.1016/j.cobeha.2017.05.011
  19. Westphal KR (2017): How Kant Justifies Freedom of Agency (without Transcendental Idealism). European Journal of Philosophy. 25(4):1695–1717. DOI: 10.1111/ejop.12264
  20. Feldman G, Farh JL, Wong KFE (2017): Agency Beliefs Over Time and Across Cultures: Free Will Beliefs Predict Higher Job Satisfaction. Personality and Social Psychology Bulletin. 44(3):304–317. DOI: 10.1177/0146167217739261
  21. Feldman G, Chandrashekar SP (2017): Laypersons’ Beliefs and Intuitions About Free Will and Determinism. Social Psychological and Personality Science. DOI: 10.1177/1948550617713254
  22. Rigato J (2017): Downward causation and supervenience: the non-reductionist’s extra argument for incompatibilism. Philosophical Explorations. 1–16. DOI: 10.1080/13869795.2017.1390146
  23. van Hateren JH (2017): A Unifying Theory of Biological Function. Biological Theory. 12(2):112–126. DOI: 10.1007/s13752-017-0261-y
  24. Avila-Núñez JL, Naya M, Otero LD, Alonso-Amelot ME (2017): Sticky trap predation in the Neotropical resin bug Heniartes stali (Wygodzinsky) (Hemiptera: Reduviidae: Harpactorinae). Journal of Ethology. 35(2):213–219. DOI: 10.1007/s10164-017-0512-1
  25. Mele AR (2017): Aspects of Agency: Decisions, Abilities, Explanations, and Free Will. Oxford University Press. ISBN: 9780190659974
  26. Kabadayi C (2017): Planning and inhibition in corvids. PhD thesis, Lund University. http://lup.lub.lu.se/record/096effc9-8dbf-47f7-ac29-5199b82a42f9
  27. Waller BN (2017): The Injustice of Punishment. Routledge Research in Applied Ethics. 8. ISBN: 978-1138506398
  28. Heinze S, von Philipsborn AC (2017): Editorial overview: Recent advances in insect neuroethology: from sensory processing to circuits controlling internal states. Current Opinion in Insect Science. 24: 4-6. DOI: 10.1016/j.cois.2017.11.006
  29. Westphal KR (2017): Empiricism, Pragmatic Realism & the A Priori in Mind and the World Order. In: Sachs C Olen P (eds.) Contemporary Perspectives on C. I. Lewis: Pragmatism in Transition (London: Palgrave Macmillan, 2017)
  30. Merker B (2016): Insects join the consciousness fray. Animal Sentience: An Interdisciplinary Journal on Animal Feeling. 1(9). http://animalstudiesrepository.org/animsent/vol1/iss9/4
  31. Bronfman ZZ, Ginsburg S (2016): The Evolutionary Origins of Consciousness: Suggesting a Transition Marker. Journal of Consciousness Studies. 23(9–10):7–34
  32. Der R, Martius G (2016): Dynamical self-consistency leads to behavioral development and emergent social interactions in robots. IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EPIROB), Link
  33. Kane R (2016): Moral Responsibility, Reactive Attitudes and Freedom of Will. The Journal of Ethics 20: 229–246
  34. Tomsic D (2016): Visual motion processing subserving behavior in crabs. Current Opinion in Neurobiology. 41:113–121. DOI: 10.1016/j.conb.2016.09.003
  35. Velasque M, Briffa M (2016): The opposite effects of routine metabolic rate and metabolic rate during startle responses on variation in the predictability of behaviour in hermit crabs. (2016). Behaviour. 153(13–14): 1545–1566. DOI: 10.1163/1568539X-00003371
  36. Roskies AL (2016): Decision-Making and Self-Governing Systems. Neuroethics. DOI: 10.1007/s12152-016-9280-9
  37. Rigato JM (2016): The Agent as Her Self: How Taking Agency Seriously Leads to Emergent Dualism. – Rivista Internazionale di Filosofia e Psicologia 7(1): 48–60 (Mimesis). doi: 10.4453/rifp.2016.0005
  38. Lavazza A (2016): Free Will and Neuroscience: From Explaining Freedom Away to New Ways of Operationalizing and Measuring It. Front Hum Neurosci. 10:262. doi: 10.3389/fnhum.2016.00262
  39. Feldman G, Wong KF, Baumeister RF (2016): Bad is freer than good: Positive-negative asymmetry in attributions of free will. Conscious Cogn. 42: 26-40. doi: 10.1016/j.concog.2016.03.005
  40. Feldman G, Chandrashekar SP, Wong KFE (2016): The freedom to excel: Belief in free will predicts better academic performance. Personality and Individual Differences 90: 377–383, doi:10.1016/j.paid.2015.11.043
  41. Kane R (2016): The complex tapestry of free will: striving will, indeterminism and volitional streams, Springer Science, DOI: 10.1007/s11229-016-1046-8
  42. Abed-Vieillard D, Cortot J (2016): When Choice Makes Sense: Menthol Influence on Mating, Oviposition and Fecundity in Drosophila melanogaster. Front Integr Neurosci. 10:5. DOI: 10.3389/fnint.2016.00005
  43. De Ridder D, Vanneste S, Gillett G, Manning P, Glue P, Langguth B (2016): Psychosurgery Reduces Uncertainty and Increases Free Will? A Review. Neuromodulation: Technology at the Neural Interface, DOI: 10.1111/ner.12405.
  44. Mohan A, De Ridder D, Vanneste S (2016): Graph theoretical analysis of brain connectivity in phantom sound perception. Sci. Rep. 6:19683, DOI: 10.1038/srep19683
  45. Lakhan R, Bokkon I, Szőke H (2015): Special Issue Transgenerational Epigenetic Mechanisms, Unconscious Creativity, and Sensory Deprivation: Semi-Free Will in the Extended Dual-aspect Monism Framework. Quantum Biosystems. 6(1): 33-53
  46. Marchetti M, Baralla F (2015): The diminished responsability at the Epimetheus’ time. Rassegna Italiana di Criminologia, 9 (2): 99-107
  47. Waller BN (2015): Restorative Free Will: Back to the Biological Base. Lexington Books, ISBN: 9781498522380, 328pp
  48. Osvath M (2015): Putting flexible animal prospection into context: escaping the theoretical box. Wiley Interdiscip Rev Cogn Sci, 7(1): 5–18, DOI: 10.1002/wcs.1372
  49. Briegel HJ, Müller T (2015): A Chance for Attributable Agency. Minds and Machines, 25: 261–279, DOI: 10.1007/s11023-015-9381-y
  50. Vimal RLP, Bókkon I, Császár N, Vas JP, Szoke H (2015): Transgenerational Epigenetic Mechanisms, Unconscious Creativity, and Sensory Deprivation: Semi-Free Will in the Extended Dual-aspect Monism Framework, Quantum Biosystems, 6(1): 33-53
  51. Kane R (2015): On the role of indeterminism in libertarian free will. Philosophical Explorations, DOI: 10.1080/13869795.2016.1085594
  52. Nadin M, Kurismaa A (2015): From Russia with Love / Russian experimental and empirical contributions informed by an anticipatory perspective. Int J Gen Sys. 44: 615–620, DOI: 10.1080/03081079.2015.1032074
  53. Der R, Martius G (2015): Novel plasticity rule can explain the development of sensorimotor intelligence. Proc Natl Acad Sci U S A, 112: E6224–E6232, DOI: 10.1073/pnas.1508400112
  54. Terao K, Matsumoto Y, Mizunami M (2015): Critical evidence for the prediction error theory in associative learning. Sci. Rep., 5, 8929, DOI: 10.1038/srep08929
  55. Lorange-Millette J (2015): Le problème philosophique des transferts épistémiques entre les sciences naturelles et les théories sociales et politiques, PhD dissertation, Université d’Ottawa
  56. Freitas PM, Andrade F, Novais P (2014): Criminal Liability of Autonomous Agents: From the Unthinkable to the Plausible. In: AI Approaches to the Complexity of Legal Systems. Volume 8929 of the series Lecture Notes in Computer Science pp 145-156
  57. Mele AR (2014): Why science hasn’t disproved free will. Oxford University Press, 112p
  58. Misirlisoy E (2014): Intentional inhibition of human action, PhD dissertation, University College London
  59. Westphal KR (2014): Autonomy, Freedom & Embodiment: Hegel’s Critique of Contemporary Biologism. Hegel Bulletin, 35: 56–83, DOI: 10.1017/hgl.2014.4
  60. Rigato JM, Murakami M, Mainen Z (2014): Spontaneous Decisions and Free Will: Empirical Results and Philosophical Considerations. Cold Spring Harb Symp Quant Biol, 79: 177–184, DOI: 10.1101/sqb.2014.79.024810
  61. Van Hateren JH (2014): Active causation and the origin of meaning. Biol Cybern, 109: 33–46, DOI: 10.1007/s00422-014-0622-6
  62. Christensen K, Papavassiliou D, de Figueiredo A, Franks NR, Sendova-Franks AB (2014): Universality in ant behaviour. J R Soc Interface. 12(102):20140985, DOI: 10.1098/rsif.2014.0985
  63. Bode S, Murawski C, Soon CS, Bode P, Stahl J, Smith PL (2014): Demystifying “free will”: The role of contextual information and evidence accumulation for predictive brain activity. Neurosci Biobehav Rev, 47: 636–645, DOI: 10.1016/j.neubiorev.2014.10.017
  64. Neuringer A (2014): Operant Variability and the Evolution of Volition. International Journal of Comparative Psychology, 27(2). https://escholarship.org/uc/item/0s78k28c#author
  65. Van Hateren JH (2014): The origin of agency, consciousness, and free will. Phenom Cogn Sci, 14: 979–1000, DOI: 10.1007/s11097-014-9396-5
  66. Shields GS (2014): Neuroscience and Conscious Causation: Has Neuroscience Shown that We Cannot Control Our Own Actions? Rev Philos Psychol, 5: 565–582, DOI:10.1007/s13164-014-0200-9
  67. Palmer D (2014): Libertarian Free Will: Contemporary Debates, Oxford University Press, ISBN 978-0-19-986008-1
  68. Delorenzi A, Maza FJ, Suárez LD, Barreiro K, Molina VA, Stehberg J (2014) Memory beyond expression. J Physiol-Paris, 108: 307–322, DOI: 10.1016/j.jphysparis.2014.07.002
  69. Khakhalin,A.S., Koren,D., Gu,J., Xu,H. and Aizenman,C.D. (2014) Excitation and inhibition in recurrent networks mediate collision avoidance in Xenopus tadpoles . European Journal of Neuroscience, 40, 2948–2962, DOI: 10.1111/ejn.12664
  70. Salvador,L.C.M., Bartumeus,F., Levin,S.A. and Ryu,W.S. (2014) Mechanistic analysis of the search behaviour of Caenorhabditis elegans. Journal of The Royal Society Interface, 11, 20131092–20131092, DOI: 10.1098/rsif.2013.1092
  71. Kane R (2014): II-Acting “of One”s Own Free Will’: Modern Reflections on an Ancient Philosophical Problem. Proceedings of the Aristotelian Society (Hardback), 114, 35–55, DOI10.1111/j.1467-9264.2014.00363.x
  72. Smiley J-P, Fernie S, Dainty A (2014): Understanding construction reform discourses. Construction Management and Economics, 32: 804–815, DOI: 10.1080/01446193.2014.909049
  73. Beran O (2014): Wittgensteinian Perspectives on the Turing Test. Studia Philosophica Estonica, 7: 35-57, DOI:10.12697/spe.2014.7.1.02
  74. Loram ID, van de Kamp C, Lakie M, Gollee H, Gawthrop PJ (2014): Does the motor system need intermittent control? Exerc Sport Sci Rev. 42(3): 117-125
  75. Gawthrop P, Loram I, Gollee H, Lakie M (2014): Intermittent control models of human standing: similarities and differences. Biol Cybern doi: 10.1007/s00422-014-0587-5
  76. Walter S (2014): Willusionism, epiphenomenalism, and the feeling of conscious will. Synthese DOI 10.1007/s11229-013-0393-y
  77. Salvador LC, Bartumeus F, Levin SA, Ryu WS (2014): Mechanistic analysis of the search behaviour of Caenorhabditis elegans. J R Soc Interface. 11(92):2013.1092
  78. Shaviro S (2014): The Universe of Things: On Speculative Realism (Posthumanities). University of Minnesota Press. ISBN: 978-0816689262
  79. Griffith M (2013): Free Will: The basics. Routledge. ISBN: 0415562198
  80. Bottini G, Sedda A, Ovadia D (2013): Passato presente e futuro delle neuroscienze e del diritto. Rassegna Italiana di Criminologia
  81. Briffa M (2013): Plastic proteans: reduced predictability in the face of predation risk in hermit crabs. Biol Lett 9(5):20130592
  82. Grandpierre A (2013): Biologically Organized Quantum Vacuum and the Cosmic Origin of Cellular Life. Phenomenology of Space and Time, DOI: 10.1007/978-3-319-02015-0_10
  83. de Ridder D, Verplaetse J, Vanneste S (2013): The predictive brain and the “free will” illusion. Front Psychol. 4, 131
  84. Zilio, D. (2013): Behavioral unit of selection and the operant-respondent distinction: The role of neurophysiological events in controlling the verbal behavior of theorizing about behavior. Psychological Record, 63(4): 895-918
  85. Walsh A (2013): “Criminological Theory: Assessing Philosophical Assumptions” Anderson Publishing, 224p, ISBN: 9781455775477
  86. Stahlman WD, Leising KJ, Garlick D, Blaisdel AP (2013): There Is Room for Conditioning in the Creative Process: Associative Learning and the Control of Behavioral Variability In: Vartanian O, Bristol AS, Kaufman JC (eds.) Neuroscience of Creativity MIT Press 272p ISBN 0262019582, 9780262019583, p45-67
  87. Biro PA, Adriaenssens B (2013): Predictability as a Personality Trait: Consistent Differences in Intraindividual Behavioral Variation. Amer. Nat. 182: 621–629
  88. Gelperin A (2013): Associative memory mechanisms in terrastrial slugs and snails. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p280-290
  89. Tse PU (2013): The Neural Basis of free will: criterial causation. MIT Press, 472p, 978-0-262-01910-1
  90. Stamps JA, Saltz JB, Krishnan VV(2013): Genotypic differences in behavioural entropy: unpredictable genotypes are composed of unpredictable individuals. Anim Behav. 86(3): 641–649
  91. Bottini G, Sedda A, Ovadia D (2013): Past present and future of neuroscience and law. Ital. J. Criminol. 1/2013: 17-22
  92. Martius G, Der R, Ay N (2013): Information driven self-organization of complex robotic behaviors. PLoS One. 8(5):e63400
  93. Briffa M, Bridger D, Biro PA (2013): How does temperature affect behaviour? Multilevel analysis of plasticity, personality and predictability in hermit crabs. Anim Behav 86(1): 47–54
  94. Gomez-Marin, A. (2013): Tools, flies and what to do next. American Institute of Physics. AIP Conf. Proc. 1510: 120-123 doi:10.1063/1.4776508
  95. Wong KFE, Cheng C (2013): Predictable or Not? Individuals’ Risk Decisions Do Not Necessarily Predict Their Next Ones. PLoS ONE 8(2): e56811
  96. Frith C (2013): The psychology of volition. Exp Brain Res. 229(3): 289-299
  97. Lemos J (2013): Freedom, Responsibility, and Determinism: A Philosophical Dialogue. Hackett Publishing Co. ISBN-13: 978-1603849302, 120 pages
  98. Martius G, Der R, Ay N (2013): Information driven self-organization of complex robotic behaviors PLoS One. 8(5):e63400
  99. Radder H, Meynen G (2013): Does the brain “initiate” freely willed processes? A philosophy of science critique of Libet-type experiments and their interpretation. Theory & Psychology, 23(1): 3-21
  100. Nepomnyashchikh VA (2012): Variability in invertebrate behavior and the problem of free will. Zhurnal Obshchei Biologii 73(6): 435-441
  101. Grandpierre A, Kafatos M (2012): Biological Autonomy. Philosophy Study, 2(9): 631-649
  102. Warzecha AK, Rosner R, Grewe J (2012): Impact and sources of neuronal variability in the fly’s motion vision pathway. J Physiol – Paris DOI: 10.1016/j.jphysparis.2012.10.002
  103. Rigoni D, Kühn S, Gaudino G, Sartori G, Brass M (2012): Reducing self-control by weakening belief in free will. Conscious Cogn. 21(3):1482-1490
  104. Zhang S, Si A, Pahl M (2012): Visually guided decision making in foraging honeybees. Front Neurosci. 6:88
  105. Nargeot R, Simmers J (2012): Functional Organization and Adaptability of a Decision-Making Network in Aplysia. Front Neurosci. 6:113
  106. Stamps JA, Briffa M, Biro PA (2012): Unpredictable animals: Individual differences in intraindividual variability (IIV). Anim Behav. 83(6): 1325–1334
  107. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  108. Barham JA (2012): Normativity, agency, and life. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 43(1): 92–103
  109. Miller SM, Ngo TT and van Swinderen B (2012): Attentional switching in humans and flies: rivalry in large and miniature brains. Front. Hum. Neurosci. 5:188. doi: 10.3389/fnhum.2011.00188
  110. Ebeling W, Feistel R (2011) Physics of Self-Organization and Evolution, WILEY-VCH, ISBN: 978-3-527-40963-1
  111. Ansorge U, Horstmann G, Scharlau I (2011): Top-down contingent feature-specific orienting with and without awareness of the visual input. Adv. Cogn. Psych. 7(1): 108-119
  112. de Sousa JC (2011): The uncertainty of free will and agent’s penal responsibility. Orbis: Revista Científica 2(3): 287-312
  113. Barham JA (2011): Teleological Realism in Biology, PhD Thesis, University of Notre Dame, USA.
  114. Mele AR (2011): Libertarianism and Human Agency. Phil Phen Res. 87 ( 1 ) 72-92 DOI: 10.1111/j.1933-1592.2011.00529.x
  115. Schüür F, Haggard P (2011): What are self-generated actions? Conscious Cogn. 20(4): 1697-1704
  116. Koukolík F (2011): Basics of cognitive, affective and social neuroscience. VI. Free will. Prakticky Lekar 91(6): 315-320
  117. Cobbe N (2011): Interspecies Mixtures and the Status of Humanity. In: Suarez A, Huarte J (eds.) Is this cell a human being? Springer, Berlin, Heidelberg. pp129-155, DOI: 10.1007/978-3-642-20772-3_9
  118. Chittka L, Skorupski P (2011): Information processing in miniature brains. Proc. Roy. Soc. B. 278(1707): 885-888
Brembs B.; Pauly D.; Schade R.; Mendoza E.; Pflüger J.; Rybak J.; Scharff C.; Zars T. (2010): The Drosophila FoxP gene is necessary for operant self-learning: implications for the evolutionary origins of language. Soc. Neurosci. Abstr., 704.7
Citations:
  1. Scharff C, Petri J (2011): Evo-devo, deep homology and FoxP2: implications for the evolution of speech and language. Philos Trans R Soc Lond B Biol Sci. 366(1574):2124-2140
van Swinderen, B.; Brembs, B. (2010): Attention-like deficit and hyperactivity in a Drosophila memory mutant. J Neurosci. 30(3): 1003-1014
Citations:
  1. Chakravarti L, Moscato EH, Kayser MS (2017): Unraveling the Neurobiology of Sleep and Sleep Disorders Using Drosophila. In: Current Topics in Developmental Biology Vol. 121 (pp. 253–285). Elsevier. DOI: 10.1016/bs.ctdb.2016.07.010
  2. Widmann A, Artinger M, Biesinger L, Boepple K, Peters C, Schlechter J, Selcho M, et al. (2016): Genetic Dissection of Aversive Associative Olfactory Learning and Memory in Drosophila Larvae. PLOS Genetics. 12(10): e1006378. DOI: 10.1371/journal.pgen.1006378
  3. Adedjeji AA, Vicente-Crespo M (2017): Rejuvenating Research and Training in Biomedical Sciences in Nigeria: Drosophila melanogaster as A Versatile Alternative Model. Archives of Basic and Applied Medicine. 5(1):1–10. http://archivesbamui.com/ojs/index.php/abam/article/view/3
  4. Rohde PD, Madsen LS, Neumann-Arvidson SM, Loeschcke V, Demontis D, Kristensen TN (2016): Testing candidate genes for attention-deficit/hyperactivity disorder in fruit flies using a high throughput assay for complex behavior. Fly (Austin). 10(1):25-34
  5. Bosch DS (2016): Analysing visual behaviour in Drosophila Dscam2 mutants using optimised optomotor and operant control assays. PhD Dissertation, University of Queensland
  6. van der Voet M, Harich B, Franke B, Schenck A (2016): ADHD-associated dopamine transporter, latrophilin and neurofibromin share a dopamine-related locomotor signature in Drosophila. Mol Psychiatry. 21(4):565-573. doi: 10.1038/mp.2015.55
  7. de Bivort BL, van Swinderen B (2016): Evidence for selective attention in the insect brain. Curr Op Ins Sci. 15:9-15, doi:10.1016/j.cois.2016.02.007
  8. Farris SM (2016): Insect societies and the social brain. Curr Op Ins Sci. 15: 1-8
  9. Koenig S, Wolf R, Heisenberg M (2016): Vision in Flies: Measuring the Attention Span. PLOS ONE 11(2):e0148208, DOI: 10.1371/journal.pone.0148208
  10. Koenig S, Wolf R, Heisenberg M (2016): Visual Attention in Flies—Dopamine in the Mushroom Bodies Mediates the After-Effect of Cueing. PLOS ONE. 11(8): e0161412. DOI: 10.1371/journal.pone.0161412
  11. Kim S, Tellez K, Buchan G, Lebestky T (2016): Fly Stampede 2.0: A Next Generation Optomotor Assay for Walking Behavior in Drosophila Melanogaster. Frontiers in Molecular Neuroscience. 9. DOI: 10.3389/fnmol.2016.00148
  12. Van De Poll MN, Zajaczkowski EL, Taylor GJ, Srinivasan MV, van Swinderen B (2015): Using an abstract geometry in virtual reality to explore choice behaviour: visual flicker preferences in honeybees. J Exp Biol. 218(Pt 21):3448-60. doi: 10.1242/jeb.125138
  13. Zhang Q, Du G, John V, Kapahi P, Bredesen DE (2015): Alzheimer’s Model Develops Early ADHD Syndrome. J Neurol Neurophysiol. 6(6): 1–6.
  14. Farris SM, Van Dyke JW (2015): Evolution and function of the insect mushroom bodies: contributions from comparative and model systems studies. Curr Opin Insect Sci. 12: 19–25, DOI: 10.1016/j.cois.2015.08.006
  15. Paulk AC, Kirszenblat L, Zhou Y, van Swinderen B (2015): Closed-Loop Behavioral Control Increases Coherence in the Fly Brain. J Neurosci 35: 10304–10315, DOI: 10.1523/JNEUROSCI.0691-15.2015
  16. Braus D (2014): EinBlick ins Gehirn: Psychiatrie als angewandte klinische Neurowissenschaft, Georg Thieme Verlag, ISBN: 9783131333537
  17. Zhong C, Zhang Y, He W, Wei P, Lu Y, Zhu Y, Liu L, Wang L (2014): Multi-unit recording with iridium oxide modified stereotrodes in Drosophila melanogaster. J Neurosci Meth. 222:218–229
  18. Tse PU (2013): The Neural Basis of free will: criterial causation. MIT Press, 472p, 978-0-262-01910-1
  19. van Alphen B, van Swinderen B (2013): Drosophila strategies to study psychiatric disorders. Brain Res Bull. 92:1-11
  20. Haendel MA, Chesler EJ (2012): Lost and found in behavioral informatics. Int Rev Neurobiol. 103:1-18
  21. van Swinderen B (2012): Competing visual flicker reveals attention-like rivalry in the fly brain. Front Integr Neurosci. 6:96. doi: 10.3389/fnint.2012.00096
  22. Arena P, Patane L, Termini P (2012): Modeling attentional loop in the insect Mushroom Bodies. The 2012 International Joint Conference on Neural Networks (IJCNN), 1-7. DOI: 10.1109/IJCNN.2012.6252833
  23. Miller SM, Ngo TT and van Swinderen B (2012): Attentional switching in humans and flies: rivalry in large and miniature brains. Front. Hum. Neurosci. 5:188. doi: 10.3389/fnhum.2011.00188
  24. Graham P, Baddeley B, Philippides A, Cheng K (2012): Parsimonious Ways to Use Vision for Navigation. i-Perception. 3(4):226–226. DOI: 10.1068/id226
  25. Baddeley B, Graham P, Husbands P, Philippides A (2012): A Model of Ant Route Navigation Driven by Scene Familiarity. PLoS Comput Biol 8(1): e1002336. doi:10.1371/journal.pcbi.1002336
  26. Leboulle G (2012): Glutamate Neurotransmission in the Honey Bee Central Nervous System. In: Galizia CG, Eisenhardt D, Giurfa M (eds.): Honeybee Neurobiology and Behavior, a tribute to Randolf Menzel. Part 3, 171-184, DOI: 10.1007/978-94-007-2099-2_14
  27. Farris SM, Pettrey C, Daly KC (2011): A subpopulation of mushroom body intrinsic neurons is generated by protocerebral neuroblasts in the tobacco hornworm moth, Manduca sexta (Sphingidae, Lepidoptera). Arthropod Struct Dev. 40(5):395-408
  28. van Swinderen B (2011): Attention in Drosophila. Int Rev Neurobiol. 99:51-85
  29. Lee PT, Lin HW, Chang YH, Fu TF, Dubnau J, Hirsh J, Lee T, Chiang AS (2011): Serotonin-mushroom body circuit modulating the formation of anesthesia-resistant memory in Drosophila. Proc Natl Acad Sci U S A. 108(33):13794-13799
  30. LaFerriere H, Speichinger K, Stromhaug A, Zars T (2011); The Radish Gene Reveals a Memory Component with Variable Temporal Properties. PLoS ONE 6(9): e24557
  31. Evans O, Paulk AC, van Swinderen B (2011): An Automated Paradigm for Drosophila Visual Psychophysics. PLoS ONE 6(6): e21619
  32. Farris SM (2011): Are mushroom bodies cerebellum-like structures? Arthropod Struct Dev. 40(4):368-379
  33. Sareen P, Wolf R, Heisenberg M (2011): Attracting the attention of a fly. Proc Natl Acad Sci U S A. 108(17):7230-7235
  34. van Swinderen B, Andretic R (2011): Dopamine in Drosophila: setting arousal thresholds in a miniature brain. Proc. Roy. Soc. B. 278(1707): 906-913
  35. Farris SM, Schulmeister S (2011): Parasitoidism, not sociality, is associated with the evolution of elaborate mushroom bodies in the brains of hymenopteran insects. Proc Biol Sci. 278(1707): 940-951
  36. Blackiston D, Shomrat T, Nicolas CL, Granata C, Levin M. (2010): A second-generation device for automated training and quantitative behavior analyses of molecularly-tractable model organisms. PLoS One 5(12):e14370
Colomb J.; Brembs, B. (2010): The biology of psychology: ‘Simple’ conditioning? Commun Integr Biol. 3(2):142-145
Citations:
  1. Bronfman ZZ, Ginsburg S, Jablonka E (2016): The Transition to Minimal Consciousness through the Evolution of Associative Learning. Frontiers in Psychology. 7. DOI: 10.3389/fpsyg.2016.01954
  2. Weiss SJ & Rosales-Ruiz J (2014): Operant/Classical Conditioning: Comparisons, Intersections and Interactions: The 2014 Winter Conference on Animal Learning and Behavior Focus and Research Seminar Sessions. International Journal of Comparative Psychology. 27(4). https://escholarship.org/uc/item/4c46c9gg
  3. Tabone CJ, De Belle JS (2014): Olfactory learning and memory assays, In: Josh Dubnau (ed.) Behavioral Genetics of the Fly (Drosophila melanogaster). pp. 231-249. Cambridge Handbooks in Behavioral Genetics. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511920585.007.
  4. Noboa V, Gillette R (2013): Selective prey avoidance learning in the predatory sea slug Pleurobranchaea californica. J Exp Biol. 216(Pt 17):3231-3236
  5. Scheich H, Brosch M (2013): Task-Related Activation of Auditory Cortex. Springer Handbook of Auditory Research. Cohen YE, Popper AN, Fay RR, editors Springer-Verlag. DOI:10.1007/978-1-4614-2350-8_3
  6. Nepomnyashchikh VA (2012): Variability in invertebrate behavior and the problem of free will. Zhurnal Obshchei Biologii 73(6): 435-441
  7. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058

Brembs, B. (2009): The importance of being active. J. Neurogen. 23(1): 120-126.
Citations:

  1. Ferris BD, Green J, Maimon G (2018): Abolishment of Spontaneous Flight Turns in Visually Responsive Drosophila. Current Biology. 28(2):170–180. DOI: 10.1016/j.cub.2017.12.008
  2. Hogan JA (2017): The Study of Behavior. Cambridge University Press. DOI: 10.1017/CBO9781108123792
  3. Bronfman ZZ, Ginsburg S (2016): The Evolutionary Origins of Consciousness: Suggesting a Transition Marker. Journal of Consciousness Studies. 23(9–10):7–34
  4. Bronfman ZZ, Ginsburg S, Jablonka E (2016): The Transition to Minimal Consciousness through the Evolution of Associative Learning. Frontiers in Psychology. 7. DOI: 10.3389/fpsyg.2016.01954
  5. Schneider S, Vogt T, Abeln V (2015): Exercise in Space: Physical and Mental Benefit. In: Sports Performance (pp. 223–243). Springer Japan. DOI: 10.1007/978-4-431-55315-1_19
  6. Tabone CJ, De Belle JS (2014): Olfactory learning and memory assays, In: Josh Dubnau (ed.) Behavioral Genetics of the Fly (Drosophila melanogaster). pp. 231-249. Cambridge Handbooks in Behavioral Genetics. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511920585.007.
  7. Gomez-Marin,A., Paton,J.J., Kampff,A.R., Costa,R.M. and Mainen,Z.F. (2014) Big behavioral data: psychology, ethology and the foundations of neuroscience. Nature Neuroscience, 17, 1455–1462, DOI: 10.1038/nn.3812
  8. Schleyer M, Diegelmann S, Michels B, Saumweber T, Gerber B (2013): ‘Decision Making’ in Larval Drosophila. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p41-58
  9. Tse PU (2013): The Neural Basis of free will: criterial causation. MIT Press, 472p, 978-0-262-01910-1
  10. Cai J, Li L (2013): Autonomous Navigation Strategy in Mobile Robot. J. Comp. 8(8): 2118-2125 doi:10.4304/jcp.8.8.2118-2125
  11. Nepomnyashchikh VA (2013): Increases in variations in animal behavior induced by autocorrelations. Biol Bull Rev, 3(1), 49–56
  12. Chen J, Ruan XG, Dai LZ (2012): Behavior Cognition Computational Model Based on Cerebellum and Basal Ganglia Mechanism. Pattern Recognition and Artificial Intelligence 25(1): 29-36
  13. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058
  14. Koukolík F (2011): Basics of cognitive, affective and social neuroscience. VI. Free will. Prakticky Lekar 91(6): 315-320
  15. Ruan X-G, Chen J (2011): Operant conditioning reflex learning control scheme based on SMC and Elman network. Control and Decision. 26(9):1398-1401
Brembs, B. (2009): Mushroom bodies regulate habit formation in Drosophila. Curr Biol. 19(16): 1351–1355.
Citations:
  1. Arena E, Arena P, Strauss R, Patané L (2017): Motor-Skill Learning in an Insect Inspired Neuro-Computational Control System. Frontiers in Neurorobotics. 11. DOI: 10.3389/fnbot.2017.00012
  2. Foley BR, Marjoram P, Nuzhdin SV (2017): Basic reversal-learning capacity in flies suggests rudiments of complex cognition. PLOS ONE. 12(8): e0181749. DOI: 10.1371/journal.pone.0181749
  3. Schatton A, Scharff C (2017): FoxP expression identifies a Kenyon cell subtype in the honeybee mushroom bodies linking them to fruit fly αβc neurons. European Journal of Neuroscience. 46(9):2534–2541. DOI: 10.1111/ejn.13713
  4. Jurjako M (2016): Reasons: A Naturalistic Explanation. PhD thesis, University of Rijeka. https://www.bib.irb.hr/842794
  5. Vogt K, Aso Y, Hige T, Knapek S, Ichinose T, Friedrich AB, Turner GC, Rubin GM, Tanimoto H (2016): Direct neural pathways convey distinct visual information to Drosophila mushroom bodies. Elife. 5. pii: e14009. doi: 10.7554/eLife.14009
  6. de Bivort BL, van Swinderen B (2016): Evidence for selective attention in the insect brain. Curr Op Ins Sci. 15:9-15, doi:10.1016/j.cois.2016.02.007
  7. Parker MO, Brock AJ, Sudwarts A, Teh MT, Combe FJ, Brennan CH (2015): Developmental role of acetylcholinesterase in impulse control in zebrafish. Front. Behav. Neurosci. 9:271, DOI: 10.3389/fnbeh.2015.00271
  8. Farris SM, Van Dyke JW (2015): Evolution and function of the insect mushroom bodies: contributions from comparative and model systems studies. Curr Opin Insect Sci. 12: 19–25, DOI: 10.1016/j.cois.2015.08.006
  9. Heisenberg M (2015): Outcome learning, outcome expectations, and intentionality in Drosophila. Learn Mem. 22: 294–298, DOI: 10.1101/lm.037481.114
  10. Weiss SJ & Rosales-Ruiz J (2014): Operant/Classical Conditioning: Comparisons, Intersections and Interactions: The 2014 Winter Conference on Animal Learning and Behavior Focus and Research Seminar Sessions. International Journal of Comparative Psychology. 27(4). https://escholarship.org/uc/item/4c46c9gg
  11. Aso Y, Sitaraman D, Ichinose T, Kaun KR, Vogt K, Belliart-Guérin G, Plaçais PY, Robie AA, Yamagata N, Schnaitmann C, Rowell WJ, Johnston RM, Ngo TT, Chen N, Korff W, Nitabach MN, Heberlein U, Preat T, Branson KM, Tanimoto H, Rubin GM (2014): Mushroom body output neurons encode valence and guide memory-based action selection in Drosophila. eLife 3:e04580, DOI: 10.7554/eLife.04580
  12. Solanki N, Wolf R, Heisenberg M (2015) Central complex and mushroom bodies mediate novelty choice behavior in Drosophila. J Neurogen. 29: 30–37, DOI: 10.3109/01677063.2014.1002661
  13. Vogt K, Schnaitmann C, Dylla KV, Knapek S, Aso Y, Rubin GM, Tanimoto H (2014): Shared mushroom body circuits underlie visual and olfactory memories in Drosophila. eLife, 3:e02395, DOI: 10.7554/eLife.02395
  14. Parker MO, Evans AM, Brock AJ, Combe FJ, Teh MT, Brennan CH (2014): Moderate alcohol exposure during early brain development increases stimulus-response habits in adulthood. Addict Biol. 21: 49–60, DOI: 10.1111/adb.12176
  15. Arena P, Patané L, Stornanti V, Termini PS, Zäpf B, Strauss R (2013): Modeling the insect mushroom bodies: Application to a delayed match-to-sample task. Neur Net 41:202–211
  16. Smith KS, Graybiel AM (2014): Investigating Habits: Strategies, Technologies, and Models. Front. Behav. Neurosci. 8:39
  17. Arena P, Caccamo S, Patane L, Strauss R (2013): A computational model for motor learning in insects. The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8
  18. Guo A, Lu H, Zhang K, Ren Q, Wong YNC (2013): Visual learning and decision making in Drosophila melanogaster. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p378-394
  19. Tse PU (2013): The Neural Basis of free will: criterial causation. MIT Press, 472p, 978-0-262-01910-1
  20. Arena P, Patane L, Strauss R (2013): The Insect Mushroom Bodies: a Paradigm of Neural Reuse. Advances in Artificial Life, ECAL 2013. MIT Press. pp. 765–772
  21. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science 4: 561–582
  22. Zhang X, Ren Q, Guo A (2013): Parallel pathways for cross-modal memory retrieval in Drosophila. J Neurosci. 33(20):8784-8793
  23. Arena P, Patané L, Stornanti V, Termini PS, Zäpf B, Strauss R (2013): Modeling the insect mushroom bodies: Application to a delayed match-to-sample task. Neur. Net. 41: 202–211. DOI: 10.1016/j.neunet.2012.11.013
  24. Parker MO, Brock AJ, Walton RT, Brennan CH (2013): The role of zebrafish (Danio rerio) in dissecting the genetics and neural circuits of executive function. Front Neural Circuits. 7:63
  25. Namiki S, Takaguchi M, Seki Y, Kazawa T, Fukushima R, Iwatsuki C, Kanzaki R (2013): Concentric zones for pheromone components in the mushroom body calyx of the moth brain. J Comp Neurol. 521(5):1073-1092
  26. Nepomnyashchikh VA (2012): Variability in invertebrate behavior and the problem of free will. Zhurnal Obshchei Biologii 73(6): 435-441
  27. Joseph RM, Heberlein U (2012): Tissue-specific activation of a single gustatory receptor produces opposing behavioral responses in Drosophila. Genetics. 192(2):521-532
  28. Shmuelof L, Huang VS, Haith AM, Delnicki RJ, Mazzoni P, Krakauer JW (2012): Overcoming motor “forgetting” through reinforcement of learned actions. J Neurosci. 32(42):14617-14621
  29. Wu Y, Ren Q, Li H, Guo A (2012): The GABAergic anterior paired lateral neurons facilitate olfactory reversal learning in Drosophila. Learn Mem. 19(10):478-486
  30. Ren Q, Li H, Wu Y, Ren J, Guo A (2012): A GABAergic inhibitory neural circuit regulates visual reversal learning in Drosophila. J Neurosci. 32(34):11524-11538
  31. Zanini D, Jallon JM, Rabinow L, Samson ML (2012): Deletion of the Drosophila neuronal gene found in neurons disrupts brain anatomy and male courtship. Genes Brain Behav. 11 (7): 819-827
  32. Zhao XL, Campos AR (2012): Insulin signalling in mushroom body neurons regulates feeding behaviour in Drosophila larvae. J Exp Biol. 215(Pt 15):2696-2702.
  33. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058
  34. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  35. van Swinderen B (2011): Attention in Drosophila. Int Rev Neurobiol. 99:51-85
  36. Farris SM (2011): Are mushroom bodies cerebellum-like structures? Arthropod Struct Dev. 40(4):368-379
  37. Sorribes A, Armendariz BG, Lopez-Pigozzi D, Murga C, de Polavieja GG (2011): The Origin of Behavioral Bursts in Decision-Making Circuitry. PLoS Comput Biol 7(6): e1002075
  38. Farris SM, Schulmeister S (2010): Parasitoidism, not sociality, is associated with the evolution of elaborate mushroom bodies in the brains of hymenopteran insects. Proc Biol Sci. 278 (1707): 940-951
  39. Foucaud J, Burns JG, Mery F (2010): Use of Spatial Information and Search Strategies in a Water Maze Analog in Drosophila melanogaster. PLoS ONE 5(12): e15231
  40. Waddell S (2010): Dopamine reveals neural circuit mechanisms of fly memory. Trends Neurosci. 33(10):457-464
  41. Abramson CI, Nolf SL, Mixson TA, Well H (2010): Can Honey Bees Learn the Removal of a Stimulus as a Conditioning Cue? Ethology 116(9): 843–854
  42. Zars T (2010): Short-term memories in Drosophila are governed by general and specific genetic systems. Learn. Mem. 17: 246-251
  43. Yu C, Gupta J, Chen JF, Yin HH (2009): Genetic Deletion of A2A Adenosine Receptors in the Striatum Selectively Impairs Habit Formation. J Neurosci. 29(48):15100-15103
  44. van Swinderen, B. (2009): Fly Memory: A Mushroom Body Story in Parts. Curr Biol. 19(18): R855-R857
Brembs, B. (2008): Operant learning of Drosophila at the torque meter. J Vis Exp. 16. http://www.jove.com/details.stp?id=731 doi:10.3791/731.
Citations:
  1. Van De Poll MN, Zajaczkowski EL, Taylor GJ, Srinivasan MV, van Swinderen B (2015): Using an abstract geometry in virtual reality to explore choice behaviour: visual flicker preferences in honeybees. J Exp Biol. 218(Pt 21):3448-60. doi: 10.1242/jeb.125138
  2. Guo C, Du Y, Yuan D, Li M, Gong H, Gong Z, Liu L (2014): A conditioned visual orientation requires the ellipsoid body in Drosophila. Learn Mem 22: 56–63, DOI: 10.1101/lm.036863.114
  3. Kirkerud NH, Wehmann H-N, Galizia CG and Gustav D (2013): APIS—a novel approach for conditioning honey bees. Front. Behav. Neurosci. 7:29. doi: 10.3389/fnbeh.2013.00029
  4. Miller SM, Ngo TT and van Swinderen B (2012): Attentional switching in humans and flies: rivalry in large and miniature brains. Front. Hum. Neurosci. 5:188. doi: 10.3389/fnhum.2011.00188
  5. Visvanathan K, Gianchandani YB (2011): Locomotion response of airborne, ambulatory and aquatic insects to thermal stimulation using piezoceramic microheaters. J. Micromech. Microeng. 21: 125002 (9pp)
  6. van Swinderen B, Andretic R (2011): Dopamine in Drosophila: setting arousal thresholds in a miniature brain. Proc. Roy. Soc. B. 278(1707): 906-913
  7. Masek P, Scott K (2010): Limited taste discrimination in Drosophila. Proc Natl Acad Sci U S A. 107(33):14833-14838
Brembs, B.; Plendl, W. (2008): Double dissociation of PKC and AC manipulations on operant and classical learning in Drosophila. Curr Biol. 18(15): 1168-1171.
Citations:
  1. Kirkerud NH, Schlegel U, Galizia GC (2017): Aversive Learning of Colored Lights in Walking Honeybees. Front Behav Neurosci. 11. DOI: 10.3389/fnbeh.2017.00094
  2. Foley BR, Marjoram P, Nuzhdin SV (2017): Basic reversal-learning capacity in flies suggests rudiments of complex cognition. PLOS ONE. 12(8): e0181749. DOI: 10.1371/journal.pone.0181749
  3. Widmann A, Eichler K, Selcho M, Thum AS, Pauls D (2017): Odor-taste learning in Drosophila larvae. J Insect Physiol. DOI: 10.1016/j.jinsphys.2017.08.004
  4. Burgos, J. E. (2015): Misbehavior in a Neural Network Model. International Journal of Comparative Psychology, 28. Retrieved from https://escholarship.org/uc/item/3vb500tv
  5. Hawkins RD, Byrne JH (2015): Associative Learning in Invertebrates. Cold Spring Harbor Perspectives in Biology, 7(5), a021709. https://doi.org/10.1101/cshperspect.a021709
  6. Heisenberg M. (2015): Outcome learning, outcome expectations, and intentionality in Drosophila. Learn Mem. 22(6): 294-298. doi: 10.1101/lm.037481.114
  7. Jozefowiez, J. (2014): The Many Faces of Pavlovian Conditioning. International Journal of Comparative Psychology, 27(4). Retrieved from https://escholarship.org/uc/item/0bg0b3kq
  8. Byrne JH, LaBar KS, LeDoux JE, Schafe GE, Thompson RF (2014): Chapter 20 – Learning and Memory: Basic Mechanisms. In: From Molecules to Networks. Elsevier, 591–637. DOI: 10.1016/b978-0-12-397179-1.00020-8
  9. Weiss SJ & Rosales-Ruiz J (2014): Operant/Classical Conditioning: Comparisons, Intersections and Interactions: The 2014 Winter Conference on Animal Learning and Behavior Focus and Research Seminar Sessions. International Journal of Comparative Psychology. 27(4). https://escholarship.org/uc/item/4c46c9gg
  10. Bédécarrats A (2014): Étude cellulaire de la genèse et de l’apprentissage d’un comportement motivé chez l’aplysie, PhD dissertation, L´Université de Bordeaux
  11. Guo C, Du Y, Yuan D, Li M, Gong H, Gong Z, Liu L (2014): A conditioned visual orientation requires the ellipsoid body in Drosophila. Learn Mem 22: 56–63, DOI: 10.1101/lm.036863.114
  12. Vogt K, Schnaitmann C, Dylla KV, Knapek S, Aso Y, Rubin GM, Tanimoto H (2014): Shared mushroom body circuits underlie visual and olfactory memories in Drosophila. eLife, 3:e02395, DOI: 10.7554/eLife.02395
  13. Cyr A, Boukadoum M, Thériault F (2014): Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot’s controller. Front Neurorobot. 8:21 DOI: 10.3389/fnbot.2014.00021
  14. Alvarez B, Morís J, Luque D, Loy I (2014): Extinction, spontaneous recovery and reinstatement in the garden snail, Helix aspersa. Anim Behav 92: 75–83
  15. Webb B (2013): Issues in Invertebrate Learning Raised by Robot Models. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p81-90
  16. Hastings M, Farah CA, Sossin WS (2013): Roles of Protein Kinase C and Protein Kinase M in Aplysia Learning. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p221-235
  17. Guo A, Lu H, Zhang K, Ren Q, Wong YNC (2013): Visual learning and decision making in Drosophila melanogaster. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p378-394
  18. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science 4: 561–582
  19. Cai J, Ao D, Yu R (2013): Bionic learning strategy applied on snake robot motion control. International Journal of Modelling, Identification and Control 19: 265
  20. Zisopoulou S, Asimaki O, Leondaritis G, Vasilaki A, Sakellaridis N, Pitsikas N, Mangoura D (2013): PKC-epsilon activation is required for recognition memory in the rat. Behav Brain Res. 253:280-289
  21. Cai J, Li L (2013): Autonomous Navigation Strategy in Mobile Robot. J. Comp. 8(8): 2118-2125 doi:10.4304/jcp.8.8.2118-2125
  22. Garren MV, Sexauer SB, Page TL (2013): Effect of Circadian Phase on Memory Acquisition and Recall: Operant Conditioning vs. Classical Conditioning. PLoS ONE 8(3): e58693
  23. Cai J, Yu R, Cheng R (2012): Autonomous navigation research for mobile robot. Proceedings of the World Congress on Intelligent Control and Automation (WCICA), art. no. 6357893, pp. 331-335
  24. Chen J, Ruan XG, Dai LZ (2012): Behavior Cognition Computational Model Based on Cerebellum and Basal Ganglia Mechanism. Pattern Recognition and Artificial Intelligence 25(1): 29-36
  25. Cai JX, Sun X, Ma HR, Wang QS (2012): Research autonomous motion control for snake robot based on bionic learning strategy. 2012 Proceedings of International IEEE Conference on Modelling, Identification & Control (ICMIC), 826-831
  26. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058
  27. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  28. Ueda A, Wu CF (2012): Cyclic Adenosine Monophosphate Metabolism in Synaptic Growth, Strength, and Precision: Neural and Behavioral Phenotype-Specific Counterbalancing Effects between dnc Phosphodiesterase and rut Adenylyl Cyclase Mutations. J Neurogenet. 26(1):64-81
  29. Shuai Y, Hu Y, Qin H, Campbell RA, Zhong Y (2011): Distinct molecular underpinnings of Drosophila olfactory trace conditioning. Proc Natl Acad Sci U S A. 108(50):20201-20206
  30. Ruan X-G, Chen J (2011): Operant conditioning reflex learning control scheme based on SMC and Elman network. Control and Decision. 26(9):1398-1401
  31. Kahsai L, Zars T (2011): Learning and memory in Drosophila: behavior, genetics, and neural systems. Int Rev Neurobiol. 99:139-167
  32. Ruan X, Chen J, Dai L (2011): Motor Learning Based on the Cooperation of Cerebellum and Basal Ganglia for a Self-balancing Two-wheeled Robot. Intelligent Control and Automation 2(3): 57-68
  33. Zars T (2010): Short-term memories in Drosophila are governed by general and specific genetic systems. Learn. Mem. 17: 246-251
  34. Claridge-Chang A, Roorda RD, Vrontou E, Sjulson L, Li H, Hirsh J, Miesenböck G. (2009): Writing memories with light-addressable reinforcement circuitry. Cell 139(2):405-415
  35. Lorenzetti FD, Baxter DA, Byrne JH (2008): Molecular Mechanisms Underlying a Cellular Analog of Operant Reward Learning. Neuron 59: 815-828
Brembs, B.; Christiansen, F.; Pflüger, H.J.; Duch, C. (2007): Flight initiation and maintenance deficits in flies with genetically altered biogenic amine levels. J Neurosci 27: 11122–11131.
Citations:
  1. Stocker B, Bochow C, Damrau C, Mathejczyk T, Wolfenberg H, Colomb J, Weber C et al. (2018): Structural and Molecular Properties of Insect Type II Motor Axon Terminals. Front Sys Neurosci. 12. DOI: 10.3389/fnsys.2018.00005
  2. Neckameyer WS, Leal SM (2017): Diverse Functions of Insect Biogenic Amines as Neurotransmitters, Neuromodulators, and Neurohormones. In: Pfaff DW, Joels M (Eds.): Hormones, Brain and Behavior (pp 367–401). Elsevier. DOI: 1016/B978-0-12-803592-4.00035-3
  3. Roeder T (2010): Pharmacology of Invertebrate Octopamine and Tyramine Receptors. Biogenic Amines: Pharmacological, neurochemical and molecular aspects in the CNS. 15:335–346.
  4. Houot B, Gigot V, Robichon A, Ferveur JF (2017): Free flight odor tracking in Drosophila: Effect of wing chemosensors, sex and pheromonal gene regulation. Scientific Reports. 7:40221. DOI: 10.1038/srep40221
  5. Roeder, T. (2016): Trace Amines. Trace Amines and Neurological Disorders (pp. 3–9). Elsevier. DOI: 10.1016/B978-0-12-803603-7.00001-X
  6. Ryglewski S, Vonhoff F, Scheckel K, Duch C (2017): Intra-neuronal Competition for Synaptic Partners Conserves the Amount of Dendritic Building Material. Neuron. 93(3):632–645.e6. DOI: 10.1016/j.neuron.2016.12.043
  7. Sinakevitch IT, Daskalova SM, Smith BH (2017): The Biogenic Amine Tyramine and its Receptor (AmTyr1) in Olfactory Neuropils in the Honey Bee (Apis mellifera) Brain. Frontiers in Systems Neuroscience. 11. DOI: 10.3389/fnsys.2017.00077
  8. Servillo L, Castaldo D, Giovane A, Casale R, D’Onofrio N, Cautela D, Balestrieri ML (2017): Tyramine Pathways in Citrus Plant Defense: Glycoconjugates of Tyramine and Its N-Methylated Derivatives. Journal of Agricultural and Food Chemistry. 65(4):892–899. DOI: 10.1021/acs.jafc.6b04423
  9. Li Y, Tiedemann L, von Frieling J, Nolte S, El-Kholy S, Stephano F, Gelhaus C, et al. (2017): The Role of Monoaminergic Neurotransmission for Metabolic Control in the Fruit Fly Drosophila melanogaster. Frontiers in Systems Neuroscience. 11. DOI: 10.3389/fnsys.2017.00060
  10. Zhang H, Blumenthal EM (2017): Identification of multiple functional receptors for tyramine on an insect secretory epithelium. Scientific Reports. 7(1). DOI: 10.1038/s41598-017-00120-z
  11. Iliadi KG, Iliadi N, Boulianne GL (2017): Drosophila mutants lacking octopamine exhibit impairment in aversive olfactory associative learning. European Journal of Neuroscience. 46(5):2080–2087. DOI: 10.1111/ejn.13654
  12. Ryglewski S, Duch C, Altenhein B (2017): Tyramine Actions on Drosophila Flight Behavior Are Affected by a Glial Dehydrogenase/Reductase. Frontiers in Systems Neuroscience. 11. DOI: 10.3389/fnsys.2017.00068
  13. Kadas D, Klein A, Krick N, Worrell JW, Ryglewski S, Duch C (2017): Dendritic and Axonal L-Type Calcium Channels Cooperate to Enhance Motoneuron Firing Output during Drosophila Larval Locomotion. The Journal of Neuroscience. 37(45):10971–10982. DOI: 10.1523/JNEUROSCI.1064-17.2017
  14. Money TGA, Sproule MKJ, Cross KP, Robertson RM (2016): Octopamine stabilizes conduction reliability of an unmyelinated axon during hypoxic stress. J Neurophys. 116(3):949–959. DOI: 10.1152/jn.00354.2016
  15. Li Y, Hoffmann J, Stephano F, Bruchhaus I, Fink C, Roeder T (2016): Octopamine controls starvation resistance, life span and metabolic traits in Drosophila. Scientific Reports. 6(1). DOI: 10.1038/srep35359
  16. Hartfil S (2016): Morphological and electrophysiological properties of lateral deutocerebral cells in desert locust Schistocerca gregaria. PhD Dissertation, FU Berlin.
  17. Berger SD, Crook SM (2015) Modeling the Influence of Ion Channels on Neuron Dynamics in Drosophila. Front. Comput. Neurosci., 9, DOI: 10.3389/fncom.2015.00139
  18. El-Kholy S, Stephano F, Li Y, Bhandari A, Fink C, Roeder T (2015): Expression analysis of octopamine and tyramine receptors in Drosophila. Cell Tissue Res, 361: 669–684, DOI: 10.1007/s00441-015-2137-4
  19. Rillich J, Stevenson PA (2015): Releasing stimuli and aggression in crickets: octopamine promotes escalation and maintenance but not initiation. Front. Behav. Neurosci., 9:95 DOI: 10.3389/fnbeh.2015.00095
  20. Sadaf S, Reddy OV, Sane SP, Hasan G (2015) Neural Control of Wing Coordination in Flies. Curr Biol. 25: 80–86, DOI: 10.1016/j.cub.2014.10.069
  21. Gross AD, Kimber MJ, Coats JR (2014): G-Protein-Coupled Receptors (GPCRs) as Biopesticide Targets: A Focus on Octopamine and Tyramine Receptors. Biopesticides: State of the Art and Future Opportunities, DOI: 10.1021/bk-2014-1172.ch004
  22. Zhao H, Zheng N, Ribi WA, Zheng H, Xue L, Gong F, Zheng X, Hu F (2014): Neuromechanism Study of Insect–Machine Interface: Flight Control by Neural Electrical Stimulation. PLoS ONE 9(11):e113012, DOI: 10.1371/journal.pone.0113012
  23. Ryglewski S, Kadas D, Hutchinson K, Schuetzler N, Vonhoff F, Duch C (2014): Dendrites are dispensable for basic motoneuron function but essential for fine tuning of behavior. Proc Natl Acad Sci U S A, 111(50): 18049–18054, DOI: 10.1073/pnas.1416247111
  24. Jezzini SH, Reyes-Colón D, Sosa MA (2014): Characterization of a Prawn OA/TA Receptor in Xenopus Oocytes Suggests Functional Selectivity between Octopamine and Tyramine. PLoS ONE 9(10):e111314, DOI: 10.1371/journal.pone.0111314
  25. Lehmann F-O (2014): Flight behavior: Degradation of flight muscle power and locomotor capacity in transgenic Drosophila. In: Josh Dubnau (ed.) Behavioral Genetics of the Fly (Drosophila melanogaster). pp. 77-87. Cambridge Handbooks in Behavioral Genetics. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511920585.007.
  26. Sadaf S, Hasan G (2014): Serotonergic neurons of the Drosophila air-puff-stimulated flight circuit. J Biosci, 39: 575–583, DOI: 10.1007/s12038-014-9449-5
  27. Luo J, Lushchak OV, Goergen P, Williams MJ, Nässel DR (2014): Drosophila Insulin-Producing Cells Are Differentially Modulated by Serotonin and Octopamine Receptors and Affect Social Behavior. PLoS ONE 9, e99732. DOI: 10.1371/journal.pone.0099732
  28. Fuchs S, Rende E, Crisanti A, Nolan T (2014): Disruption of aminergic signalling reveals novel compounds with distinct inhibitory effects on mosquito reproduction, locomotor function and survival. Sci. Rep. 4:5526, DOI: 10.1038/srep05526
  29. Ruppert MB (2013): Dissecting Tbh and Hangover function in ethanol tolerance in Drosophila melanogaster. Dissertation, Universität zu Köln.
  30. Sieling F, Bédécarrats A, Simmers J, Prinz AA, Nargeot R (2014): Differential roles of nonsynaptic and synaptic plasticity in operant reward learning-induced compulsive behavior. Curr Biol. 24(9):941-950
  31. Lee YJ (2014): Motion Vision Processing in Fly Lobula Plate Tangential Cells. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 984. 47 pp. ISBN 978-91-554-8908-3.
  32. Ohta H, Ozoe Y (2014): Molecular Signalling, Pharmacology, and Physiology of Octopamine and Tyramine Receptors as Potential Insect Pest Control Targets. Adv Insect Physiol 46: Target Receptors in the Control of Insect Pests: Part II: 73-166
  33. Rien D, Kern R, Kurtz R (2013): Octopaminergic modulation of a fly visual motion-sensitive neuron during stimulation with naturalistic optic flow. Front Behav Neurosci 7
  34. Agrawal T, Sadaf S, Hasan G (2013): A Genetic RNAi Screen for IP3/Ca2+ Coupled GPCRs in Drosophila Identifies the PdfR as a Regulator of Insect Flight. PLoS Genet 9(10): e1003849
  35. Homberg U, Seyfarth J, Binkle U, Monastirioti M, Alkema MJ (2013): Identification of distinct tyraminergic and octopaminergic neurons innervating the central complex of the desert locust, Schistocerca gregaria. J Comp Neurol. 521(9):2025-2041
  36. Fuenzalida-Uribe N, Meza RC, Hoffmann HA, Varas R, Campusano JM (2013): nAChR-induced octopamine release mediates the effect of nicotine on a startle response in Drosophila melanogaster. J Neurochem. 2013 Jan 19. doi: 10.1111/jnc.12161. [Epub ahead of print]
  37. Rillich J, Stevenson PA, Pflueger H-J (2013): Flight and Walking in Locusts–Cholinergic Co-Activation, Temporal Coupling and Its Modulation by Biogenic Amines. PLoS ONE 8(5): e62899
  38. Wosnitza A, Bockemühl T, Dübbert M, Scholz H, Büschges A. (2013): Inter-leg coordination in the control of walking speed in Drosophila. J Exp Biol. 216(Pt 3):480-491
  39. Schneider A, Ruppert M, Hendrich O, Giang T, Ogueta M, Hampel S, Vollbach M, Büschges A, Scholz H (2012): Neuronal Basis of Innate Olfactory Attraction to Ethanol in Drosophila. PLoS ONE 7(12): e52007
  40. Adamo SA (2013): Parasites: evolution’s neurobiologists. J Exp Biol. 216(Pt 1):3-10. doi: 10.1242/jeb.073601.
  41. Suver MP, Mamiya A, Dickinson MH (2012): Octopamine Neurons Mediate Flight-Induced Modulation of Visual Processing in Drosophila. Curr Biol. 22(24): 2294-2302
  42. Sadaf S, Birman S, Hasan G (2012): Synaptic Activity in Serotonergic Neurons Is Required for Air-Puff Stimulated Flight in Drosophila melanogaster. PLoS ONE 7(9): e46405
  43. Herrera-Valdez MA, McKiernan EC, Berger SD, Ryglewski S, Duch C, Crook S (2012): Relating ion channel expression, bifurcation structure, and diverse firing patterns in a model of an identified motor neuron. J Comput Neurosci. 34(2):211-229
  44. Todorovic D, Markovic T, Prolic Z, Mihajlovic S, Rauš S, Nikolic L, Janac B (2012): The influence of static magnetic field (50 mT) on development and motor behaviour of Tenebrio (Insecta, Coleoptera). Int J Radiat Biol. 89(1):44-50
  45. Selcho M, Pauls D, Jundi BE, Stocker RF, Thum AS (2012): The role of octopamine and tyramine in Drosophila larval locomotion. J Comp Neurol. 2012 May 24. doi: 10.1002/cne.23152
  46. Adamo SA (2012): Parasites – Evolution’s neurobiologists. What have they learned after millions of years of evolution? Journal of Experimental Biology Symposium 2012, Tenuta Il Cicalino, Massa Marittima, Italy: 17–21 March 2012: http://jeb2012.biologists.com/PDF/Adamo.pdf
  47. Lehmann FO, Schutzner P, Wang, H (2012): Visual motion sensing and flight path control in flies. IN: Frontiers in Sensing: From Biology to Engineering. (Eds. F. Barth, P. Humphrey, M. Srinivasan) 129-141, ISBN: 978-3-211-99748-2
  48. Cossío-Bayúgar R, Miranda-Miranda E, Narváez Padilla V, Olvera-Valencia F, Reynaud E (2012): Perturbation of tyraminergic/octopaminergic function inhibits oviposition in the cattle tick Rhipicephalus (Boophilus) microplus. J Insect Physiol. 58(5):628-633
  49. Holden-Dye L, Walker RJ (2012): Report on the 12th symposium on invertebrate neurobiology held 31 August-4 September 2011 at the Balaton Limnological Research Institute of the Hungarian Academy of Sciences, Tihany, Hungary. Invert Neurosci. 12(1): 69-79
  50. Vonhoff F, Williams A, Ryglewski S, Duch C (2012): Drosophila as a Model for MECP2 Gain of Function in Neurons. PLoS ONE 7(2): e31835
  51. Banks CN, Adams ME (2011): Biogenic amines in the nervous system of the cockroach, Periplaneta americana following envenomation by the jewel wasp, Ampulex compressa. Toxicon. 59(2):320-328
  52. Pflüger HJ, Duch C (2011): Dynamic Neural Control of Insect Muscle Metabolism Related to Motor Behavior. Physiology 26:293-303
  53. Jung SN, Borst A, Haag J (2011): Flight activity alters velocity tuning of fly motion-sensitive neurons. J Neurosci. 31(25): 9231-9237
  54. Palmer CR, Kristan WB Jr. (2011): Contextual modulation of behavioral choice. Curr Opin Neurobiol. 21(4):520-526
  55. Stocker B (2011): Locust thoracic dorsal unpaired median (DUM) neurons: Differential activation and peripheral distribution of octopamine and tyramine. PhD Thesis, Freie Universität Berlin, Germany.
  56. Sinakevitch I, Mustard JA, Smith BH (2011): Distribution of the Octopamine Receptor AmOA1 in the Honey Bee Brain. PLoS ONE 6(1): e14536
  57. Longden KD, Krapp HG (2010): Octopaminergic modulation of temporal frequency coding in an identified optic flow-processing interneuron. Front. Syst. Neurosci. 4:153
  58. Yarali A, Gerber B (2010): A Neurogenetic Dissociation between Punishment-, Reward-, and Relief-Learning in Drosophila. Front Behav Neurosci. 4:189
  59. Zars T (2010): Short-term memories in Drosophila are governed by general and specific genetic systems. Learn. Mem. 17: 246-251
  60. Sitaraman D, Zars M, Zars T (2010): Place memory formation in Drosophila is independent of proper octopamine signaling. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 196(4):299-305
  61. Schnaitmann C, Vogt K, Triphan T and Tanimoto H (2010): Appetitive and aversive visual learning in freely moving Drosophila. Front. Behav. Neurosci. 4:10. doi:10.3389/fnbeh.2010.00010
  62. Maimon G, Straw AD, Dickinson MH (2010): Active flight increases the gain of visual motion processing in Drosophila. Nat Neurosci. 13(3):393-9
  63. Vierk R, Duch C, Pflüger HJ (2010): Postembryonic development of centrally generated flight motor patterns in the hawkmoth, Manduca sexta. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 196(1): 37-50
  64. Longden KD, Krapp HG (2009): State-dependent performance of optic-flow processing interneurons. J Neurophysiol. 102(6):3606-3618
  65. Huang J, Ohta H, Inoue N, Takao H, Kita T, Ozoe F, Ozoe Y (2009): Molecular cloning and pharmacological characterization of a Bombyx mori tyramine receptor selectively coupled to intracellular calcium mobilization. Insect Biochem Mol Biol. 39(11):842-849
  66. Blumenthal EM (2009): Isoform- and cell-specific function of tyrosine decarboxylase in the Drosophila Malpighian tubule. J Exp Biol. 212(Pt 23):3802-3809
  67. Hesselberg T, Lehmann FO (2009): The role of experience in flight behaviour of Drosophila. J Exp Biol. 212(Pt 20):3377-3386.
  68. Westmark S, Oliveira EE, Schmidt J (2009): Pharmacological analysis of tonic activity in motoneurons during stick insect walking. J Neurophysiol. 102(2):1049-1061
  69. Peric-Mataruga V, Mircic D, Vlahovic M, Mrdakovic M, Todorovic D, Stevanovic D, Milosevic V. (2009): Effects of ghrelin on the feeding behavior of Lymantria dispar L. (Lymantriidae) caterpillars. Appetite. 53(1): 147-150.
  70. Pirri JK, McPherson AD, Donnelly JL, Francis MM, Alkema MJ (2009): A tyramine-gated chloride channel coordinates distinct motor programs of a Caenorhabditis elegans escape response. Neuron. 62(4):526-538.
  71. Lange AB (2009): Tyramine: from octopamine precursor to neuroactive chemical in insects. Gen Comp Endocrinol. 162(1):18-26
  72. Vierk R, Pflueger HJ, Duch C (2009): Differential effects of octopamine and tyramine on the central pattern generator for Manduca flight. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 195(3): 265-277
  73. Kononenko NL, Wolfenberg H, Pflüger H-J (2009): Tyramine as an independent transmitter and a precursor of octopamine in the locust central nervous system: An immunocytochemical study. J. comp. Neurol. 512: 433-452
  74. Socha R, Kodrík D, Zemek R. (2008): Stimulatory effects of bioamines norepinephrine and dopamine on locomotion of Pyrrhocoris apterus (L.): is the adipokinetic hormone involved? Comp Biochem Physiol B Biochem Mol Biol. 151(3):305-310
  75. Duch C, Vonhoff F, Ryglewski S. (2008): Dendrite elongation and dendritic branching are affected separately by different forms of intrinsic motoneuron excitability. J Neurophysiol. 100(5):2525-2536
  76. Buhl E, Schildberger K, Stevenson PA (2008): A muscarinic cholinergic mechanism underlies activation of the central pattern generator for locust flight. J Exp Biol. 211(Pt 14):2346-57.
  77. Dierick HA. (2008): Fly fighting: octopamine modulates aggression. Curr Biol. 18(4):R161-163
  78. Vömel M, Wegener C (2008): Neuroarchitecture of Aminergic Systems in the Larval Ventral Ganglion of Drosophila melanogaster. PLoS ONE 3(3): e1848
  79. Ryglewski S (2008): Functional analysis of membrane properties in identified insect neurons: The roles of ionic currents for intracellular calcium signaling, intrinsic excitability and dendritic growth. Doctoral thesis , FU Berlin, Germany.
Maye, A.; Hsieh, C.; Sugihara, G. and Brembs, B. (2007): Order in spontaneous behavior. PLoS ONE 2(5): e443
Citations:
  1. Ferris BD, Green J, Maimon G (2018): Abolishment of Spontaneous Flight Turns in Visually Responsive Drosophila. Current Biology. 28(2):170–180. DOI: 10.1016/j.cub.2017.12.008
  2. Toepfer F, Wolf R, Heisenberg M (2018): Multi-stability with ambiguous visual stimuli in Drosophila orientation behavior. PLOS Biology. 16(2):e2003113. DOI: 10.1371/journal.pbio.2003113
  3. Fisher DN, Brachmann M, Burant JB (2018): Complex dynamics and the development of behavioural individuality. Animal Behaviour. 138:1-6. DOI: 10.1016/j.anbehav.2018.02.015
  4. Ehrlich DE, Schoppik D (2017): Control of Movement Initiation Underlies the Development of Balance. Current Biology. 27(3):334–344. DOI: 10.1016/j.cub.2016.12.003
  5. Melanson A, Mejias JF, Jun JJ, Maler L, Longtin A (2017): Nonstationary Stochastic Dynamics Underlie Spontaneous Transitions between Active and Inactive Behavioral States. Eneuro. 4(2). DOI: 10.1523/ENEURO.0355-16.2017
  6. Ishida Y, Chiba R (2017): Free Will and Turing Test with Multiple Agents: An Example of Chatbot Design. Procedia Computer Science. 112: 2506–2518. DOI: 10.1016/j.procs.2017.08.190
  7. Yunes RA (2017): Information, system, complexity, feedbacks, retro-causality: an hypothesis based in the new paradigms of the universe, life, evolution and man. Syntropy. 1: 22-42. ISSN: 1825-7968
  8. Shi L, Xiao A (2017): Modeling Anomalous Diffusion by a Subordinated Integrated Brownian Motion. Advances in Mathematical Physics. 1–7. DOI: 10.1155/2017/7246865
  9. Nagaya N, Mizumoto N, Abe MS, Dobata S, Sato R, Fujisawa R (2017): Anomalous diffusion on the servosphere: A potential tool for detecting inherent organismal movement patterns. PLOS ONE. 12(6): e0177480. DOI: 10.1371/journal.pone.0177480
  10. Lindsay T, Sustar A, Dickinson M (2017): The Function and Organization of the Motor System Controlling Flight Maneuvers in Flies. Current Biology. 27(3):345–358. DOI: 10.1016/j.cub.2016.12.018
  11. Jandhyala VK, Fotopoulos SB (2017): Applications of random search methods to foraging in ecological environments and other natural phenomena-A review. Environmetrics. e2451. DOI: 10.1002/env.2451
  12. Guisandez L, Baglietto G, Rozenfeld A (2017): Heterogeneity promotes first to second order phase transition on flocking systems. arXiv:1711.11531. http://arxiv.org/abs/1711.11531
  13. Mele AR (2017): Aspects of Agency: Decisions, Abilities, Explanations, and Free Will. Oxford University Press. ISBN: 9780190659974
  14. Walter S (2016): Illusion freier Wille? B. Metzler. DOI: 10.1007/978-3-476-05445-6
  15. Campos D, Bartumeus F, Méndez V, Andrade JS Jr, Espadaler X (2016): Variability in individual activity bursts improves ant foraging success. Journal of The Royal Society Interface. 13(125): 20160856. DOI: 10.1098/rsif.2016.0856
  16. Zilio D (2016): On the autonomy of psychology from neuroscience: A case study of Skinner’s radical behaviorism and behavior analysis. Rev Gen Psych. 20: 155–170
  17. Kane R (2016): Moral Responsibility, Reactive Attitudes and Freedom of Will. The Journal of Ethics 20: 229–246
  18. Velasque M, Briffa M (2016): The opposite effects of routine metabolic rate and metabolic rate during startle responses on variation in the predictability of behaviour in hermit crabs. Behaviour. 153:1545–1566. doi:10.1163/1568539x-00003371
  19. Racine E, Nguyen V, Saigle V, Dubljevic V (2016): Media Portrayal of a Landmark Neuroscience Experiment on Free Will. Science and Engineering Ethics. 23(4):989–1007. DOI: 10.1007/s11948-016-9845-3
  20. Calderon DP, Kilinc M, Maritan A, Banavar JR, Pfaff D (2016): Generalized CNS arousal: An elementary force within the vertebrate nervous system. Neurosci Biobehav Rev. 68:167-176. doi: 10.1016/j.neubiorev.2016.05.014
  21. Valenti D, Denaro G, Conversano F, Brunet C, Bonanno A, Basilone G, Mazzola S, Spagnolo B (2016): The role of noise on the steady state distributions of phytoplankton populations. J. Stat. Mech., 054044
  22. Dunn TW, Mu Y, Narayan S, Randlett O, Naumann EA, Yang CT, Schier AF, Freeman J, Engert F, Ahrens MB (2016): Brain-wide mapping of neural activity controlling zebrafish exploratory locomotion. Elife. 5. pii: e12741. doi: 10.7554/eLife.12741
  23. Reynolds AM, Bartumeus F, Kölzsch A, van de Koppel J (2016): Signatures of chaos in animal search patterns. Sci Rep. 6:23492. doi: 10.1038/srep23492
  24. Chmielarz P, Kreiner G, Kusmierczyk J, Kowalska M, Roman A, Tota K, Nalepa I (2016): Depressive-like immobility behavior and genotype?×?stress interactions in male mice of selected strains. Stress 3:1-8, DOI: 10.3109/10253890.2016.1150995
  25. Kane R (2016): The complex tapestry of free will: striving will, indeterminism and volitional streams, Springer Science, DOI: 10.1007/s11229-016-1046-8
  26. Kane R (2016): Moral Responsibility, Reactive Attitudes and Freedom of Will. The Journal of Ethics. 20(1–3): 229–246. DOI: 10.1007/s10892-016-9234-9
  27. Hunt ER, Baddeley RJ, Worley A, Sendova-Franks AB, Franks NR (2016): Ants determine their next move at rest: motor planning and causality in complex systems. R. Soc. open sci. 3(1):150534 DOI: 10.1098/rsos.150534
  28. Taylor G (2015): Unravelling the sensory control of behaviour in honeybees using virtual reality paradigms. PhD thesis, University of Queensland. DOI: 14264/uql.2015.332
  29. Waller BN (2015): Restorative Free Will: Back to the Biological Base. Lexington Books, ISBN: 9781498522380, 328pp
  30. Sims DW (2015): Intrinsic Lévy behaviour in organisms–searching for a mechanism: Comment on “Liberating Lévy walk research from the shackles of optimal foraging” by A.M. Reynolds. Phys Life Rev. 14:111-114. doi: 10.1016/j.plrev.2015.06.002
  31. Van De Poll MN, Zajaczkowski EL, Taylor GJ, Srinivasan MV, van Swinderen B (2015): Using an abstract geometry in virtual reality to explore choice behaviour: visual flicker preferences in honeybees. J Exp Biol. 218(Pt 21):3448-60. doi: 10.1242/jeb.125138
  32. Moy K, Li W, Tran HP, Simonis V, Story E, Brandon C, Furst J, Raicu D, Kim H. (2015) Computational Methods for Tracking, Quantitative Assessment, and Visualization of C. elegans Locomotory Behavior. PLOS ONE 10(12):e0145870, DOI:10.1371/journal.pone.0145870
  33. Abe MS, Shimada M (2015): Lévy Walks Suboptimal under Predation Risk. PLoS Comput Biol. 11(11):e1004601, DOI: 10.1371/journal.pcbi.1004601
  34. Kane R (2015): On the role of indeterminism in libertarian free will. Philosophical Explorations, DOI: 10.1080/13869795.2016.1085594
  35. Neuringer A (2015): Reinforced (un)predictability and the voluntary operant. Europ J Behav Anal, DOI: 10.1080/15021149.2015.1084767
  36. Lee RX, Kuhn B, Stephens GJ (2015): Prediction of spontaneous behavioral dynamics by neuronal population imaging in mouse neocortex. Presented at the 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), IEEE. DOI: 10.1109/ICIIBMS.2015.7439527
  37. Schwarz RF, Branicky R, Grundy LJ, Schafer WR, Brown AE (2015): Changes in Postural Syntax Characterize Sensory Modulation and Natural Variation of C. elegans Locomotion. PLoS Comput Biol. 11(8):e1004322 DOI: 10.1016/j.procs.2015.08.297
  38. Ishida Y (2015): A Note on Continuous Self-Identification as Self-Awareness: An Example of Robot Navigation. Procedia Computer Science, 60: 1865–1874, DOI: 10.1371/journal.pcbi.1004322
  39. Valenti D, Denaro G, Spagnolo B, Mazzola S, Basilone G, Conversano F, Brunet C, Bonanno A (2015): Stochastic models for phytoplankton dynamics in Mediterranean Sea. Ecol Complex DOI: 10.1016/j.ecocom.2015.06.001
  40. Kim AJ, Fitzgerald JK, Maimon G (2015): Cellular evidence for efference copy in Drosophila visuomotor processing. Nat Neurosci. 18: 1247–1255, DOI: 10.1038/nn.4083
  41. Sullivan C, Loughlin R, Schank JC, Joshi SS (2015): Genetic algorithms produce individual robotic rat pup behaviors that match Norway rat pup behaviors at multiple scales. Artif Life Robotics 20: 93–102, DOI: 10.1007/s10015-015-0208-y
  42. Kölzsch A, Alzate A, Bartumeus F, de Jager M, Weerman EJ, Hengeveld GM, Naguib M, Nolet BA, van de Koppel J (2015): Experimental evidence for inherent Lévy search behaviour in foraging animals. Proc Biol Sci. 282: 20150424–20150424, DOI: 10.1098/rspb.2015.0424
  43. Nurzaman SG, Yu X, Kim Y, Iida F (2015): Goal-directed multimodal locomotion through coupling between mechanical and attractor selection dynamics. Bioinspir. Biomim. 10(2):025004, DOI: 10.1088/1748-3190/10/2/025004
  44. Muijres FT, Elzinga MJ, Iwasaki NA, Dickinson MH (2015): Body saccades of Drosophila consist of stereotyped banked turns. J Exp Biol. 218: 864–875, DOI: 10.1242/jeb.114280
  45. Bell HC (2014): Behavioral Variability in the Service of Constancy, International Journal of Comparative Psychology, 27(2): 338-360
  46. Humphries NE, Sims DW (2014): Optimal foraging strategies: Lévy walks balance searching and patch exploitation under a very broad range of conditions. J Theor Biol. 358: 179–193, DOI: 10.1016/j.jtbi.2014.05.032
  47. Christensen K, Papavassiliou D, de Figueiredo A, Franks NR, Sendova-Franks AB (2014): Universality in ant behaviour. J R Soc Interface. 12(102):20140985, DOI: 10.1098/rsif.2014.0985
  48. Pyke GH (2014): Understanding movements of organisms: it’s time to abandon the Lévy foraging hypothesis. Methods Ecol Evol, 6: 1–16, DOI: 10.1111/2041-210X.12298
  49. Kane R (2014): II-Acting “of One”s Own Free Will’: Modern Reflections on an Ancient Philosophical Problem. Proceedings of the Aristotelian Society. 114:35–55. DOi: 10.1111/j.1467-9264.2014.00363.x
  50. Hillebrandt H, Friston KJ, Blakemore SJ (2014): Effective connectivity during animacy perception – dynamic causal modelling of Human Connectome Project data. Sci Rep. 4: 6240. DOI: 10.1038/srep06240
  51. Jung K, Jang H, Kralik JD, Jeong J (2014): Bursts and Heavy Tails in Temporal and Sequential Dynamics of Foraging Decisions. PLoS Comput Biol, 10: e1003759. DOI: 10.1371/journal.pcbi.1003759
  52. Palmer D (2014): Libertarian Free Will: Contemporary Debates, Oxford University Press, ISBN 978-0-19-986008-1
  53. Sinnott-Armstrong W (2014): Moral Psychology, Volume 4: Free Will and Moral Responsibility, MIT Press, 474pp., ISBN 9780262525473
  54. MacIntosh AJJ (2014): The Fractal PrimatePrimate: Interdisciplinary Science and the Math behind the Monkey. Primate Res. 30: 95–119. DOI: 10.2354/psj.30.011
  55. Gomez-Marin A, Paton JJ, Kampff AR, Costa RM, Mainen ZF (2014) Big behavioral data: psychology, ethology and the foundations of neuroscience. Nat Neurosci, 17: 1455–1462. DOI: 10.1038/nn.3812
  56. Heisenberg M (2014): The Beauty of the Network in the Brain and the Origin of the Mind in the Control of Behavior. J Neurogen, 28: 389–399. DOI: 10.3109/01677063.2014.912279
  57. Moritz JM (2014): Animal suffering, evolution, and the origins of evil: toward a “free creatures” defense. Zygon 49: 348–380. DOI: 10.1111/zygo.12085
  58. Mix LJ, Masel J (2014): Chance, purpose, and progress in evolution and christianity. Evolution. 68(8):2441-2451, 10.1111/evo.12434. DOI:10.1111/evo.12434
  59. Nurzaman S, Yu X, Kim Y, Iida F (2014): Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism. Entropy 16: 2592–2610
  60. Wearmouth VJ, McHugh MJ, Humphries NE, Naegelen A, Ahmed MZ, Southall EJ, Reynolds AM, Sims DW (2014): Scaling laws of ambush predator ‘waiting’ behaviour are tuned to a common ecology. Proc Biol Sci. 281(1782):20132997
  61. Wang R, Wang G, Zheng J (2014): An Exploration of the Range of Noise Intensity That Affects the Membrane Potential of Neurons. Abstract and Applied Analysis 2014:Article ID 801642, 1–11
  62. Seuront L, Stanley HE (2014): Anomalous diffusion and multifractality enhance mating encounters in the ocean. Proc Natl Acad Sci. 111:2206–2211
  63. Salvador LC, Bartumeus F, Levin SA, Ryu WS (2014): Mechanistic analysis of the search behaviour of Caenorhabditis elegans. J R Soc Interface. 11(92):2013.1092
  64. Benhamou S (2014): Of scales and stationarity in animal movements. Ecol Lett. 17:261–272
  65. Nayakar CSM, Omkar S, Srikanth R (2014): Consciousness, Libertarian Free Will and Quantum Randomness. pp 307-323 In: Menon S, Sinha A, Sreekantan BV (Eds.): Interdisciplinary Perspectives on Consciousness and the Self. 328p, Springer-Verlag, ISBN: 978-81-322-1587-5
  66. Humphries NE, Weimerskirch H, Sims DW (2013): A new approach for objective identification of turns and steps in organism movement data relevant to random walk modelling. Methods Ecol Evol. 4(10): 930–938 DOI: 10.1111/2041-210X.12096
  67. Griffith M (2013): Free Will: The basics. Routledge. ISBN: 0415562198
  68. Briffa M (2013): Plastic proteans: reduced predictability in the face of predation risk in hermit crabs. Biol Lett 9(5):20130592
  69. Kawabata M, Ueno T, Tomita J, Kawatani J, Tomoda A, Kume S, Kume K (2013): Temporal organization of rest defined by actigraphy data in healthy and childhood chronic fatigue syndrome children. BMC Psychiatry 13:281
  70. Zilio, D. (2013): Behavioral unit of selection and the operant-respondent distinction: The role of neurophysiological events in controlling the verbal behavior of theorizing about behavior. Psychological Record, 63(4): 895-918
  71. Dickinson MH (2014): Death Valley, Drosophila , and the Devonian Toolkit . Annu Rev Entomol. 59: 51–72
  72. Biro PA, Adriaenssens B (2013): Predictability as a Personality Trait: Consistent Differences in Intraindividual Behavioral Variation. Amer. Nat. 182: 621–629
  73. Heisenberg M (2013): Action Selection: The Brain as a Behavioral Organizer. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p9-13
  74. Tse PU (2013): The Neural Basis of free will: criterial causation. MIT Press, 472p, 978-0-262-01910-1
  75. Humphries NE, Weimerskirch H, Sims DW (2013): A new approach for objective identification of turns and steps in organism movement data relevant to random walk modelling. Methods in Ecology and Evolution: n/a–n/a. DOI:http://dx.doi.org/10.1111/2041-210X.12096
  76. Denaro G, Valenti D, Spagnolo B, Basilone G, Mazzola S, Zgosi SW, Aronica S, Nonanno A (2013) Dynamics of Two Picophytoplankton Groups in Mediterranean Sea: Analysis of the Deep Chlorophyll Maximum by a Stochastic Advection-Reaction-Diffusion Model. PLoS ONE 8(6): e66765
  77. Raja S (2013): The neuronal basis of spontaneous flight behavior in Drosophila. PhD dissertation, FU Berlin
  78. Briffa M, Bridger D, Biro PA (2013): How does temperature affect behaviour? Multilevel analysis of plasticity, personality and predictability in hermit crabs. Anim Behav 86(1): 47–54
  79. Gomez-Marin, A. (2013): Tools, flies and what to do next. American Institute of Physics. AIP Conf. Proc. 1510: 120-123 doi:10.1063/1.4776508
  80. Censi A, Straw AD, Sayaman RW, Murray RM, Dickinson MH (2013): Discriminating external and internal causes for heading changes in freely flying Drosophila. PLoS Comput Biol. 9(2):e1002891
  81. Nepomnyashchikh VA (2013): Increases in variations in animal behavior induced by autocorrelations. Biol Bull Rev, 3(1), 49–56
  82. Wong KFE, Cheng C (2013): Predictable or Not? Individuals’ Risk Decisions Do Not Necessarily Predict Their Next Ones. PLoS ONE 8(2): e56811
  83. Heisenberg, M. (2013): The Origin of Freedom in Animal Behaviour. 95–103 In: Suarez, Antoine; Adams, Peter (Eds.) Is Science Compatible with Free Will? Is Science Compatible with Free Will? Exploring Free Will and Consciousness in the Light of Quantum Physics and Neuroscience. Springer 312p ISBN 978-1-4614-5212-6
  84. Martius G, Der R, Ay N (2013): Information driven self-organization of complex robotic behaviors PLoS One. 8(5):e63400
  85. Libersat F, Gal R (2013): What can parasitoid wasps teach us about decision-making in insects? J Exp Biol. 216(Pt 1):47-55. doi: 10.1242/jeb.073999
  86. Warzecha AK, Rosner R, Grewe J (2013): Impact and sources of neuronal variability in the fly’s motion vision pathway. J Physiol – Paris 07(1-2): 26-40. DOI: 10.1016/j.jphysparis.2012.10.002
  87. Nayakar CSM, Srikanth R (2012): Uncomputability and free will, arXiv:1210.6301 [physics.hist-ph]
  88. Sreedhar M, Upadhyay NM, Mishra S (2012): Optimized solutions for an optimization technique based on minority charge carrier inspired algorithm applied to selective harmonic elimination in induction motor drive. 2012 1st International Conference on Recent Advances in Information Technology (RAIT), DOI: 10.1109/RAIT.2012.6194523
  89. Petrou G (2012): Kinematics of cricket phonotaxis. PhD Thesis, University of Edinburgh
  90. Sreedhar M, Dasgupta A (2012): Experimental verification of Minority Charge Carrier Inspired Algorithm applied to voltage source inverter. In: 2012 IEEE 5th India International Conference on Power Electronics (IICPE). Institute of Electrical and Electronics Engineers, pp 1–6. [online] URL: http://dx.doi.org/10.1109/IICPE.2012.6450395
  91. Sims DW, Humphries NE (2012): Lévy flight search patterns of marine predators not questioned: a reply to Edwards et al. arXiv:1210.2288 [q-bio.PE]
  92. Paulk A, Millard SS, van Swinderen B (2012): Vision in Drosophila: Seeing the World Through a Model’s Eyes. Annu Rev Entomol. 58:313–332
  93. van Swinderen B (2012): Competing visual flicker reveals attention-like rivalry in the fly brain. Front Integr Neurosci. 6:96. doi: 10.3389/fnint.2012.00096
  94. Hartston W (2012): The Things That Nobody Knows: 501 Mysteries of Life, the Universe and Everything. Atlantic Books, ISBN-13: 978-1848878259
  95. Nurzaman SG, Matsumoto Y, Nakamura Y, Shirai K, Ishiguro H (2012): Bacteria-inspired underactuated mobile robot based on a biological fluctuation, Adapt Behav. 20(4) 225–236
  96. Koch C (2012): Consciousness: Confessions of a Romantic Reductionist. MIT Press ISBN-13: 978-0262017497
  97. Proekt A, Banavar JR, Maritan A, Pfaff DW (2012): Scale invariance in the dynamics of spontaneous behavior. Proc Natl Acad Sci U S A. 2012 Jun 7. [Epub ahead of print]
  98. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058
  99. Bazazi S, Bartumeus F, Hale JJ, Couzin ID (2012): Intermittent motion in desert locusts: behavioural complexity in simple environments. PLoS Comput Biol. 8(5):e1002498
  100. Magdziarz M, Metzler R, Szczotka W, Zebrowski P (2012): Correlated continuous-time random walks – Scaling limits and Langevin picture. J Stat Mech: Theor Exp. 4: P04010
  101. Humphries NE, Weimerskirch H, Queiroz N, Southall EJ, Sims DW (2012): Foraging success of biological Lévy flights recorded in situ. Proc Natl Acad Sci U S A. 109(19):7169-7174
  102. Sims DW, Humphries NE, Bradford RW, Bruce BD (2012): Lévy flight and Brownian search patterns of a free-ranging predator reflect different prey field characteristics. J Anim Ecol. 81(2):432-442
  103. Barham JA (2012): Normativity, agency, and life. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 43(1): 92–103
  104. Joseph J, Dunn FA, Stopfer M (2012): Spontaneous olfactory receptor neuron activity determines follower cell response properties. J Neurosci. 32(8):2900-2910
  105. Mandayam Nayakar CS, Omkar S, Srikanth R (2012): Libertarian free will and quantum indeterminism. arXiv:1202.4440v2
  106. Ueno T, Masuda N, Kume S, Kume K (2012); Dopamine Modulates the Rest Period Length without Perturbation of Its Power Law Distribution in Drosophila melanogaster. PLoS ONE 7(2): e32007
  107. Miller SM, Ngo TT and van Swinderen B (2012): Attentional switching in humans and flies: rivalry in large and miniature brains. Front. Hum. Neurosci. 5:188. doi: 10.3389/fnhum.2011.00188
  108. Barham JA (2011): Teleological Realism in Biology, PhD Thesis, University of Notre Dame, USA.
  109. Bendesky A, Bargmann CI (2011): Genetic contributions to behavioural diversity at the gene-environment interface. Nat Rev Genet. 12(12):809-820
  110. Rosner R, Warzecha AK (2011): Relating neuronal to behavioral performance: variability of optomotor responses in the blowfly. PLoS One. 6(10):e26886
  111. Mele AR (2011): Libertarianism and Human Agency. Phil Phen Res. DOI: 10.1111/j.1933-1592.2011.00529.x
  112. Sims DW, Humphries NE, Bradford RW, Bruce BD (2011): Lévy flight and Brownian search patterns of a free-ranging predator reflect different prey field characteristics. J Anim Ecol. 2011 Oct 17. doi: 10.1111/j.1365-2656.2011.01914.x. [Epub ahead of print]
  113. Windecker R (2011): Stochastic Artificial Neural Networks and random walks. The 2011 International Joint Conference on Neural Networks, 1134-1140
  114. He BJ (2011): Scale-Free Properties of the Functional Magnetic Resonance Imaging Signal during Rest and Task. J Neurosci. 31(39):13786-13795
  115. Nurzaman SG, Matsumoto Y, Nakamura Y, Koizumi S, Ishiguro H (2011): ‘Yuragi’-Based Adaptive Mobile Robot Search With and Without Gradient Sensing: From Bacterial Chemotaxis to a Lévy Walk. Adv. Robot. 25(16): 2019-2037
  116. Lewejohann L, Zipser B, Sachser N (2011): “Personality” in laboratory mice used for biomedical research: A way of understanding variability? Dev Psychobiol. 53(6):624-630
  117. Hays GC, Bastian T, Doyle TK, Fossette S, Gleiss AC, Gravenor MB, Hobson VJ, Humphries NE, Lilley MK, Pade NG, Sims DW (2011): High activity and Lévy searches: jellyfish can search the water column like fish. Proc Biol Sci. 279(1728):465-473
  118. Sorribes A, Armendariz BG, Lopez-Pigozzi D, Murga C, de Polavieja GG (2011): The Origin of Behavioral Bursts in Decision-Making Circuitry. PLoS Comput Biol 7(6): e1002075
  119. Abidin ZZ, Arshad MR, Ngah UK (2011): A simulation based fly optimization algorithm for swarms of mini autonomous surface vehicles application. Ind. J. Geo-Mar. Sci. 40(2): 250-266
  120. Flammang BE, Porter ME (2011): Bioinspiration: Applying Mechanical Design to Experimental Biology. Integr Comp Biol. 51 (1): 128-132
  121. Zou S, Liedo P, Altamirano-Robles L, Cruz-Enriquez J, Morice A, Ingram DK, Kaub K, Papadopoulos N, Carey JR (2011): Recording Lifetime Behavior and Movement in an Invertebrate Model. PLoS ONE 6(4): e18151.
  122. Glaser SM, Ye H, Maunder MN, MacCall AD, Fogarty MJ, Sugihara G (2011): Detecting and forecasting complex nonlinear dynamics in spatially-structured catch-per-unit-effort time series for North Pacific albacore (Thunnus alalunga). Can. J. Fish. Aquat. Sci. 68: 400–412
  123. Nurzaman SG, Matsumoto Y, Nakamura Y, Shirai K, Koizumi S, Ishiguro H. (2011): From Lévy to Brownian: a computational model based on biological fluctuation. PLoS One. 6(2):e16168
  124. Nayakar CSM, Srikanth R (2010): Quantum randomness and free will. arXiv:1011.4898v1
  125. Tang S, Juusola M (2010): Intrinsic Activity in the Fly Brain Gates Visual Information during Behavioral Choices. PLoS ONE 5(12): e14455. doi:10.1371/journal.pone.0014455
  126. Abidin ZZ, Arshad MR, Ngah UK (2010): Waypoint control of drosobots: Swarms of mini ASVs. IEEE Symposium on Industrial Electronics and Applications, art. no. 5679401, pp. 556-561
  127. Tanimura Y, Yang MC, Ottens AK, Lewis MH (2010): Development and temporal organization of repetitive behavior in an animal model. Dev Psychobiol. 52(8):813-824
  128. Gal R, Libersat F (2010): On predatory wasps and zombie cockroaches: Investigations of “free will” and spontaneous behavior in insects. Commun Integr Biol. 3(5):458-61
  129. Abidin ZZ, Ngah UK, Arshad MR, Ping OB (2010): A novel fly optimization algorithm for swarming application2010 IEEE Conference on Robotics Automation and Mechatronics (RAM) 425-428, DOI: 10.1109/RAMECH.2010.5513157
  130. Tanimura Y, Yang MC, Ottens AK, Lewis MH (2010): Development and temporal organization of repetitive behavior in an animal model. Dev Psychobiol. 2010 Jul 6. DOI: 10.1002/dev.20477
  131. Gardiner J, Overall R, Marc J (2010): The Fractal Nature of the Brain: EEG Data Suggests That the Brain Functions as a “Quantum Computer” in 5-8 Dimensions. NeuroQuantology 2: 137-141
  132. He BJ, Zempel JM, Snyder AZ, Raichle ME (2010): The temporal structures and functional significance of scale-free brain activity. Neuron. 66(3):353-369
  133. Stewart FJ, Baker DA, Webb B (2010): A model of visual-olfactory integration for odour localisation in free-flying fruit flies. J Exp Biol. 213(11):1886-1900
  134. Gal R, Libersat F (2010): A Wasp Manipulates Neuronal Activity in the Sub-Esophageal Ganglion to Decrease the Drive for Walking in Its Cockroach Prey. PLoS ONE 5(4): e10019
  135. Frye MA (2010): Multisensory systems integration for high-performance motor control in flies. Curr Opin Neurobiol. 20 (3): 347-352
  136. Hong YY, Velegol D, Chaturvedi, N, Sen, A (2010): Biomimetic behavior of synthetic particles: from microscopic randomness to macroscopic control. Phys. Chem. Chem. Phys. 12(7): 1423-1435
  137. Kagaya K, Takahata m (2010): Readiness Discharge for Spontaneous Initiation of Walking in Crayfish. J Neurosci. 30(4):1348-1362
  138. Nurzaman SG, Matsumoto Y, Nakamura Y, Shirai K, Koizumi S, Ishiguro H (2010): An adaptive switching behavior between levy and Brownian random search in a mobile robot based on biological fluctuation. Presented at the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE. DOI: 10.1109/IROS.2010.5651671
  139. Nurzaman SG, Matsumoto Y, Nakamura Y, Koizumi S, Ishiguro H (2009): Biologically inspired adaptive mobile robot search with and without gradient sensing. Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems, St. Louis, MO, USA Pages: 142-147
  140. Remy SL (2009): How to teach a new robot new tricks-an interactive learning framework applied to service robotics. PhD Dissertation, Georgia Institute of Technology, USA
  141. Abidin ZZ, Arshad MR, Ngah UK (2009): A Survey: Animal-Inspired Metaheuristic Algorithms. 2nd Postgraduate Colloquium School of Electrical & Electronic USM, EEPC 2009, Bukit Jawi Golf Resort, 2nd November 2009
  142. Stewart FJ (2009): Modelling visual-olfactory integration in free-flying Drosophila. PhD dissertation, University of Edinburgh, UK
  143. Koch C (2009): Free Will, Physics, Biology, and the Brain. In: Understanding Complex Systems: Downward Causation and the Neurobiology of Free Will. (Springer Berlin / Heidelberg); 31-52. ISBN: 978-3-642-03204-2
  144. Bartumeus F Catalan J (2009): Optimal search behavior and classic foraging theory. J Phys A: Math Theor. 42(43): 434002
  145. Chechkin, AV, Hofmann, M,; Sokolov, IM (2009): Continuous-time random walk with correlated waiting times Phys Rev. E 80 (3): Art. No. 031112 Part 1
  146. Chow DM, Frye MA (2009): The neuro-ecology of resource localization in Drosophila: behavioral components of perception and search. Fly (Austin). 3(1):50-61
  147. Yanagawa T, Mogi K. (2009): Analysis of ongoing dynamics in neural networks. Neurosci Res. 64(2):177-184.
  148. Steven Shaviro (2009): Without Criteria: Kant, Whitehead, Deleuze, and Aesthetics (Cambridge: MIT Press).
  149. Ryser, P (2009): Creative Choice: How the Mind could Causally Affect the Brain. J Consc Stud. 16(2-3): 6-29
  150. Bartumeus F (2009): Behavioral intermittence, Lévy patterns, and randomness in animal movement. Oikos. 118(4): 488-494
  151. Krstic D, Boll W, Noll M (2009): Sensory integration regulating male courtship behavior in Drosophila. PLoS ONE. 4(2):e4457
  152. Vacariu G (2008): Epistemologicallky different worlds. Editura Universitatii din Bucuresti, ISBN 978-973-737-442-4
  153. Bartumeus F, Levin SA (2008): Fractal reorientation clocks: Linking animal behavior to statistical patterns of search. Proc Natl Acad Sci U S A. 105(49):19072-19077
  154. Dees ND, Bahar S, Moss F (2008): Stochastic resonance and the evolution of Daphnia foraging strategy. Phys. Biol. 5: 1-6
  155. Chikamoto K, Kagaya K, Takahata M (2008): Electromyographic Characterization of Walking Behavior Initiated Spontaneously in Crayfish. Zool. Sci. 25(8): 783–792
  156. Takahashi H, Horibe N, Ikegami T, Shimada M (2008): Analyzing house fly’s exploration behavior with autoregression methods. J. Phys. Soc. Jpn. 77(8): 084802
  157. Schoppik D, Nagel KI, Lisberger SG (2008): Cortical Mechanisms of Smooth Eye Movements Revealed by Dynamic Covariations of Neural and Behavioral Responses. Neuron 58, 248–260
  158. Meixner U (2008): New Perspectives for a Dualistic Conception of Mental Causation. J. Consc. Stud. 15(1): 17-38
  159. Artzy-Randrup Y, Bartumeus F, Mahoney J (2007): Human Random Search Strategies in a Soccer Field. Paper presented at the 2007 Complex Systems Summer School, Santa Fe.
  160. Paixão T (2007): The Stochastic Basis of Somatic Variation. Doctoral thesis, University of Porto, Portugal.
  161. Hong Y, Blackman NMK, Kopp ND, Sen A, Velegol D (2007): Chemotaxis of Nonbiological Colloidal Rods. Phys. Rev. Let. 99, 178103
  162. Niven JE (2007): Ghost in the machine? J. exp. Biol. 210(19): V
Brembs B, Hempel de Ibarra N. (2006): Different parameters support generalization and discrimination learning in Drosophila at the flight simulator. Learn Mem. 13(5): 629-637
Citations:
  1. White TE, Dalrymple RL, Herberstein ME, Kemp DJ (2016): The perceptual similarity of orb-spider prey lures and flower colours. Evol Ecol. 31(1): 1–20. DOI: 10.1007/s10682-016-9876-x
  2. Ajuria-Ibarra H, Tapia-McClung H & Rao D (2017): Mapping the variation in spider body colouration from an insect perspective. Evol Ecol. 31(5): 663–681. DOI: 10.1007/s10682-017-9904-5
  3. Robledo-Ospina LE, Escobar-Sarria F, Troscianko J & Rao D (2017): Two ways to hide: predator and prey perspectives of disruptive coloration and background matching in jumping spiders. Biol J Linnean Soc. 122(4): 752–764. DOI: 10.1093/biolinnean/blx108
  4. Marcus M, Burnham TC, Stephens DW & Dunlap AS (2017). Experimental evolution of color preference for oviposition in Drosophila melanogaster. J Bioeconomics. 20(1), 125–140. DOI: 10.1007/s10818-017-9261-z
  5. White TE, Kemp DJ (2016): Color polymorphic lures target different visual channels in prey. Evolution. 70(6):1398-1408. doi: 10.1111/evo.12948
  6. Germain M, Blanchet S, Loyau A, Danchin É (2016): Mate-choice copying in Drosophila melanogaster: Impact of demonstration conditions and male-male competition. Behav Processes. 125:76-84. doi: 10.1016/j.beproc.2016.02.002
  7. Cohen S, Benjamini Y, Golani I (2015): Coping with Space Neophobia in Drosophila melanogaster: The Asymmetric Dynamics of Crossing a Doorway to the Untrodden. PLOS ONE 10:(12):e0140207, DOI: 10.1371/journal.pone.0140207
  8. Kelly MM, Gaskett AC (2014): UV reflectance but no evidence for colour mimicry in a putative brood-deceptive orchid Corybas cheesemanii. Curr Zool 60 (1), 104-113
  9. Giurfa M, Menzel R (2013): Cognitive components of insect behavior. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p14-25
  10. van Swinderen B (2011): Attention in Drosophila. Int Rev Neurobiol. 99:51-85
  11. Casimir MJ (2009): On the Origin and Evolution of Affective Capacities in Lower Vertebrates. In: Böttger-Rössler B, Markowitsch HJ (eds.) Emotions as Bio-cultural Processes, p. 1-39. Springer, New York, DOI: 10.1007/978-0-387-09546-2_4
  12. Niggebrügge, C (2008): Untersuchungen zum Farbensehen und Farbenlernen der Honigbiene (Apis mellifera): vom Photorezeptor zum Verhalten. Doctoral thesis , FU Berlin, Germany.
  13. Peng Y, Xi W, Zhang W, Zhang K, Guo A (2007): Experience Improves Feature Extraction in Drosophila. J. Neurosci. 27:5139-5145
Brembs B. and Wiener J. (2006): Context and occasion setting in Drosophila visual learning. Learn. Mem. 13(5): 618-628
Citations:
  1. Leising KJ, Bonardi C (2017): Occasion setting. Behav Proc. 137: 1–4. DOI: 10.3389/fnbeh.2017.00141
  2. Kirkerud NH, Schlegel U, Giovanni Galizia C (2017): Aversive Learning of Colored Lights in Walking Honeybees. Front Behav Neurosci. 11. DOI: 10.3389/fnbeh.2017.00094
  3. Schultheiss P, Buatois A, Avarguès-Weber A, Giurfa M (2017): Using virtual reality to study visual performances of honeybees. Curr Opin Insect Sci. 24:43–50. DOI: 10.1016/j.cois.2017.08.003
  4. Santos-Pata D, Escuredo A, Mathews Z, Verschure PF (2017): Insect behavioral evidence of spatial memories during environmental reconfiguration. 
  5. Ravi S, Garcia JE, Wang C, Dyer AG (2016): The answer is blowing in the wind: free-flying honeybees can integrate visual and mechano-sensory inputs for making complex foraging decisions. J Exp Biol. 219(21): 3465–3472. DOI: 10.1242/jeb.142679
  6. Liu Q, Yang X, Tian J, Gao Z, Wang M, Li Y, Guo A (2016): Gap junction networks in mushroom bodies participate in visual learning and memory in Drosophila.. Elife. 5. pii: e13238. doi: 10.7554/eLife.13238
  7. Farris SM (2016): Insect societies and the social brain. Curr Op Ins Sci. 15: 1-8
  8. Van De Poll MN, Zajaczkowski EL, Taylor GJ, Srinivasan MV, van Swinderen B (2015): Using an abstract geometry in virtual reality to explore choice behaviour: visual flicker preferences in honeybees. J Exp Biol. 218(Pt 21):3448-60. doi: 10.1242/jeb.125138
  9. Avargués-Weber A, Lihoreau M, Isabel G, Giurfa M (2015): Information transfer beyond the waggle dance: observational learning in bees and flies. Front Ecol Evol, 3, DOI: 10.3389/fevo.2015.00024
  10. Vogt K, Schnaitmann C, Dylla KV, Knapek S, Aso Y, Rubin GM, Tanimoto H (2014): Shared mushroom body circuits underlie visual and olfactory memories in Drosophila. eLife, 3:e02395, DOI: 10.7554/eLife.02395
  11. Kottler B, van Swinderen B (2014): Taking a new look at how flies learn. eLife, 3:e03978, DOI: 10.7554/eLife.03978
  12. Guo A, Lu H, Zhang K, Ren Q, Wong YNC (2013): Visual learning and decision making in Drosophila melanogaster. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p378-394
  13. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science 4: 561–582
  14. Zhang X, Ren Q, Guo A (2013): Parallel pathways for cross-modal memory retrieval in Drosophila. J Neurosci. 33(20):8784-8793
  15. Fustiñana MS, Carbó Tano M, Romano A, Pedreira ME (2013): Contextual Pavlovian conditioning in the crab Chasmagnathus. Anim Cogn. 16(2):255-272
  16. Ren Q, Li H, Wu Y, Ren J, Guo A (2012): A GABAergic inhibitory neural circuit regulates visual reversal learning in Drosophila. J Neurosci. 32(34):11524-11538
  17. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  18. van Swinderen B (2011): Attention in Drosophila. Int Rev Neurobiol. 99:51-85
  19. Wessnitzer J, Young JM, Armstrong JD, Webb B (2011): A model of non-elemental olfactory learning in Drosophila. J Comput Neurosci. 32(2):197-212
  20. Young JM, Wessnitzer J, Armstrong JD, Webb B (2011): Elemental and non-elemental olfactory learning in Drosophila. Neurobiol Learn Mem. 96(2):339-352
  21. Farris SM (2011): Are mushroom bodies cerebellum-like structures? Arthropod Struct Dev. 40(4):368-379
  22. Mota T, Giurfa M, Sandoz JC (2011): Color modulates olfactory learning in honeybees by an occasion-setting mechanism. Learn Mem. 18(3):144-155
  23. Farris SM, Schulmeister S (2010): Parasitoidism, not sociality, is associated with the evolution of elaborate mushroom bodies in the brains of hymenopteran insects. Proc Biol Sci. 278 (1707): 940-951
  24. Foucaud J, Burns JG, Mery F (2010): Use of Spatial Information and Search Strategies in a Water Maze Analog in Drosophila melanogaster. PLoS ONE 5(12): e15231
  25. Lau HL (2010): Chemosensory context conditioning in Ceanorhabditis elegans. MSc dissertation, The University of British Columbia
  26. Dunlap-Lehtilä AS (2009): Change and Reliability in the Evolution of Learning and Memory. PhD dissertation, University of Minnesota
  27. Casimir MJ (2009): On the Origin and Evolution of Affective Capacities in Lower Vertebrates. In: Böttger-Rössler B, Markowitsch HJ (eds.) Emotions as Bio-cultural Processes, p. 1-39. Springer, New York, DOI: 10.1007/978-0-387-09546-2_4
  28. van Swinderen B, McCartney A, Kauffman S, Flores K, Agrawal K, Wagner J, Paulk A (2009): Shared Visual Attention and Memory Systems in the Drosophila Brain. PLoS ONE 4(6): e5989.
  29. Seugnet L, Suzuki Y, Stidd R, Shaw PJ. (2009): Aversive Phototaxic Suppression: evaluation of a short-term memory assay in Drosophila melanogaster. Genes Brain Behav. 8(4): 377-389
  30. Bueno JL, Holland PC (2008): Occasion setting in Pavlovian ambiguous target discriminations. Behav Processes. 79(3):132-147
  31. Tanaka NK, Tanimoto H, Ito K. (2008): Neuronal assemblies of the Drosophila mushroom body. J Comp Neurol. 508(5):711-755.
  32. van Swinderen B. (2007): Attention-like processes in Drosophila require short-term memory genes. Science. 315(5818):1590-1593
  33. Peng Y, Xi W, Zhang W, Zhang K, Guo A (2007): Experience Improves Feature Extraction in Drosophila. J. Neurosci. 27:5139-5145
Menzel R.; Brembs, B. and Giurfa M. (2006): Cognition in Invertebrates. In: Kaas, J.H. (ed.) Evolution of Nervous Systems. Academic Press, Oxford ; pp. 403-442
Citations:
  1. Menzel R (2017): Navigation and Communication in Insects. In: Byrne JH (Eds): Learning and Memory: A Comprehensive Reference. 389–405. Elsevier. DOI: 10.1016/B978-0-12-809324-5.21018-3
  2. Schilling M, Cruse H (2017): ReaCog, a Minimal Cognitive Controller Based on Recruitment of Reactive Systems. Front Neurorobotics, 11. DOI: 10.3389/fnbot.2017.00003
  3. Domjan M & Krause M (2017): Generality of the Laws of Learning: From Biological Constraints to Ecological Perspectives. In Byrne JH (Eds): Learning and Memory: A Comprehensive Reference. 189–201. Elsevier. DOI: 10.1016/B978-0-12-809324-5.21012-2
  4. Zhang H & Blumenthal EM (2017): Identification of multiple functional receptors for tyramine on an insect secretory epithelium. Sci Rep. 7(1). DOI: 10.1038/s41598-017-00120-z
  5. Borgeaud C (2016): Strategic social behaviour in wild vervet monkeys. PhD thesis, Université de Neuchâtel
  6. Service EW, Plowright CMS (2015): Food restriction and threat of predation affect visual pattern choices by flower-naïve bumblebees. Learn Motiv. 50: 3-10, DOI:10.1016/j.lmot.2014.10.006
  7. Arien Y, Dag A, Zarchin S, Masci T, Shafir S (2015): Omega-3 deficiency impairs honey bee learning. Proc Natl Acad Sci U S A. 112(51):15761-15766, DOI: 10.1073/pnas.1517375112.
  8. Roth G (2015): Convergent evolution of complex brains and high intelligence. Philos Trans R Soc Lond B Biol Sci. 370(1684). pii: 20150049, DOI: 10.1098/rstb.2015.0049
  9. Falibene A, Roces F, Rössler W (2015): Long-term avoidance memory formation is associated with a transient increase in mushroom body synaptic complexes in leaf-cutting ants. Front. Behav. Neurosci., 9:84 DOI: 10.3389/fnbeh.2015.00084
  10. Tew ER, Adamson A, Hesselberg T (2015): The web repair behaviour of an orb spider. Anim Behav. 103: 137–146, DOI: 10.1016/j.anbehav.2015.02.016
  11. Cheeseman JF, Millar CD, Greggers U, Lehmann K, Pawley MD, Gallistel CR, Warman GR, Menzel R (2014): Way-finding in displaced clock-shifted bees proves bees use a cognitive map. Proc Natl Acad Sci U S A. 111: 8949–8954, DOI: 10.1073/pnas.1408039111
  12. Cruse H, Schilling M (2013): How and to what end may consciousness contribute to action? Attributing properties of consciousness to an embodied, minimally cognitive artificial neural network. Front. Psychol. 4:324
  13. Parmir E (2013): From behavioral plasticity to neuronal computation: An investigation of associative learning in the honeybee brain. PhD thesis, Freie Universität Berlin http://www.diss.fu-berlin.de/diss/receive/FUDISS_thesis_000000094475
  14. Hussaini SA, Menzel R (2013): Mushroom body extrinsic neurons in the honeybee brain encode cues and contexts differently. J Neurosci. 33(17):7154-7164
  15. Eckstein MP, Mack SC, Liston DB, Bogush L, Menzel R, Krauzlis RJ (2013): Rethinking human visual attention: Spatial cueing effects and optimality of decisions by honeybees, monkeys and humans. Vision Res. 2013 Jan 5. doi:pii: S0042-6989(12)00416-6. 10.1016/j.visres.2012.12.011
  16. Carazo P, Fernández-Perea R, Font E (2012): Quantity estimation based on numerical cues in the mealworm beetle (Tenebrio molitor). Front. Psychology 3:502. doi: 10.3389/fpsyg.2012.00502
  17. Jeanson R, Dussutour A, Fourcassié V (2012): Key factors for the emergence of collective decision in invertebrates. Front Neurosci. 6:121
  18. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  19. Giurfa M, Sandoz JC (2012): Invertebrate learning and memory: Fifty years of olfactory conditioning of the proboscis extension response in honeybees. Learn Mem. 19(2):54-66
  20. Pamir E, Chakroborty NK, Stollhoff N, Gehring KB, Antemann V, Morgenstern L, Felsenberg J, Eisenhardt D, Menzel R, Nawrot MP. (2011): Average group behavior does not represent individual behavior in classical conditioning of the honeybee. Learn Mem. 18(11):733-741
  21. Vinauger C, Buratti L, Lazzari CR (2011): Learning the way to blood: first evidence of dual olfactory conditioning in a blood-sucking insect, Rhodnius prolixus. I. Appetitive learning. J Exp Biol. 214(Pt 18):3032-3038
  22. Matsumoto CS, Matsumoto Y, Watanabe H, Nishino H, Mizunami M. (2011): Context-dependent olfactory learning monitored by activities of salivary neurons in cockroaches. Neurobiol Learn Mem. 2011 Sep 10. [Epub ahead of print]
  23. Cruse H, Wehner R (2011): No Need for a Cognitive Map: Decentralized Memory for Insect Navigation. PLoS Comput Biol 7(3): e1002009
  24. Bar-Shaia N, Keasarb T, Shmida A (2011): The use of numerical information by bees in foraging tasks. Behav Ecol 22 (2): 317-325
  25. Gal R, Libersat F (2010): On predatory wasps and zombie cockroaches: Investigations of “free will” and spontaneous behavior in insects. Commun Integr Biol. 3(5):458-61
  26. Roussel E, Sandoz JC, Giurfa M (2010): Searching for learning-dependent changes in the antennal lobe: simultaneous recording of neural activity and aversive olfactory learning in honeybees. Front Behav. Neurosci. 4: 155
  27. Abramson CI, Nolf SL, Mixson TA, Well H (2010): Can Honey Bees Learn the Removal of a Stimulus as a Conditioning Cue? Ethology 116: 1–12 doi: 10.1111/j.1439-0310.2010.01796.x
  28. Bar-Shai N, Keasar T, Shmida A (2010): The use of numerical information by bees in foraging tasks. Center for the study of rationality – Hebrew University of Jerusalem, Discussion Paper # 555 June 2010
  29. Tomina Y, Takahata M. (2010): A behavioral analysis of force-controlled operant tasks in American lobster. Physiol Behav. 101(1): 108-116
  30. Abramson CI (2009): A Study in Inspiration: Charles Henry Turner (1867–1923) and the Investigation of Insect Behavior. Annu. Rev. Entomol. 54:343–359
  31. Wehner R (2009): The architecture of the desert ant’s navigational toolkit (Hymenoptera: Formicidae). Myrmecological News, 12: 85-96
  32. Bozkurt A, Gilmour RF, Sinha A, Stern D, Lal A (2009): Insect–Machine Interface Based Neurocybernetics. IEEE Transactions on Biomedical Engineering 56(6): 1727 – 1733
  33. Josens R, Eschbach C, Giurfa M (2009): Differential conditioning and long-term olfactory memory in individual Camponotus fellah ants. J Exp Biol. 212(Pt 12):1904-1911
  34. Carazo P, Font E, Forteza-Behrendt E, Desfilis E (2009): Quantity discrimination in Tenebrio molitor: evidence of numerosity discrimination in an invertebrate? Anim Cogn. 12(3):463-470
  35. Garzón PC, Keijzer F (2009): Cognition in plants. In: F. Baluška (Ed.) Plant – environment interactions: Behavioral perspective. Elsevier.
  36. Menzel R. (2009): Serial position learning in honeybees. PLoS ONE 4(3): e4694.
  37. Platt M, Dayan P, Dehaene S, McCabe K, Menzel R, Phelps E, Plassmann H, Ratcliff R, Shadlen M, Singer W (2008): Neuronal correlates of decision making. In: Engel C and Singer W (Eds.) Better Than Conscious? Decision Making, the Human Mind, and Implications For Institutions. MIT Press
  38. Menzel R. (2008): Insect minds for human minds. In: Benjamin AS, de Belle JS, Etnyre B, Polk TA(eds.) Human Learning, pp. 271-285, Elsevier
  39. Menzel R. (2007): Electrophysiology and Optophysiology of Complex Brain Functions in Insects. In: North G and Greenspan RJ (eds.) Invertebrate Neurobiology, pp. 53-78, CSHL Press.
  40. Okada R, Rybak J, Manz G, Menzel R. (2007): Learning-related plasticity in PE1 and other mushroom body-extrinsic neurons in the honeybee brain. J Neurosci. 27(43):11736-11747.
  41. van Duijn M, Keijzer F, Franken D (2006): Principles of minimal cognition: Casting cognition as sensorimotor coordination. Adapt. Behav. 14 (2): 157-170
Phillips A.M.; Smart R.; Strauss R.; Brembs B. and Kelly L.E. (2005): The Drosophila black enigma: the molecular and behavioural characterization of the black1 mutant allele. Gene 351:131-142
Citations:
  1. Perkin LC, Gerken AR, Oppert B (2017): RNA-Seq Validation of RNAi Identifies Additional Gene Connectivity in Tribolium castaneum (Coleoptera: Tenebrionidae). Journal of Insect Science. 17(2). DOI: 10.1093/jisesa/iex026
  2. Han Y, Xiong L, Xu Y, Tian T, Wang T (2017): The β-alanine transporter BalaT is required for visual neurotransmission in Drosophila. eLife. 6. DOI: 10.7554/eLife.29146
  3. Minami R, Sato C, Yamahama Y, Kubo H, Hariyama T, Kimura K (2016): An RNAi Screen for Genes Involved in Nanoscale Protrusion Formation on Corneal Lens in Drosophila melanogaster. Zoological Science. 33(6): 583–591. DOI: 10.2108/zs160105
  4. Sugumaran M, Barek H (2016): Critical Analysis of the Melanogenic Pathway in Insects and Higher Animals. International Journal of Molecular Sciences. 17(10):1753. DOI: 10.3390/ijms17101753
  5. Beasley V, Dowse H (2016): Suppression of Tryptophan 2,3-Dioxygenase Produces a Slow Heartbeat Phenotype in Drosophila melanogaster. Journal of Experimental Zoology Part A: Ecological Genetics and Physiology. 325(10):651–664. DOI: 10.1002/jez.2057
  6. Deshmukh R, Baral S, Gandhimathi A, Kuwalekar M, Kunte K (2017): Mimicry in butterflies: co-option and a bag of magnificent developmental genetic tricks. Wiley Interdisciplinary Reviews: Developmental Biology. 7(1): e291. DOI: 10.1002/wdev.291
  7. Arakane Y, Noh MY, Asano T, Kramer KJ (2016): Tyrosine Metabolism for Insect Cuticle Pigmentation and Sclerotization. In: Cohen E, Moussian B (Eds.): Extracellular Composite Matrices in Arthropods (pp. 165–220). Springer, Cham. DOI: 10.1007/978-3-319-40740-1_6
  8. Noh MY, Koo B, Kramer KJ, Muthukrishnan S, Arakane Y (2016): Arylalkylamine N-acetyltransferase 1 gene (TcAANAT1) is required for cuticle morphology and pigmentation of the adult red flour beetle, Tribolium castaneum. Insect Biochemistry and Molecular Biology. 79: 119–129. DOI: 10.1016/j.ibmb.2016.10.013
  9. Noh MY, Muthukrishnan S, Kramer KJ, Arakane Y (2016): Cuticle formation and pigmentation in beetles. Curr Opin Insect Sci. 17, 1–9. doi: 10.1016/j.cois.2016.05.004
  10. Lei Y, Wang Y, Ahola V, Luo S, Xu C, Wang R (2016): RNA sequencing reveals differential thermal regulation mechanisms between sexes of Glanville fritillary butterfly in the Tianshan Mountains, China. Molecular Biology Reports. 43(12): 1423–1433. DOI: 10.1007/s11033-016-4076-x
  11. Connahs H, Rhen T, Simmons RB (2016): Transcriptome analysis of the painted lady butterfly, Vanessa cardui during wing color pattern development. BMC Genomics. 17(1):270. doi: 10.1186/s12864-016-2586-5
  12. Dai F, Qiao L, Cao C, Liu X, Tong X, He S, Hu H, Zhang L, Wu S, Tan D, Xiang Z, Lu C (2015) Aspartate Decarboxylase is Required for a Normal Pupa Pigmentation Pattern in the Silkworm, Bombyx mori. Sci. Rep., 5, 10885.
  13. Chaturvedi R, Reddig K, Li H-S (2014): Long-distance mechanism of neurotransmitter recycling mediated by glial network facilitates visual function in Drosophila. Proc Natl Acad Sci. 111:2812–2817
  14. Müller R, Jenny A, Stanley P (2013): The EGF Repeat-Specific O-GlcNAc-Transferase Eogt Interacts with Notch Signaling and Pyrimidine Metabolism Pathways in Drosophila. PLoS ONE 8(5): e62835
  15. Ziegler AB, Brüsselbach F, Hovemann BT (2013): Activity and coexpression of Drosophila black with ebony in fly optic lobes reveals putative cooperative tasks in vision that evade electroretinographic detection. J Comp Neurol. 521(6):1207-1224
  16. Aleksandrov ID, Namolovan LN, Aleksandrova MV (2012): Radiation biology of structurally different Drosophila genes. Report III. The black gene: general and molecular characteristics of its radiomutability. Radiats Biol Radioecol. 52(5):453-466
  17. Pulver SR, Berni J (2012): The fundamentals of flying: simple and inexpensive strategies for employing Drosophila genetics in neuroscience teaching laboratories. J Undergrad Neurosci Educ. 11(1):A139-148
  18. Ilg T, Berger M, Noack S, Rohwer A, Gaßel M (2012): Glutamate decarboxylase of the parasitic arthropods Ctenocephalides felis and Rhipicephalus microplus: gene identification, cloning, expression, assay development, identification of inhibitors by high throughput screening and comparison with the orthologs from Drosophila melanogaster and mouse. Insect Biochem Mol Biol. 43(2): 162-177
  19. Pulver SR, Berni J (2012): The Fundamentals of Flying: Simple and Inexpensive Strategies for Employing Drosophila Genetics in Neuroscience Teaching Laboratories. The Journal of Undergraduate Neuroscience Education (JUNE) 11(1):A139-A148
  20. Saenko SV, Jerónimo MA, Beldade P (2012): Genetic basis of stage-specific melanism: a putative role for a cysteine sulfinic acid decarboxylase in insect pigmentation. Heredity (Edinb). 108(6):594-601
  21. Wardill TJ, List O, Li X, Dongre S, McCulloch M, Ting CY, O’Kane CJ, Tang S, Lee CH, Hardie RC, Juusola M (2012): Multiple spectral inputs improve motion discrimination in the Drosophila visual system. Science. 336(6083):925-931
  22. Borycz J, Borycz JA, Edwards TN, Boulianne GL, Meinertzhagen IA (2012): The metabolism of histamine in the Drosophila optic lobe involves an ommatidial pathway: ß-alanine recycles through the retina. J Exp Biol. 215(Pt 8):1399-1411
  23. Saenko SV, Jerónimo MA, Beldade P (2012): Genetic basis of stage-specific melanism: a putative role for a cysteine sulfinic acid decarboxylase in insect pigmentation. Heredity (Edinb). 2012 Jan 11. doi: 10.1038/hdy.2011.127. [Epub ahead of print]
  24. Rund SS, Hou TY, Ward SM, Collins FH, Duffield GE (2011): Genome-wide profiling of diel and circadian gene expression in the malaria vector Anopheles gambiae. Proc Natl Acad Sci U S A. 108(32):E421-430
  25. Ziegler, AB; Hovemann, BT (2011): Aspartate decarboxylase Black as a part of visual signal transduction. J. Neurogen. 24: 51
  26. Richardson G, Ding H, Rocheleau T, Mayhew G, Reddy E, Han Q, Christensen BM, Li J (2010): An examination of aspartate decarboxylase and glutamate decarboxylase activity in mosquitoes. Mol Biol Rep. 37(7):3199-3205
  27. Gallot A, Rispe C, Leterme N, Gauthier JP, Jaubert-Possamai S, Tagu D (2010): Cuticular proteins and seasonal photoperiodism in aphids. Insect Biochem Mol Biol. 40(3):235-240
  28. Richardson G, Ding H, Rocheleau T, Mayhew G, Reddy E, Han Q, Christensen BM, Li J (2009): An examination of aspartate decarboxylase and glutamate decarboxylase activity in mosquitoes. Mol Biol Rep. [Epub ahead of print]
  29. Le Trionnaire G, Francis F, Jaubert-Possamai S, Bonhomme J, De Pauw E, Gauthier JP, Haubruge E, Legeai F, Prunier-Leterme N, Simon JC, Tanguy S, Tagu D (2009): Transcriptomic and proteomic analyses of seasonal photoperiodism in the pea aphid. BMC Genomics 10:456
  30. Arakane Y, Lomakin J, Beeman RW, Muthukrishnan S, Gehrke SH, Kanost MR, Kramer KJ (2009): Molecular and Functional Analyses of Amino Acid Decarboxylases Involved in Cuticle Tanning in Tribolium castaneum. J Biol Chem. 284(24):16584-16594
  31. Davis MM, Primrose DA, Hodgetts RB (2008): A member of the p38 mitogen-activated protein kinase family is responsible for transcriptional induction of Dopa decarboxylase in the epidermis of Drosophila melanogaster during the innate immune response. Mol Cell Biol. 28(15):4883-4895.
  32. Stuart AE, Borycz J, Meinertzhagen IA (2007): The dynamics of signaling at the histaminergic photoreceptor synapse of arthropods. Prog Neurobiol. 82(4):202-227
Brembs B.; Baxter D.A. and Byrne J.H. (2004): Extending In Vitro Conditioning in Aplysia to Analyze Operant and Classical Processes in the Same Preparation. Learn. Mem. 11: 412-420.
Citations:
  1. Cropper EC, Jing J, Perkins MH, Weiss KR (2017): Use of the Aplysia feeding network to study repetition priming of an episodic behavior. J Neurophys. 118(3): 1861–1870. DOI: 10.1152/jn.00373.2017
  2. Simmers J, Sillar KT (2017): Plasticity and Learning in Motor Control Networks. Neurobiology of Motor Control (pp. 417–442). John Wiley & Sons, Inc. DOI: 10.1002/9781118873397.ch13
  3. Zilio D (2016): On the autonomy of psychology from neuroscience: A case study of Skinner’s radical behaviorism and behavior analysis. Rev Gen Psych. 20: 155–170
  4. Basil J, Crook R (2014): Evolution of behavioral and neural complexity: Learning and memory in chambered nautilus. In: Darmaillacq AS, Dickel L, Mather J (eds.): Cephalopod Cognition, pp. 31 – 56, Cambridge University Press.
  5. Bédécarrats A (2014): Étude cellulaire de la genèse et de l’apprentissage d’un comportement motivé chez l’aplysie, PhD dissertation, L´Université de Bordeaux
  6. Dasgupta S, Wörgötter F, Manoonpong P (2014): Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control. Front Neural Circuits, 8:126, DOI: 10.3389/fncir.2014.00126
  7. Zilio, D. (2013): Behavioral unit of selection and the operant-respondent distinction: The role of neurophysiological events in controlling the verbal behavior of theorizing about behavior. Psychological Record, 63(4): 895-918
  8. Mozzachiodi R, Baxter DA, Byrne JH (2013): Comparison of Operant and Classical Conditioning of Feeding Behavior in Aplysia. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p183-193
  9. Bédécarrats A, Cornet C, Simmers J, Nargeot R (2013): Implication of dopaminergic modulation in operant reward learning and the induction of compulsive-like feeding behavior in Aplysia. Learn Mem. 20(6):318-327
  10. Guerra, LGGC, Silva, MTA (2010): Learning processes and the neural analysis of conditioning. Psych Neur. 3(2), doi: 10.3922/j.psns.2010.2.xxx
  11. Nargeot R, Simmers J (2010): Neural mechanisms of operant conditioning and learning-induced behavioral plasticity in Aplysia. Cell Mol Life Sci. 68(5): 803-816
  12. Katzoff A, Miller N, Susswein AJ (2009): Nitric oxide and histamine signal attempts to swallow: A component of learning that food is inedible in Aplysia. Learn Mem. 17(1):839-851
  13. Grasso FW, Basil JA (2009): The evolution of flexible behavioral repertoires in cephalopod molluscs. Brain Behav Evol. 74(3):231-245
  14. Tomsic D, de Astrada MB, Sztarker J, Maldonado H. (2009): Behavioral and neuronal attributes of short- and long-term habituation in the crab Chasmagnathus. Neurobiol Learn Mem. 92(2):176-182
  15. Buganová M (2008): Hemoprotein nitric oxide synthase in Aplysia californica. PhD thesis, University of Karlova. https://dspace.cuni.cz/handle/20.500.11956/16511
  16. Jing J, Vilim FS, Cropper EC, Weiss KR (2008): Neural analog of arousal: persistent conditional activation of a feeding modulator by serotonergic initiators of locomotion. J Neurosci. 28(47):12349-12361.
  17. Nargeot R, Petrissans C, Simmers J. (2007): Behavioral and in vitro correlates of compulsive-like food seeking induced by operant conditioning in Aplysia. J Neurosci. 27(30): 8059-8070
  18. Silva MTA, Goncalves FL, Garcia-Mijares M (2007): Neural events in the reinforcement contingency. Behav. Anal. 30(1): 17-30
  19. Krylov AK, Aleksandrov YI (2007): “Situatedness in an environment” as alternative to stimuli presentation: Model study. Psykhologicheskii Zhurnal 28(2): 106-113
  20. Wright JW, Olson ML, Harding JW (2006): The role of the brain angiotensin system in learning, memory and neural plasticity. In: Trends in Learning Research (ed.: Hogan SH). Nova Publishers, pp. 1-39
  21. Baxter DA, Byrne JH (2006): Feeding behavior of Aplysia: A model system for comparing cellular mechanisms of classical and operant conditioning. Learn. Mem. 13: 669-680
  22. Goel P, Gelperin A. (2006): A neuronal network for the logic of Limax learning. J Comput Neurosci. 21(3):259-270
  23. Katzoff A, Ben-Gedalya T, Hurwitz I, Miller N, Susswein YZ, Susswein AJ. (2006): Nitric oxide signals that aplysia have attempted to eat, a necessary component of memory formation after learning that food is inedible. J Neurophysiol. 96(3):1247-1257
  24. Diaz-Rios M, Miller MW (2006): Target-specific regulation of synaptic efficacy in the feeding central pattern generator of Aplysia: potential substrates for behavioral plasticity? Biol Bull. 210(3):215-29.
  25. Hawkins RD, Clark, GA, Kandel, ER (2006): Operant Conditioning of Gill Withdrawal in Aplysia. J. Neurosci. 26(9):2443-2448
  26. Agin V, Chichery R, Dickel L, Chichery MP. (2006): The “prawn-in-the-tube” procedure in the cuttlefish: habituation or passive avoidance learning? Learn Mem. 13(1):97-101
  27. Jezzini SH, Bodnarova M, Moroz LL. (2005): Two-color in situ hybridization in the CNS of Aplysia californica. J Neurosci Methods. 149(1): 15-25
  28. Reyes FD, Mozzachiodi R, Baxter DA, Byrne JH (2005): Reinforcement in an in vitro analog of appetitive classical conditioning of feeding behavior in Aplysia: Blockade by a dopamine antagonist. Learn. Mem. 12: 216-220
  29. Zhurov Y, Proekt A, Weiss KR, Brezina V. (2005): Changes of internal state are expressed in coherent shifts of neuromuscular activity in Aplysia feeding behavior. J Neurosci. 25(5): 1268-1280.
  30. Giurfa M (2004): “This paper shows that it is possible to study the two major forms of associative…” Evaluation of: [Brembs B et al. Extending in vitro conditioning in Aplysia to analyze operant and classical processes in the same preparation. Learn Mem. 2004 Jul-Aug; 11(4):412-20; doi: 10.1101/lm.74404]. Faculty of 1000, 11 Nov 2004. F1000.com/1022188
Brembs, B (2003): Operant Conditioning in Invertebrates. Curr. Opin. Neurobiol. 13(6): 710-717.
Citations:
  1. Lepeltier T, Bonnardel Y, Sigler P (2018): La révolution antispéciste. Presses Universitaires de France. 978-2130799092
  2. Hinsch M, Komdeur J (2017): Punish the thief—coevolution of defense and cautiousness stabilizes ownership. Behavioral Ecology and Sociobiology. 71(7). DOI: 10.1007/s00265-017-2330-4
  3. Chouhan NS, Mohan K, Ghose A (2017): cAMP signaling mediates behavioral flexibility and consolidation of social status in Drosophila aggression. The Journal of Experimental Biology. 220(23):4502–4514. DOI: 10.1242/jeb.165811
  4. Gaburro J, Nahavandi S, Bhatti A (2017): Insects Neural Model: Potential Alternate to Mammals for Electrophysiological Studies. Series in BioEngineering (pp. 119–130). Springer Singapore. DOI: 10.1007/978-981-10-3957-7_6
  5. Simmers J & Sillar KT (2017): Plasticity and Learning in Motor Control Networks. Neurobiology of Motor Control (pp. 417–442). John Wiley & Sons, Inc. DOI: 10.1002/9781118873397.ch13
  6. Abramson CI, Dinges CW, Wells H (2016): Operant Conditioning in Honey Bees (Apis mellifera L.): The Cap Pushing Response. PLOS ONE. 11(9): e0162347. DOI: 10.1371/journal.pone.0162347
  7. Cassel CS (2016): Bugs After the Bomb: Insect Representations in Postatomic American Fiction and Film. PhD thesis, University of Michigan. https://deepblue.lib.umich.edu/handle/2027.42/133284
  8. Feinberg TE, Mallatt JM (2016): The Ancient Origins of Consciousness: How the Brain Created Experience. The MIT Press. ISBN: 978-0262034333
  9. Bhimani R, Huber R (2015): Operant avoidance learning in crayfish, Orconectes rusticus: Computational ethology and the development of an automated learning paradigm. Learn Behav. 2015 Nov 5. [Epub ahead of print]
  10. Mirwan HB, Mason GJ, Kevan PG (2015): Complex operant learning by worker bumblebees (Bombus impatiens): detour behaviour and use of colours as discriminative stimuli. Insectes Sociaux, 62: 365–377, DOI: 10.1007/s00040-015-0414-6
  11. Hoedjes KM (2014): Natural variation in memory formation among Nasonia parasitic wasps: from genes to behaviour. PhD thesis, Wageningen University
  12. Soltoggio A (2014): Short-term plasticity as cause–effect hypothesis testing in distal reward learning. Biol Cybern. 109: 75–94, DOI: 10.1007/s00422-014-0628-0
  13. Hermann PM, Watson SN, Wildering WC (2014): Phospholipase A2 – nexus of aging, oxidative stress, neuronal excitability, and functional decline of the aging nervous system? Insights from a snail model system of neuronal aging and age-associated memory impairment. Front Genet. 5:419 DOI: 10.3389/fgene.2014.00419
  14. Cyr A, Boukadoum M, Thériault F (2014): Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot’s controller. Front Neurorobot. 8:21 DOI: 10.3389/fnbot.2014.00021
  15. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdiscip Rev Cogn Sci. 4(5): 561–582., DOI: 10.1002/wcs.1248
  16. Palminteri S, Pessiglione M (2013): Reinforcement learning and Tourette syndrome. Int Rev Neurobiol. 112:131-153
  17. Søvik E, Barron AB (2013): Invertebrate Models in Addiction Research. Brain Behav Evol. 82: 153–165
  18. DuRousseau, D. R. (2013): QEEG Biomarkers: Assessment and Selection of Special Operators, and Improving Individual Performance (pp. 562–571). Lecture Notes in Computer Science. Springer-Verlag. doi:10.1007/978-3-642-39454-6_60
  19. Lukowiak K, Dalesman S (2013): Operant Conditioning of Respiration in Lymnaea: The Environmental Context. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p265-279
  20. Mozzachiodi R, Baxter DA, Byrne JH (2013): Comparison of Operant and Classical Conditioning of Feeding Behavior in Aplysia. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p183-193
  21. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science 4: 561–582
  22. Thran J (2013): Ein räumliches Orientierungsgedächtnis im Zentralkomplex von Drosophila melanogaster und die spezifische Rolle von ellipsoid-body-open. PhD thesis. University of Mainz. http://ubm.opus.hbz-nrw.de/volltexte/2013/3415/
  23. Kirkerud NH, Wehmann H-N, Galizia CG and Gustav D (2013): APIS—a novel approach for conditioning honey bees. Front. Behav. Neurosci. 7:29. doi: 10.3389/fnbeh.2013.00029
  24. Alberini CM, Bambah-Mukku D, Chen DY (2012): Memory Consolidation and Its Underlying Mechanisms. In: Memory Mechanisms in Health and Disease: Mechanistic Basis of Memory (ed.: Karl Peter Giese). World Scientific, ISBN 9814366692, 444 pages, pp. 147-171
  25. Milinkeviciute G, Gentile C, Neely GG (2012): Drosophila as a tool for studying the conserved genetics of pain. Clin Genet. 82(4):359-366
  26. Nargeot R, Simmers J (2012): Functional Organization and Adaptability of a Decision-Making Network in Aplysia. Front Neurosci. 6:113
  27. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058
  28. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  29. Kapustjansky, A (2012): In vivo imaging and optogenetic approach to study the formation of olfactory memory and locomotor behaviour in Drosophila melanogaster. PhD Thesis, Julius-Maximilians Universität Würzburg
  30. Dalesman S, Lukowiak K (2012): How Stress Alters Memory in ‘Smart’ Snails. PLoS ONE 7(2): e32334
  31. Dalesman S, Braun MH, Lukowiak K. (2011): Low environmental calcium blocks long-term memory formation in a freshwater pulmonate snail. Neurobiol Learn Mem. 95(4):393-403
  32. Nargeot R, Simmers J (2010): Neural mechanisms of operant conditioning and learning-induced behavioral plasticity in Aplysia. Cell Mol Life Sci. 68(5): 803-816
  33. Tomina Y, Takahata M. (2010): A behavioral analysis of force-controlled operant tasks in American lobster. Physiol Behav. 2010 Apr 29. [Epub ahead of print]
  34. Sokolowski MBC, Disma G, Abramson CI (2010): A paradigm for operant conditioning in Blow Flies (Phormia terrae novae Robineau-Desvoidy, 1830). J exp. Anal. Behav. 93 (1): 81-89
  35. Dayan P, Huys QJ. (2009): Serotonin in Affective Control. Annu Rev Neurosci. 32: 95-126
  36. Khan AM, Spencer GE (2009): Novel neural correlates of operant conditioning in normal and differentially reared Lymnaea. J Exp Biol. 212(Pt 7):922-933
  37. Pitman JL, Dasgupta S, Krashes MJ, Leung B, Perrat PN, Waddell S. (2009): There are many ways to train a fly. Fly (Austin). 3(1): 3-9
  38. Vandersal ND (2008): Rapid spatial learning in a velvet ant (Dasymutilla coccineohirta). Anim Cogn. 11(3):563-567
  39. Lukowiak K, Martens K, Rosenegger D, Browning K, de Caigny P, Orr M (2008): The perception of stress alters adaptive behaviours in Lymnaea stagnalis. J Exp Biol. 211(Pt 11):1747-1756.
  40. VanderSal ND, Hebets EA. (2007): Cross-modal effects on learning: a seismic stimulus improves color discrimination learning in a jumping spider. J Exp Biol. 210(Pt 20):3689-3695.
  41. Henry F, Dauce E, Soula H (2007): Temporal pattern identification using spike-timing dependent plasticity. Neurocomp. 70(10-12): 2009-2016
  42. Kim YC, Lee HG, Han KA. (2007): Classical reward conditioning in Drosophila melanogaster. Genes Brain Behav. 6(2):201-207
  43. Daucé E, Henry F (2006): Hebbian learning in large recurrent neural networks. Paper presented at NeuroComp 2006, 202
  44. Dupuy F, Sandoz JC, Giurfa M, Josens R (2006): Individual olfactory learning in Camponotus ants. Anim. Behav. 72: 1081-1091
  45. Baxter DA, Byrne JH (2006): Feeding behavior of Aplysia: A model system for comparing cellular mechanisms of classical and operant conditioning. Learn. Mem. 13: 669-680
  46. Aragona BJ, Carelli RM. (2006): Dynamic neuroplasticity and the automation of motivated behavior. Learn Mem. 13(5):558-559
  47. Hawkins RD, Clark, GA, Kandel, ER (2006): Operant Conditioning of Gill Withdrawal in Aplysia. J. Neurosci. 26(9):2443-2448
  48. Barbas D, Zappulla JP, Angers S, Bouvier M, Mohamed HA, Byrne JH, Castellucci VF, Desgroseillers L. (2006): An aplysia dopamine-like receptor: molecular and functional characterization. J Neurochem. 96(2):414-427
  49. Burggren WW, Monticino MG. (2005): Assessing physiological complexity.J Exp Biol. 208(17): 3221-3232.
  50. Reyes FD, Mozzachiodi R, Baxter DA, Byrne JH (2005): Reinforcement in an in vitro analog of appetitive classical conditioning of feeding behavior in Aplysia: Blockade by a dopamine antagonist. Learn. Mem. 12: 216-220
  51. Manev H, Dimitrijevic N. (2005): Fruit flies for anti-pain drug discovery. Life Sci. 76(21):2403-7.
  52. Dacher M (2005): Role des recepteurs nicotiniques dans differentes formes de memoire chez l’abeille Apis mellifera. Doctoral thesis, Université de Toulouse, Paul Sabatier, France
  53. Demirci S, Esel E (2004): The biological mechanisms of learning and memory, and their relationships with psychiatric disorders. Anatol. J. Psych. 5:239-248
  54. Lamme VAF (2004): Weg met de psychologie! Netherlands journal of psychology 59: 90–100
Brembs, B (2003): Operant Reward Learning in Aplysia. Curr. Dir. Psych. Sci. 12 (6): 218-221.
Citations:
  1. Sakurai A, Katz PS (2015): Phylogenetic and individual variation in gastropod central pattern generators. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 201: 829–839, DOI: 10.1007/s00359-015-1007-6
  2. Shi Z, Lu C, Sun X, Wang Q, Chen S, Li Y, Qu L, Chen L, Bu L, Liao D, Liu X (2015): Tong Luo Jiu Nao ameliorates Aß1–40-induced cognitive impairment on adaptive behavior learning by modulating ERK/CaMKII/CREB signaling in the hippocampus. BMC Complement Altern Med. 15, DOI: 10.1186/s12906-015-0584-9
  3. Bédécarrats A (2014): Étude cellulaire de la genèse et de l’apprentissage d’un comportement motivé chez l’aplysie, PhD dissertation, L´Université de Bordeaux
  4. Cyr A, Boukadoum M, Thériault F (2014): Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot’s controller. Front Neurorobot. 8:21 DOI: 10.3389/fnbot.2014.00021
  5. Le Pelley ME (2014): Primate polemic: Commentary on Smith, Couchman, and Beran (2014). J Comp Psych 128: 132–134, DOI:10.1037/a0034227
  6. Radecki G, Nargeot R, Jelescu IO, Le Bihan D, Ciobanu L (2014): Functional magnetic resonance microscopy at single-cell resolution in Aplysia californica. Proc Natl Acad Sci U S A 111: 8667–8672, DOI: 10.1073/pnas.1403739111
  7. Sieling F, Bédécarrats A, Simmers J, Prinz AA, Nargeot R (2014): Differential roles of nonsynaptic and synaptic plasticity in operant reward learning-induced compulsive behavior. Curr Biol. 24(9):941-950
  8. Jain P, Bhalla US (2014): Transcription Control Pathways Decode Patterned Synaptic Inputs into Diverse mRNA Expression Profiles. PLoS ONE, 9:e95154. DOI: 10.1371/journal.pone.0095154
  9. Zilio D (2013): Behavioral unit of selection and the operant-respondent distinction: The role of neurophysiological events in controlling the verbal behavior of theorizing about behavior. Psychological Record, 63(4): 895-918
  10. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science 4: 561–582
  11. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res 229: 91–105, DOI: 10.1016/j.bbr.2011.12.044
  12. Casimir MJ (2009): On the Origin and Evolution of Affective Capacities in Lower Vertebrates. In: Böttger-Rössler B, Markowitsch HJ (eds.) Emotions as Bio-cultural Processes, p. 1-39. Springer, New York, DOI: 10.1007/978-0-387-09546-2_4
  13. Baxter DA, Byrne JH (2006): Feeding behavior of Aplysia: A model system for comparing cellular mechanisms of classical and operant conditioning. Learn. Mem. 13: 669-680
  14. Goldman MS, Darkes J, Reich RR, Brandon KO (2006): From DNA to conscious thought: The influence of anticipatory processes on human alcohol consumption. In: Munafò M, Albery IP (Eds) Cognition and addiction. (pp. 147-184). New York, NY, US: Oxford University Press. x, 307 pp.
  15. Reich RR, Noll JA, Goldman MS. (2005): Cue patterns and alcohol expectancies: how slight differences in stimuli can measurably change cognition. Exp Clin Psychopharmacol. 13(1): 65-71.
Brembs B.; Lorenzetti F.D.; Reyes F.D.; Baxter D.A. and Byrne J.H. (2002): Operant Reward Learning in Aplysia: Neuronal Correlates and Mechanisms. Science 296: 1706-1709.
Citations:
  1. Lepeltier T, Bonnardel Y, Sigler P (2018): La révolution antispéciste. Presses Universitaires de France. 978-2130799092
  2. Casado-Aranda LA, Martínez-Fiestas M, Sánchez-Fernández J (2018): Neural effects of environmental advertising: An fMRI analysis of voice age and temporal framing. Journal of Environmental Management. 206:664–675. DOI: 10.1016/j.jenvman.2017.10.006
  3. Simmers J & Sillar KT (2017): Plasticity and Learning in Motor Control Networks. Neurobiology of Motor Control (pp. 417–442). John Wiley & Sons, Inc. DOI: 10.1002/9781118873397.ch13
  4. Silva JE, Ferreira P, Coimbra JL, Menezes I (2017): Theater and Psychological Development: Assessing Socio-Cognitive Complexity in the Domain of Theater. Creativity Research Journal. 29(2):157–166. DOI: 10.1080/10400419.2017.1302778
  5. Mizunami M, Matsumoto Y (2017): Roles of Octopamine and Dopamine Neurons for Mediating Appetitive and Aversive Signals in Pavlovian Conditioning in Crickets. Frontiers in Physiology. 8. DOI: 10.3389/fphys.2017.01027
  6. Xu P, Wang K, Lu C, Dong L, Chen Y, Wang Q, Shi Z et al. (2017): Effects of the chronic restraint stress induced depression on reward-related learning in rats. Behavioural Brain Research. 321:185–192. DOI: 10.1016/j.bbr.2016.12.045
  7. Lu C, Shi Z, Sun X, Pan R, Chen S, Li Y, Qu L et al. (2017): Kai Xin San aqueous extract improves Aβ 1-40 -induced cognitive deficits on adaptive behavior learning by enhancing memory-related molecules expression in the hippocampus. Journal of Ethnopharmacology. 201:73–81. DOI: 10.1016/j.jep.2016.10.002
  8. Hernandez JS, Wainwright ML, Mozzachiodi R (2017): Long-term sensitization training in Aplysia decreases the excitability of a decision-making neuron through a sodium-dependent mechanism. Learning & Memory. 24(6):257–261. DOI: 10.1101/lm.044883.116
  9. Holca-Lamarre R, Lücke J, Obermayer K (2017): Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations. Frontiers in Computational Neuroscience. 11. DOI: 10.3389/fncom.2017.00054
  10. Weisz HA, Wainwright ML, Mozzachiodi R (2017): A novel in vitro analog expressing learning-induced cellular correlates in distinct neural circuits. Learning & Memory. 24(8):331–340. DOI: 10.1101/lm.045229.117
  11. Cai Z, Neveu CL, Baxter DA, Byrne JH, Aazhang B (2017): Inferring neuronal network functional connectivity with directed information. Journal of Neurophysiology. 118(2):1055–1069. DOI: 10.1152/jn.00086.2017
  12. Butlin P (2017): Why Hunger is not a Desire. Review of Philosophy and Psychology. 8(3):617–635. DOI: 10.1007/s13164-017-0332-9
  13. Cyr A, Avarguès-Weber A, Thériault F (2017): Sameness/difference spiking neural circuit as a relational concept precursor model: A bio-inspired robotic implementation. Biologically Inspired Cognitive Architectures. 21:59–66. DOI: 10.1016/j.bica.2017.05.001
  14. Mather JA, Dickel L (2017): Cephalopod complex cognition. Current Opinion in Behavioral Sciences. 16:131–137. DOI: 10.1016/j.cobeha.2017.06.008
  15. Wong-Lin K, Wang DH, Moustafa AA, Cohen JY, Nakamura K (2017): Toward a multiscale modeling framework for understanding serotonergic function. Journal of Psychopharmacology. 31(9):1121–1136. DOI: 10.1177/026988111769961
  16. Nargeot R, Bédécarrats A (2017): Electrical Synapses and Learning–Induced Plasticity in Motor Rhythmogenesis. In: Jing J (Ed.): Network Functions and Plasticity (pp. 109–136). Elsevier. DOI: 10.1016/B978-0-12-803471-2.00006-0
  17. Byrne JH (Ed) (2017): Learning and Memory: A Comprehensive Reference. Elsevier. DOI: 10.1016/B978-0-12-805159-7.01001-9
  18. Siddique N, Dhakan P, Rano I, Merrick K (2017): A Review of the Relationship between Novelty, Intrinsic Motivation and Reinforcement Learning. Journal of Behavioral Robotics. 8(1). DOI: 10.1515/pjbr-2017-0004
  19. Benjamin PR, Kemenes G (2017): Behavioral and circuit analysis of learning and memory in mollusks. In: Byrne JH (Ed): Learning and Memory: A Comprehensive Reference (Second Edition, pp. 427–440). Oxford: Elsevier. ISBN: 9780128051597
  20. Ciobanu L (2017): Microscopic Magnetic Resonance Imaging: A Practical Perspective. CRC Press. ISBN: 9789814774420
  21. Huang J, Ruan X, Yu N, Fan Q, Li J, Cai J (2016): A Cognitive Model Based on Neuromodulated Plasticity. In: Computational Intelligence and Neuroscience, (2016):1–15. Hindawi Limited. DOI: 10.1155/2016/4296356
  22. de Araujo IE (2016): High fat takes the low road to the brain’s reinforcement system. Current Opinion in Behavioral Sciences. 9:158–162. DOI: 10.1016/j.cobeha.2016.04.013
  23. Awata H, Wakuda R, Ishimaru Y, Matsuoka Y, Terao K, Katata S, Matsumoto Y et al. (2016): Roles of OA1 octopamine receptor and Dop1 dopamine receptor in mediating appetitive and aversive reinforcement revealed by RNAi studies. Scientific Reports. 6(1). DOI: 10.1038/srep29696
  24. Bronfman ZZ, Ginsburg S, Jablonka E (2016): The Transition to Minimal Consciousness through the Evolution of Associative Learning. Frontiers in Psychology. 7. DOI: 10.3389/fpsyg.2016.01954
  25. Wolfe KD, Wainwright ML, Smee DL, Mozzachiodi R (2016): Eat or be eaten? Modifications of Aplysia californica feeding behaviour in response to natural aversive stimuli. Animal Behaviour. 120:123–133. DOI: 10.1016/j.anbehav.2016.07.030
  26. Kemenes I, Kemenes G (2016): PACAP and Learning in Invertebrates. In: Current Topics in Neurotoxicity (pp. 43–50). Springer International Publishing. DOI: 10.1007/978-3-319-35135-3_4
  27. Kool VK, Agrawal R (2016): Technology, Psychology, and Evolution. In: Psychology of Technology (pp. 43–83). Springer International Publishing. DOI: 10.1007/978-3-319-45333-0_2
  28. Wang J (2016): An Ecology of Literacy: A Context-based Inter-disciplinary Curriculum for Chinese as a Foreign Language. PhD thesis, The Ohio State University. https://etd.ohiolink.edu/pg_10?0::NO:10:P10_ACCESSION_NUM:osu1461251633
  29. Feinberg TE, Mallatt JM (2016): The Ancient Origins of Consciousness: How the Brain Created Experience. The MIT Press. ISBN: 978-0262034333
  30. Awata H, Wakuda R, Ishimaru Y, Matsuoka Y, Terao K, Katata S, Matsumoto Y, Hamanaka Y, Noji S, Mito T, Mizunami M (2016): Roles of OA1 octopamine receptor and Dop1 dopamine receptor in mediating appetitive and aversive reinforcement revealed by RNAi studies. Sci Rep. 6:29696
  31. De Araujo IE (2016): High fat takes the low road to the brain’s reinforcement system. Curr Opin Behav Sci. 9, 158–162. doi: 10.1016/j.cobeha.2016.04.013
  32. Trout JD (2016): Wondrous Truths: The Improbable Triumph of Modern Science. Oxford University Press. 264p, ISBN: 9780199385072
  33. Lakin MR, Stefanovic D (2016): Supervised Learning in Adaptive DNA Strand Displacement Networks. ACS Synth Biol. 2016 May 11. [Epub ahead of print]
  34. Bartoszeck FK, Chang YC, Bartoszeck AB (2016): A Possible Role of Basic Neurophysiology in Explanation of Mind by Psychology. Revista Psicologia e Saúde 8(1): 44-51
  35. Silverman K, Jarvis BP, Jessel J, Lopez AA (2016): Incentives and motivation. Translational Issues in Psychological Science, 2: 97–100
  36. Yang CY, Yu K, Wang Y, Chen SA, Liu DD, Wang ZY, Su YN, Yang SZ, Chen TT, Livnat I, Vilim FS, Cropper EC, Weiss KR, Sweedler JV, Jing J (2016): Aplysia Locomotion: Network and Behavioral Actions of GdFFD, a D-Amino Acid-Containing Neuropeptide. PLOS ONE, 11, DOI: 10.1371/journal.pone.0147335
  37. Bhimani R, Huber R (2015): Operant avoidance learning in crayfish, Orconectes rusticus: Computational ethology and the development of an automated learning paradigm. Learning & Behavior. 44(3):239–249. DOI: 10.3758/s13420-015-0205-y
  38. Carballo F, Freidin E, Bentosela M (2015): Estudios Sobre Cooperación en Perros Domésticos: una Revisión Crítica. Revista Colombiana de Psicología. 24(1):145–163. DOI: 10.15446/rcp.v24n1.41221
  39. Kemenes G (2015): Dynamic Molecular Mechanisms of Memory Consolidation after Single-Trial Food-Reward Classical Conditioning in Lymnaea. In: Sakakibara M, Ito E (eds.) Memory Consolidation. pp. 127-141. Nova. ISBN: 978-1-63482-623-5
  40. Newquist G, Gardner RA (2015): Reconsidering Food Reward, Brain Stimulation, and Dopamine: Incentives Act Forward. Am J Psychol. 128(4):431-444
  41. Carballo F, Freidin E, Bentosela M. (2015): Estudios sobre cooperación en perros domésticos: una revisión crítica. Revista Colombiana de Psicología, 24(1): 145-163, doi: 10.15446/rcp.v24n1.41221
  42. Dickinson KJ, Wainwright ML, Mozzachiodi R (2015): Change in excitability of a putative decision-making neuron in Aplysia serves as a mechanism in the decision not to feed following food satiation. Behav Brain Res. 281:131-136. doi: 10.1016/j.bbr.2014.12.022
  43. Kirszenblat L, van Swinderen B (2015): The Yin and Yang of Sleep and Attention. Trends Neurosci. 38: 776–786, DOI: 10.1016/j.tins.2015.10.001
  44. Awata H, Watanabe T, Hamanaka Y, Mito T, Noji S, Mizunami M (2015): Knockout crickets for the study of learning and memory: Dopamine receptor Dop1 mediates aversive but not appetitive reinforcement in crickets. Sci. Rep. 5:15885 DOI: 10.1038/srep15885
  45. Dorenbosch MM (2015): The Idea of Will, J Cons Expl & Res. 6(7): 449-472
  46. Gillette R, Brown JW (2015): The Sea Slug, Pleurobranchaea californica?: A Signpost Species in the Evolution of Complex Nervous Systems and Behavior . Integr Comp Biol. DOI: 10.1093/icb/icv081
  47. Hawkins RD, Byrne JH (2015): Associative Learning in Invertebrates. Cold Spring Harb Perspect Biol. 7: a021709, DOI: 10.1101/cshperspect.a021709
  48. Cyr A, Thériault F (2015): Action Selection and Operant Conditioning: A Neurorobotic Implementation. Journal of Robotics, 2015, 1–10, DOI: 10.1155/2015/643869
  49. Sakurai A, Katz PS (2015): Phylogenetic and individual variation in gastropod central pattern generators. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 201: 829–839, DOI: 10.1007/s00359-015-1007-6
  50. Shi Z, Lu C, Sun X, Wang Q, Chen S, Li Y, Qu L, Chen L, Bu L, Liao D, Liu X (2015): Tong Luo Jiu Nao ameliorates Aß1–40-induced cognitive impairment on adaptive behavior learning by modulating ERK/CaMKII/CREB signaling in the hippocampus. BMC Complement Altern Med. 15, DOI: 10.1186/s12906-015-0584-9
  51. Aunger R, Curtis V (2015): Gaining Control – How human Behaviour evolved, Oxford University Press, ISBN: 978-0-19-968895-1
  52. Buchta WC, Riegel AC (2015): Chronic cocaine disrupts mesocortical learning mechanisms. Brain Res. 1628: 88–103, DOI: 10.1016/j.brainres.2015.02.003
  53. Weiss SJ & Rosales-Ruiz J (2014): Operant/Classical Conditioning: Comparisons, Intersections and Interactions: The 2014 Winter Conference on Animal Learning and Behavior Focus and Research Seminar Sessions. International Journal of Comparative Psychology. 27(4). https://escholarship.org/uc/item/4c46c9gg
  54. Soltoggio A (2014): Short-term plasticity as cause–effect hypothesis testing in distal reward learning. Biol Cybern. 109: 75–94, DOI: 10.1007/s00422-014-0628-0
  55. Jun H (2014): Cognitive Learning and Memory Systems using Spiking Neural, PhD dissertation, National University of Singapore
  56. Lakin MR, Minnich A, Lane T, Stefanovic D (2014): Design of a biochemical circuit motif for learning linear functions. J R Soc Interface 11, DOI: 10.1098/rsif.2014.0902
  57. Cyr A, Boukadoum M, Thériault F (2014): Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot’s controller. Front Neurorobot. 8:21 DOI: 10.3389/fnbot.2014.00021
  58. Le Pelley ME (2014): Primate polemic: Commentary on Smith, Couchman, and Beran (2014). J Comp Psych 128: 132–134, DOI:10.1037/a0034227
  59. Dasgupta S, Wörgötter F, Manoonpong P (2014): Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control. Front Neural Circuits, 8:126, DOI: 10.3389/fncir.2014.00126
  60. Soltoggio,A., Lemme,A., Reinhart,F. and Steil,J.J. (2013) Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances. Front. Neurorobot., 7, DOI: 10.3389/fnbot.2013.00006
  61. Radecki G, Nargeot R, Jelescu IO, Le Bihan D, Ciobanu L (2014): Functional magnetic resonance microscopy at single-cell resolution in Aplysia californica. Proc Natl Acad Sci U S A 111: 8667–8672, DOI: 10.1073/pnas.1403739111
  62. Sieling F, Bédécarrats A, Simmers J, Prinz AA, Nargeot R (2014): Differential roles of nonsynaptic and synaptic plasticity in operant reward learning-induced compulsive behavior. Curr Biol. 24(9):941-950
  63. Jain P, Bhalla US (2014): Transcription Control Pathways Decode Patterned Synaptic Inputs into Diverse mRNA Expression Profiles. PLoS ONE 9(5): e95154
  64. Kandel ER, Dudai Y, Mayford MR (2014): The molecular and systems biology of memory. Cell. 157(1):163-186
  65. Schacher S, Hu J-Y (2014): The less things change, the more they are different: contributions of long-term synaptic plasticity and homeostasis to memory. Learn Mem 21:128–134
  66. Zilio, D. (2013): Behavioral unit of selection and the operant-respondent distinction: The role of neurophysiological events in controlling the verbal behavior of theorizing about behavior. Psychological Record, 63(4): 895-918
  67. Kemenes G (2013): Molecular and Cellular Mechanisms of Classical Conditioning in the Feeding System of Lymnaea. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p252-264
  68. Benjamin P (2013): A Systems Analysis of Neural Networks Underlying Gastropod Learning and Memory. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p163-172
  69. Mozzachiodi R, Baxter DA, Byrne JH (2013): Comparison of Operant and Classical Conditioning of Feeding Behavior in Aplysia. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p183-193
  70. Hastings M, Farah CA, Sossin WS (2013): Roles of Protein Kinase C and Protein Kinase M in Aplysia Learning. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p221-235
  71. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science 4: 561–582
  72. Weatherill DB, Dunn TW, McCamphill PK, Sossin WS (2013): Exploring mechanisms of synaptic plasticity using exogenous expression of proteins at the sensory-to-motor neuron synapse of Aplysia. Neuromethods, 81: 61-91
  73. Shi Z, Chen L, Li S, Chen S, Sun X, Sun L, Li Y, Zeng J, He Y, Liu X (2013): Chronic scopolamine-injection-induced cognitive deficit on reward-directed instrumental learning in rat is associated with CREB signaling activity in the cerebral cortex and dorsal hippocampus. Psychopharmacology (Berl). 230:245–260
  74. Bédécarrats A, Cornet C, Simmers J, Nargeot R (2013): Implication of dopaminergic modulation in operant reward learning and the induction of compulsive-like feeding behavior in Aplysia. Learn Mem. 20(6):318-327
  75. Schultz W (2013): Updating dopamine reward signals. Curr Opin Neurobiol. 23(2): 229–238. doi:pii: S0959-4388(12)00186-9. 10.1016/j.conb.2012.11.012.
  76. Shields-Johnson ME, Hernandez JS, Torno C, Adams KM, Wainwright ML, Mozzachiodi R (2012): Effects of aversive stimuli beyond defensive neural circuits: Reduced excitability in an identified neuron critical for feeding in Aplysia. Learn Mem. 20(1):1-5
  77. Shi Z, Chen S, Chen L, Sun X, Song G, Wang Q, Chang Q, Li H, Li Y, Qu L, Liu X (2012): Evaluation of reward-relevant learning and memory behavior with operant conditioning task in rats. Acta Laboratorium Animalis Scientia Sinica, 20 (4): 9-15
  78. Gantt EE, Melling BS, Reber JS (2012): Mechanisms or metaphors? The emptiness of evolutionary psychological explanations. Theory Psychology 22(6): 823-841
  79. Hirayama K, Catanho M, Brown JW, Gillette R (2012): A core circuit module for cost/benefit decision. Front Neurosci. 6:123
  80. Soltoggio A, Stanley KO (2012): From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation. Neural Netw. 34:28-41
  81. Shi Z, Sun X, Liu X, Chen S, Chang Q, Chen L, Song G, Li H. (2012): Evaluation of an Aß(1-40)-induced cognitive deficit in rat using a reward-directed instrumental learning task. Behav Brain Res. 234(2):323-333
  82. Harris CA, Buckley CL, Nowotny T, Passaro PA, Seth AK, Kemenes G, O’Shea M (2012): Multi-neuronal refractory period adapts centrally generated behaviour to reward. PLoS One. 7(7):e42493
  83. Nargeot R, Simmers J (2012): Functional Organization and Adaptability of a Decision-Making Network in Aplysia. Front Neurosci. 6:113
  84. Susswein AJ, Chiel HJ. (2012): Nitric oxide as a regulator of behavior: New ideas from Aplysia feeding. Prog Neurobiol. 97(3):304-317
  85. Eschbach C (2012): Classical and operant learning in the larvae of Drosophila melanogaster. PhD thesis, University of Würzburg, http://opus.bibliothek.uni-wuerzburg.de/volltexte/2012/7058
  86. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  87. Acheampong A, Kelly K, Shields-Johnson M, Hajovsky J, Wainwright M, Mozzachiodi R (2012): Rapid and persistent suppression of feeding behavior induced by sensitization training in Aplysia. Learn Mem. 19(4):159-163
  88. Cheu EY, Quek C, Ng SK (2012): ARPOP: An Appetitive Reward-Based Pseudo-Outer-Product Neural Fuzzy Inference System Inspired From the Operant Conditioning of Feeding Behavior in Aplysia. IEEE Transactions on Neural Networks and Learning Systems, 23(2): 317 – 329
  89. Kappeler PM (2012): Entwicklung und Kontrolle des Verhaltens. In: Verhaltensbiologie, Springer Lehrbuch, DOI: 10.1007/978-3-642-20653-5
  90. Ponulak F, Kasinski A (2011): Introduction to spiking neural networks: Information processing, learning and applications. Acta Neurobiol Exp (Wars). 71(4):409-433
  91. Lorenzetti FD, Baxter DA, Byrne JH (2011): Classical conditioning analog enhanced acetylcholine responses but reduced excitability of an identified neuron. J Neurosci. 31(41):14789-14793.
  92. Miller N, Saada R, Markovich S, Hurwitz I, Susswein AJ. (2011): L-arginine via nitric oxide is an inhibitory feedback modulator of Aplysia feeding. J Neurophysiol. 105(4):1642-1650
  93. Cheu EY, Quek C, Ng SK (2010): Time Series Forecasting With Appetitive Reward-based Pseudo-Outer-Product Fuzzy Neural Network. The 2010 International Joint Conference on Neural Networks (IJCNN), doi: 10.1109/IJCNN.2010.5596738
  94. Guerra, LGGC, Silva, MTA (2010): Learning processes and the neural analysis of conditioning. Psych Neur. 3(2), doi: 10.3922/j.psns.2010.2.xxx
  95. Barron AB, Søvik E, Cornish JL (2010): The roles of dopamine and related compounds in reward-seeking behavior across animal phyla. Front Behav Neurosci. 4:163
  96. Nargeot R, Simmers J (2010): Neural mechanisms of operant conditioning and learning-induced behavioral plasticity in Aplysia. Cell Mol Life Sci. 68(5): 803-816
  97. Pirger Z, László Z, Kemenes I, Tóth G, Reglodi D, Kemenes G (2010): A homolog of the vertebrate pituitary adenylate cyclase-activating polypeptide is both necessary and instructive for the rapid formation of associative memory in an invertebrate. J Neurosci. 30(41):13766-13773
  98. Wu JS, Vilim FS, Hatcher NG, Due MR, Sweedler JV, Weiss KR, Jing J. (2010): A Composite Modulatory Feedforward Loop Contributes to the Establishment of a Network State. J Neurophysiol. 2010 Feb 24. [Epub ahead of print]
  99. Mozzachiodi R, Byrne JH (2010): More than synaptic plasticity: role of nonsynaptic plasticity in learning and memory. Trends Neurosci. 33 (1): 17-26
  100. Katzoff A, Miller N, Susswein AJ (2009): Nitric oxide and histamine signal attempts to swallow: A component of learning that food is inedible in Aplysia. Learn Mem. 17(1):839-851
  101. Casimir MJ (2009): On the Origin and Evolution of Affective Capacities in Lower Vertebrates. In: Böttger-Rössler B, Markowitsch HJ (eds.) Emotions as Bio-cultural Processes, p. 1-39. Springer, New York, DOI: 10.1007/978-0-387-09546-2_4
  102. Claridge-Chang A, Roorda RD, Vrontou E, Sjulson L, Li H, Hirsh J, Miesenböck G. (2009): Writing memories with light-addressable reinforcement circuitry. Cell 139(2):405-415
  103. Kemenes G (2009): Learning and Memory: How Sea Slug Behaviors Become Compulsive. Curr Biol. 19(13):R515-R517
  104. Nargeot R, Le Bon-Jego M, Simmers J (2009): Cellular and network mechanisms of operant learning-induced compulsive behavior in Aplysia. Curr Biol. 19(12):975-984
  105. Dayan P, Huys QJ. (2009): Serotonin in Affective Control. Annu Rev Neurosci. 32: 95-126
  106. Martínez-Rubio C, Serrano GE, Miller MW (2009): Localization of biogenic amines in the foregut of Aplysia californica: catecholaminergic and serotonergic innervation. J Comp Neurol. 514(4):329-342
  107. Khan AM, Spencer GE (2009): Novel neural correlates of operant conditioning in normal and differentially reared Lymnaea. J Exp Biol. 212(Pt 7):922-933
  108. Kisch J, Haupt SS (2009): Side-specific operant conditioning of antennal movements in the honey bee. Behav Brain Res. 196(1):131-133
  109. Kappeler PM (2008): Verhaltensbiologie 2nd edition. Springer-Lehrbuch ISSN 0937-7433
  110. Soltoggio A (2008): Neuromodulation Increases Decision Speed in Dynamic Environments. In: Schlesinger, M., Berthouze, L., and Balkenius, C. (2008): Proceedings of the Eighth International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems. Lund University Cognitive Studies, 139.
  111. Lee YS, Bailey CH, Kandel ER, Kaang BK (2008): Transcriptional regulation of long-term memory in the marine snail Aplysia. Mol Brain. 1(1):3.
  112. Proekt A, Wong J, Zhurov Y, Kozlova N, Weiss KR, Brezina V. (2008): Predicting adaptive behavior in the environment from central nervous system dynamics. PLoS ONE. 3(11): e3678
  113. Mozzachiodi R, Lorenzetti FD, Baxter DA, Byrne JH. (2008): Changes in neuronal excitability serve as a mechanism of long-term memory for operant conditioning. Nat Neurosci. 11: 1146-1148
  114. Lorenzetti FD, Byrne JH (2008): Cellular mechnaisms of associative learning in Aplysia. In: Byrne, JH (ed.) Concise Learning and Memory: The Editor’s Selection. Academic Press, London San Diego
  115. Lorenzetti FD, Baxter DA, Byrne JH (2008): Molecular Mechanisms Underlying a Cellular Analog of Operant Reward Learning. Neuron 59: 815-828
  116. Soltoggio A, Bullinaria JA, Mattiussi C, Dürr P, Floreano D (2008): Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward-based Scenarios. Proc 11th Int. Conf. Art. Life (Alife XI), 2008. LIS-CONF-2008-012
  117. Levitan D, Lyons LC, Perelman A, Green CL, Motro B, Eskin A, Susswein AJ. (2008): Training with inedible food in Aplysia causes expression of C/EBP in the buccal but not cerebral ganglion. Learn Mem. 15(6):412-416.
  118. Benjamin PR, Kemenes G, Kemenes I. (2008): Non-synaptic neuronal mechanisms of learning and memory in gastropod molluscs. Front Biosci. 13: 4051-4057
  119. Barandiaran X, Moreno A (2008): On the nature of neural information: A critique of the received view 50 years later. Neurocomp. 71 (4-6): 681-692
  120. Hurwitz I, Ophir A, Korngreen A, Koester J, Susswein AJ. (2008): Currents contributing to decision making in neurons b31/b32 of Aplysia. J Neurophysiol. 99(2): 814-830
  121. Nikitin ES, Korshunova TA, Zakharov IS, Balaban PM. (2008): Olfactory experience modifies the effect of odour on feeding behaviour in a goal-related manner. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 194(1):19-26
  122. Barandiaran X, Moreno A (2008): Adaptivity: From Metabolism to Behavior. Adapt Behav. 16 (5): 325-344
  123. Glanzman DL (2007): Simple Minds: The Neurobiology of Invertebrate Learning and Memory. Chapter 14 in: North G (ed.) Invertebrate Neurobiology, p. 347-380. Cold Spring Harbor Press.
  124. Alcaro A, Huber R, Panksepp J. (2007): Behavioral functions of the mesolimbic dopaminergic system: an affective neuroethological perspective. Brain Res Rev. 56(2): 283-321.
  125. Philips GT, Tzvetkova EI, Carew TJ. (2007): Transient mitogen-activated protein kinase activation is confined to a narrow temporal window required for the induction of two-trial long-term memory in Aplysia. J Neurosci. 27(50):13701-13705.
  126. Martin GG, Oakes CT, Tousignant HR, Crabtree H, Yamakawa R (2007): Structure and function of haemocytes in two marine gastropods, Megathura crenulata and Aplysia californica. J. Mollusc. Stud. 73: 355-365
  127. Rumbaugh DM, King JE, Beran MJ, Washburn DA, Gould K (2007): A Salience Theory of Learning and Behavior: With Perspectives on Neurobiology and Cognition. Int. J. Primatol. 28(5): 973-996
  128. Nargeot R, Petrissans C, Simmers J. (2007): Behavioral and in vitro correlates of compulsive-like food seeking induced by operant conditioning in Aplysia. J Neurosci. 27(30): 8059-8070
  129. Serrano GE, Martinez-Rubio C, Miller MW. (2007): Endogenous motor neuron properties contribute to a program-specific phase of activity in the multifunctional feeding central pattern generator of Aplysia. J Neurophysiol. 98(1):29-42
  130. Silva MTA, Goncalves FL, Garcia-Mijares M (2007): Neural events in the reinforcement contingency. Behav. Anal. 30(1): 17-30
  131. Daucé E (2007): Learning and control with large dynamic neural networks. Eur. Phys. J. Special Topics 142, 123–161
  132. Shaywitz SE, Shaywitz BA (2007): What neuroscience really tells us about reading instructions – A response to Judy Willis. Educational Leadership 64 (5): 74-76
  133. Willis J (2007): The gully in the “brain glitch” theory. Educational Leadership 64 (5): 68-73
  134. Cataldo E, Brunelli M, Av-Ron E, Cai Y, Baxter DA (2007): Geometry, activity-dependent mechanisms, membrane kinetics and channel density distribution interplay in single neuron plasticity: a computational study. In: Mondaini RP, Dilão R (eds.) Biomat 2007: International Symposium on Mathematical and Computational Biology. 154-178
  135. Kappeler PM (2006): Verhaltensbiologie, Springer-Lehrbuch, ISBN: 978-3-540-24056-3
  136. Rossini L, Rossini P (2006): Pharmacotherapeutic receptor specificities and selectivity classes, and plecebo effects: a perspective. Pharmacologyonline 2: 206-235
  137. Cataldo E, Byrne JH, Baxter DA (2006): Computational model of a central pattern generator. Computational Methods in Systems Biology, Proceedings Lecture Notes in Computer Science 4210: 242-256
  138. Baxter DA, Byrne JH (2006): Feeding behavior of Aplysia: A model system for comparing cellular mechanisms of classical and operant conditioning. Learn. Mem. 13: 669-680
  139. Giurfa, M (2006): Associative Learning: The Instructive Function of Biogenic Amines. Curr. Biol. 16(20): R892-R895
  140. Paolucci, M; Conte, R; Di Tosto, G (2006): A model of social organization and the evolution of food sharing in vampire bats. Adapt. Behav. 14 (3): 223-238
  141. Katzoff A, Ben-Gedalya T, Hurwitz I, Miller N, Susswein YZ, Susswein AJ. (2006): Nitric oxide signals that aplysia have attempted to eat, a necessary component of memory formation after learning that food is inedible. J Neurophysiol. 96(3):1247-1257
  142. Diaz-Rios M, Miller MW. (2006): Target-specific regulation of synaptic efficacy in the feeding central pattern generator of Aplysia: potential substrates for behavioral plasticity? Biol Bull. 210(3):215-29.
  143. Kemenes I, Straub VA, Nikitin ES, Staras K, O’shea M, Kemenes G, Benjamin PR. (2006): Role of delayed nonsynaptic neuronal plasticity in long-term associative memory. Curr Biol. 16(13):1269-1279
  144. Cheng J, Feenstra MG. (2006): Individual differences in dopamine efflux in nucleus accumbens shell and core during instrumental learning. Learn. Mem. 13(2):168-177
  145. Fioravante D, Smolen PD, Byrne JH. (2006): The 5-HT- and FMRFa-activated signaling pathways interact at the level of the Erk MAPK cascade: potential inhibitory constraints on memory formation. Neurosci Lett. 396(3):235-240
  146. Lowe MR, Spencer GE. (2006): Perturbation of the activity of a single identified neuron affects long-term memory formation in a molluscan semi-intact preparation. J Exp Biol. 209(Pt 4):711-721
  147. Shirinyan D, Teshiba T, Taylor K, O’neill P, Lee SC, Krasne FB. (2006): Rostral Ganglia are required for induction but not expression of crayfish escape reflex habituation: role of higher centers in reprogramming low-level circuits. J Neurophysiol. 95(4):2721-2724
  148. Hawkins RD, Clark, GA, Kandel, ER (2006): Operant Conditioning of Gill Withdrawal in Aplysia. J. Neurosci. 26(9):2443-2448
  149. Teague CL (2006): Perceptions of the Silent Majority: Projects as Assessments in a Brain Compatible Curriculum. ED thesis, University Of Cincinnati, USA
  150. Barbas D, Zappulla JP, Angers S, Bouvier M, Mohamed HA, Byrne JH, Castellucci VF, Desgroseillers L. (2006): An aplysia dopamine-like receptor: molecular and functional characterization. J Neurochem. 96(2):414-427
  151. Lorenzetti FD, Mozzachiodi R, Baxter DA, Byrne JH. (2006): Classical and operant conditioning differentially modify the intrinsic properties of an identified neuron. Nat Neurosci. 9(1):17-19.
  152. Silva MTA, Guerra LGGC (2005): Behavioral Models in Neuroscience: Braz J Behav Anal. 1(2): 167-185
  153. Douglas SJ, Dawson-Scully K, Sokolowski MB. (2005): The neurogenetics and evolution of food-related behaviour. Trends Neurosci. 28(12):644-652.
  154. Kristan WB Jr, Calabrese RL, Friesen WO. (2005): Neuronal control of leech behavior. Prog Neurobiol. 76(5): 279-327
  155. Kazdin AE (2005): Treatment for oppositional, aggressive and antisocial behavior n children and adolescents . Oxford University Press, UK
  156. Tobler PN, O’Doherty JP, Dolan RJ, Schultz W. (2005): Human neural learning depends on reward prediction errors in the blocking paradigm. J Neurophysiol. 95(1):301-310
  157. McComb C, Rosenegger D, Varshney N, Kwok HY, Lukowiak K. (2005): Operant conditioning of an in vitro CNS – pneumostome preparation of Lymnaea. Neurobiol Learn Mem. 84(1): 9-24.
  158. Reyes FD, Mozzachiodi R, Baxter DA, Byrne JH (2005): Reinforcement in an in vitro analog of appetitive classical conditioning of feeding behavior in Aplysia: Blockade by a dopamine antagonist. Learn. Mem. 12: 216-220
  159. Frick A, Johnston D (2005): Plasticity of dendritic excitability. J Neurobiol. 64 (1): 100-115
  160. Diaz-Rios M, Miller MW.(2005): Rapid dopaminergic signaling by interneurons that contain markers for catecholamines and GABA in the feeding circuitry of Aplysia. J Neurophysiol. 93(4):2142-2156.
  161. Smith WB, Starck SR, Roberts RW, Schuman EM, (2005): Dopaminergic Stimulation of Local Protein Synthesis Enhances Surface Expression of GluR1 and Synaptic Transmission in Hippocampal Neurons. Neuron. 45(5):765-79
  162. Reich RR, Noll JA, Goldman MS. (2005): Cue patterns and alcohol expectancies: how slight differences in stimuli can measurably change cognition. Exp Clin Psychopharmacol. 13(1): 65-71.
  163. Cooper SJ (2005): Donald O. Hebb’s synapse and learning rule: a history and commentary. Neurosci Biobehav Rev. 28(8): 851-874.
  164. Dacher M (2005): Role des recepteurs nicotiniques dans differentes formes de memoire chez l’abeille Apis mellifera. Doctoral thesis, Université de Toulouse, Paul Sabatier, France
  165. Haupt, SH (2005): Das gustatorische System und antennales Lernen der Honigbiene (Apis mellifera L.). Doktoral thesis, TU Berlin, Germany.
  166. Shtonda BB (2004): Electrophysiological and behavioral mechanisms od Caenorhabditis elegans feeding. PhD dissertation, The University of Texas Southwestern Medical Center at Dallas.
  167. Schroeder T (2004): Three faces of desire. Oxford University Press, 213pp
  168. Friedel RO (2004): Dopamine dysfunction in borderline personality disorder: a hypothesis. Neuropsychopharm. 29(6): 1029-39.
  169. Grünewald B (2004): ionic bases of olfactory memory. Membrane currents and modulations of neurons within the honeybee olfactory pathway. Habilitation thesis, Freie Universität Berlin, Germany
  170. Kelley, AE (2004): Memory and addiction: Shared neural circuitry and molecular mechanisms. NEURON 44 (1): 161-179
  171. Zull JE (2004): The art of changing the brain. EDUCATIONAL LEADERSHIP 62 (1): 68-72
  172. Panksepp JB, Huber R (2004): Ethological analyses of crayfish behavior: a new invertebrate system for measuring the rewarding properties of psychostimulants. BEHAV. BRAIN RES. 153 (1): 171-180
  173. Leonard JL, Edstrom JP (2004):Parallel processing in an identified neural circuit: the Aplysia californica gill-withdrawal response model system. BIOL REV 79 (1): 1-59
  174. Cropper EC, Evans CG, Hurwitz I, Jing J, Proekt A, Romero A, Rosen SC (2004): Feeding neural networks in the mollusc Aplysia. NEUROSIGNALS 13 (1-2): 70-86
  175. Lorenzetti FD, Byrne JH (2004): Classical Conditioning and Operant Conditioning. In: Byrne JH (ed.) Learning and Memory, Macmillan Psychology Reference Series, Macmillan, New York
  176. Scholz RW, Binder CR (2003): The Paradigm of Human-Environment Systems (Working Paper, 37). Zürich: ETH Zürich, Umweltnatur- und Umweltsozialwissenschaften.
  177. Wickens JR, Reynolds JNJ, Hyland BI (2003): Neural mechanisms of reward-related motor learning. CURR OPIN NEUROBIOL 13 (6): 685-690
  178. Roberts AC, Glanzman DL (2003): Learning in Aplysia: looking at synaptic plasticity from both sides. TRENDS NEUROSCI 26 (12): 662-670
  179. Daoudal G, Debanne D (2003): Long-term plasticity of intrinsic excitability: Learning rules and mechanisms. LEARN MEM 10 (6): 456-465
  180. Mozzachiodi R, Lechner HA, Baxter DA, Byrne, JH (2003): In vitro analog of classical conditioning of feeding behavior in Aplysia. LEARN MEM 10 (6): 478-494
  181. Barbas D, DesGroseillers L, Castellucci VF, Carew TJ, Marinesco S (2003): Multiple serotonergic mechanisms contributing to sensitization in Aplysia: Evidence of diverse serotonin receptor subtypes. LEARN MEM 10 (5): 373-386
  182. Dembrow NC, Jing J, Proekt A, Romero A, Vilim FS, Cropper EC, Weiss KR (2003): A newly identified buccal interneuron initiates and modulates feeding motor programs in Aplysia. J NEUROPHYSIOL 90 (4): 2190-2204
  183. Johnson LR, Byrne JH (2003): Essential medical physiology. Academic Press, 1008pp
  184. Shaik S (2003): Chemistry – A central pillar of human culture. ANGEW CHEM INT EDIT 42 (28): 3208-3215
  185. Nargeot R (2003): Voltage-dependent switching of sensorimotor integration by a lobster central pattern generator. J NEUROSCI 23 (12): 4803-4808
  186. Jones NG, Kemenes I, Kemenes G, et al. (2003): A persistent cellular change in a single modulatory neuron contributes to associative long-term memory. CURR BIOL 13 (12): 1064-1069 JUN 17 2003
  187. Shaik S (2003): Die Chemie – eine zentrale Säule der menschlichen Kultur. Angew. Chem. 115, 3326–3333
  188. Schultz W (2002): “The authors tested the reinforcing effects of dopamine in an in vitro cellular model of…” Evaluation of: [Brembs B et al. Operant reward learning in Aplysia: neuronal correlates and mechanisms. Science. 2002 May 31; 296(5573):1706-9; doi: 10.1126/science.1069434]. Faculty of 1000, 11 Jul 2002. F1000.com/1007610
  189. Menzel R (2002): “This paper analyses for the first time operant reward learning in the mollusc Aplysia at…” Evaluation of: [Brembs B et al. Operant reward learning in Aplysia: neuronal correlates and mechanisms. Science. 2002 May 31; 296(5573):1706-9; doi: 10.1126/science.1069434]. Faculty of 1000, 11 Sep 2002. F1000.com/1007610
  190. Katzoff A, Ben-Gedalya T, and Susswein AJ 2002: Nitric Oxide is necessary for multiple memory processes after learning that a food is inedible in Aplysia. J NEUROSCI 22(21): 9581-9594
  191. Schultz W 2002: Getting formal with dopamine and reward. NEURON 36: 241-263
  192. Carew TJ 2002: Neurobiology – Understanding the consequences. NATURE 417: 803-806
  193. Rankin CH 2002: Neuroscience: A bite to remember. SCIENCE 296 (5573): 1624-1625
Baier A.; Wittek B. and Brembs B. (2002): Drosophila as a new model organism for the neurobiology of aggression? J. Exp. Biol. 205 (9): 1233–1240.
Citations:
  1. Kang WN, Zeng Y, Zhu DH (2018): Effects of physical and social experiences and octopamine receptor agonist on fighting behavior of male crickets Velarifictorus aspersus (Orthoptera: Gryllidaeik). Journal of Asia-Pacific Entomology. 21(2): 445–450. DOI: 10.1016/j.aspen.2018.02.008
  2. Golden CJ, Zachar R, Lowry B, Tran V (2017): Role of Neurobiological Factors. Handbook of Behavioral Criminology (pp. 25–42). Springer International Publishing. DOI: 10.1007/978-3-319-61625-4_3
  3. Davis SM, Thomas AL, Liu L, Campbell IM, Dierick HA (2017): Isolation of Aggressive Behavior Mutants in Drosophila Using a Screen for Wing Damage. Genetics. 208(1): 273–282. DOI: 10.1534/genetics.117.300292
  4. Himoji H, Aonuma H, Miura T, Tsuji K, Sasaki K, Okada Y (2017): Queen contact and among-worker interactions dually suppress worker brain dopamine as a potential regulator of reproduction in an ant. Behavioral Ecology and Sociobiology. 71(2). DOI: 10.1007/s00265-016-2263-3
  5. Watanabe K, Chiu H, Pfeiffer BD, Wong AM, Hoopfer ED, Rubin GM, Anderson DJ (2017): A Circuit Node that Integrates Convergent Input from Neuromodulatory and Social Behavior-Promoting Neurons to Control Aggression in Drosophila. Neuron. 95(5):1112–1128.DOI: 10.1016/j.neuron.2017.08.017
  6. Bosco JM, Riechert SE, O’Meara BC (2017): The ontogeny of personality traits in the desert funnel-web spider, Agelenopsis lisa (Araneae: Agelenidae). Ethology. 123(9):648–658. DOI: 10.1111/eth.12639
  7. Pons M, Soulard C, Soustelle L, Parmentier ML, Grau Y, Layalle S (2017): A New Behavioral Test and Associated Genetic Tools Highlight the Function of Ventral Abdominal Muscles in Adult Drosophila. Front Cell Neurosci. 11. DOI: 10.3389/fncel.2017.00371
  8. Chapman T, Wolfner MF (2017): Reproductive behaviour: Make love, then war. Nat Ecol Evol. 1(6):174. DOI: 10.1038/s41559-017-0174
  9. Stevenson PA, Rillich J (2017): Neuromodulators and the Control of Aggression in Crickets. The Cricket as a Model Organism (pp. 169–195). Springer Japan. DOI: 10.1007/978-4-431-56478-2_12
  10. Nouvian MVM (2017): Neural and molecular mechanisms underlying the olfactory modulation of aggression in honeybees. PhD thesis, University of Queensland. DOI: 10.14264/uql.2017.464
  11. Asahina K (2017): Neuromodulation and Strategic Action Choice in Drosophila Aggression. Ann Rev Neurosci. 40(1): 51–75. DOI: 10.1146/annurev-neuro-072116-031240
  12. Anderson DJ (2016): Circuit modules linking internal states and social behaviour in flies and mice. Nature Reviews Neuroscience. 17(11):692–704. DOI: 10.1038/nrn.2016.125
  13. Kim YK (2016): A Drosophila Model for Aggression. In: Animal Models of Behavior Genetics (pp. 35–61). Springer New York. DOI: 10.1007/978-1-4939-3777-6_2
  14. chneider J, Atallah J, Levine JD (2016): Social structure and indirect genetic effects: genetics of social behaviour. Biological Reviews. 92(2): 1027–1038. DOI: 10.1111/brv.12267
  15. Trannoy S, Kravitz EA (2016): Strategy changes in subsequent fights as consequences of winning and losing in fruit fly fights. Fly. 11(2): 129–138. DOI: 10.1080/19336934.2016.1259041
  16. uhl J, Rogers S (2016): Mechanisms underpinning aggregation and collective movement by insect groups. Curr Opin Insect Sci. 15, 125–130. doi: 10.1016/j.cois.2016.04.011
  17. Hoopfer ED (2016): Neural control of aggression in Drosophila. Curr Opin Neurobiol. 38:109-118. doi: 10.1016/j.conb.2016.04.007
  18. Hoopfer ED, Jung Y, Inagaki HK, Rubin GM, Anderson DJ (2016): P1 interneurons promote a persistent internal state that enhances inter-male aggression in Drosophila. Elife. 4. pii: e11346. doi: 10.7554/eLife.11346
  19. Hong KB, Park Y, Suh HJ (2016): Sleep-promoting effects of a GABA/5-HTP mixture: Behavioral changes and neuromodulation in an invertebrate model. Life Sci. 150: 42-49. doi: 10.1016/j.lfs.2016.02.086
  20. Schneider J, Atallah J, Levine JD (2016): Social structure and indirect genetic effects: genetics of social behaviour. Biol Rev Camb Philos Soc. doi: 10.1111/brv.12267
  21. Kravitz EA, Fernandez Mde L (2015): Aggression in Drosophila. Behav Neurosci. 129(5):549-63. doi: 10.1037/bne0000089
  22. Peterson EK, Carrico P (2015): Laboratory exercise in behavioral genetics using team-based learning strategies, Bioscene 41(2): 32-39.
  23. Zwarts L, Vanden Broeck L, Cappuyns E, Ayroles JF, Magwire MM, Vulsteke V, Clements J, Mackay TF, Callaerts P (2015): The genetic basis of natural variation in mushroom body size in Drosophila melanogaster. Nat Commun. 6:10115, DOI: 10.1038/ncomms10115
  24. Maximino C, Silva RX, da Silva Sde N, Rodrigues Ldo S, Barbosa H, de Carvalho TS, Leão LK, Lima MG, Oliveira KR, Herculano AM (2015): Non-mammalian models in behavioral neuroscience: consequences for biological psychiatry. Front Behav Neurosci. 9: DOI: 10.3389/fnbeh.2015.00233
  25. Schneider J (2015): Group Dynamics in Drosophila melanogaster, PhD dissertation, University of Toronto
  26. Newland PL, Al Ghamdi MS, Sharkh S, Aonuma H, Jackson CW (2015): Exposure to static electric fields leads to changes in biogenic amine levels in the brains of Drosophila. Proc Biol Sci. 282: 20151198, DOI: 10.1098/rspb.2015.1198
  27. Bubak AN, Rieger NS, Watt MJ, Renner KJ, Swallow JG (2015): David vs. Goliath: Serotonin modulates opponent perception between smaller and larger rivals. Behav Brain Res 292: 521–527, DOI: 10.1016/j.bbr.2015.07.028
  28. Shorter J, Couch C, Huang W, Carbone MA, Peiffer J, Anholt RR, Mackay TF (2015): Genetic architecture of natural variation in Drosophila melanogaster aggressive behavior . Proc Natl Acad Sci U S A. 112: E3555–E3563, DOI: 10.1073/pnas.1510104112
  29. Rohrscheib CE, Bondy E, Josh P, Riegler M, Eyles D, van Swinderen B, Weible MW 2nd, Brownlie JC (2015): Wolbachia Influences the Production of Octopamine and Affects Drosophila Male Aggression. Appl Environ Microbiol. 81(14): 4573–4580, DOI: 10.1128/AEM.00573-15
  30. Haynes PR, Christmann BL, Griffith LC (2015): A single pair of neurons links sleep to memory consolidation in Drosophila melanogaster. eLife 4, DOI: 10.7554/eLife.03868
  31. Benelli G (2015): Should I fight or should I flight? How studying insect aggression can help integrated pest management. Pest Manag Sci 71: 885–892, DOI: 10.1002/ps.3974
  32. Rillich J, Stevenson PA (2015): Releasing stimuli and aggression in crickets: octopamine promotes escalation and maintenance but not initiation. Front. Behav. Neurosci., 9, DOI: 10.3389/fnbeh.2015.00095
  33. Ostrowski D, Kahsai L, Kramer EF, Knutson P, Zars T (2015) Place memory retention in Drosophila. Neurobiol Learn Mem 123: 217–224. DOI: 10.1016/j.nlm.2015.06.015
  34. Ostrowski D, Zars T (2014): Place memory, In: Josh Dubnau (ed.) Behavioral Genetics of the Fly (Drosophila melanogaster). pp. 125-134. Cambridge Handbooks in Behavioral Genetics. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511920585.007
  35. Ruiz-Rubio M, Calahorro F, Gámez-del-Estal MM (2014): Invertebrate Models of Synaptic Transmission in Autism Spectrum Disorders. Organism Models of Autism Spectrum Disorders IN: Neuromethods 100: pp 157-182 DOI: 10.1007/978-1-4939-2250-5_6
  36. Bubak AN, Grace JL, Watt MJ, Renner KJ, Swallow JG (2014): Neurochemistry as a bridge between morphology and behavior: Perspectives on aggression in insects, Curr Zool 60(6): 778–790
  37. Jezzini SH, Reyes-Colón D, Sosa MA (2014): Characterization of a Prawn OA/TA Receptor in Xenopus Oocytes Suggests Functional Selectivity between Octopamine and Tyramine. PLoS ONE, 9 DOI: 10.1371/journal.pone.0111314
  38. Yapici N, Zimmer M, Domingos AI (2014): Cellular and molecular basis of decision-making. EMBO Rep 15: 1023–1035. DOI: 10.15252/embr.201438993
  39. Goergen P (2014): The Molecular Mechanism of Aggression and Feeding Behaviour in Drsophila melanogaster. PhD dissertation, Uppsala Universitet, ISBN: 978-91-554-8985-4
  40. Luo J, Lushchak OV, Goergen P, Williams MJ, Nässel DR (2014): Drosophila Insulin-Producing Cells Are Differentially Modulated by Serotonin and Octopamine Receptors and Affect Social Behavior. PLoS ONE 9, e99732. DOI: 10.1371/journal.pone.0099732
  41. Penick CA, Brent CS, Dolezal K, Liebig J (2014): Neurohormonal changes associated with ritualized combat and the formation of a reproductive hierarchy in the ant Harpegnathos saltator. J Exp Biol 217: 1496–1503. DOI: 10.1242/jeb.098301
  42. Selcho M, Pauls D, Huser A, Stocker RF, Thum AS (2014): Characterization of the octopaminergic and tyraminergic neurons in the central brain of Drosophila larvae . J Comp Neurol 522: 3485–3500. DOI:10.1002/cne.23616
  43. Moore D, Paquette C, Shropshire JD, Seier E, Joplin KH (2014): Extensive reorganization of behavior accompanies ontogeny of aggression in male flesh flies. PLoS One. 9(4):e93196
  44. Asahina K, Watanabe K, Duistermars BJ, Hoopfer E, González CR, Eyjólfsdóttir EA, Perona P, Anderson DJ (2014) Tachykinin-Expressing Neurons Control Male-Specific Aggressive Arousal in Drosophila. Cell 156:221–235
  45. Strauss R (2014): Neurobiological Models of the Central Complex and the Mushroom Bodies. In: Arena P, Patane L (Eds.): Spatial Temporal Patterns for Action-Oriented Perception in Roving Robots II. Springer-Verlag, ISBN 978-3-319-02362-5
  46. Briffa M, Hardy ICW, Mowles SL (2013): Prospects for animal contests. In: Ian C. W. Hardy and Mark Briffa (eds.) Animal Contests. pp. 335-341. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9781139051248.018
  47. Williams MJ, Goergen P, Rajendran J, Klockars A, Kasagiannis A, Fredriksson R, Schiöth HB (2013): Regulation of Aggression by Obesity-Linked Genes TfAP-2 and Twz Through Octopamine Signaling in Drosophila. Genetics 196: 349–362. DOI: 10.1534/genetics.113.158402
  48. Blenau W, Thamm M, Baumann A (2013): Serotonin in insects: Distribution, biosynthesis, uptake, inactivation, receptors, functions, and implications for human health. In: F.S. Hall (ed.). Serotonin: Biosynthesis, Regulation and Health Implications, NOVA Science Publishers, 1-26. ISBN: 9781624176364
  49. Herberholz J (2013): Serotonergic modulation of aggression. In: F.S. Hall (ed.). Serotonin: Biosynthesis, Regulation and Health Implications, NOVA Science Publishers, 27-51. ISBN: 9781624176364
  50. Szczuka A, Korczynska J, Wnuk A, Symonowicz B, Szwacka AG, Mazurkiewicz P, Kostowski W, Godzinska EJ (2013): The effects of serotonin, dopamine, octopamine and tyramine on behavior of workers of the ant Formica polyctena during dyadic aggression tests. Acta Neurobiol Exp (Wars). 73(4):495-520
  51. Klowden MJ (2013): Behavioral Systems. In: Physiological Systems in Insects, 696p, Elsevier, ISBN-13: 978-0124158191
  52. Kamhi JF, Traniello JFA (2013): Biogenic Amines and Collective Organization in a Superorganism: Neuromodulation of Social Behavior in Ants. Brain Behav Evol 82:220–236
  53. Williams MJ, Goergen P, Rajendran J, Klockars A, Kasagiannis A, Fredriksson R, Schiöth HB (2014): Regulation of Aggression by Obesity-Linked Genes TfAP-2 and Twz Through Octopamine Signaling in Drosophila. Genetics 196: 349–362 DOI: 10.1534/genetics.113.158402
  54. Bubak AN, Swallow JG, Renner KJ (2013): Whole Brain Monoamine Detection and Manipulation in a Stalk-eyed Fly. J Neurosci Methods. 219(1):124-130
  55. Donnelly JL, Clark CM, Leifer AM, Pirri JK, Haburcak M, et al. (2013): Monoaminergic Orchestration of Motor Programs in a Complex C. elegans Behavior. PLoS Biol 11(4): e1001529. doi:10.1371/journal.pbio.1001529
  56. van Alphen B, van Swinderen B (2013): Drosophila strategies to study psychiatric disorders. Brain Res Bull. 92:1-11
  57. Stevenson PA, Schildberger K (2013): Mechanisms of experience dependent control of aggression in crickets. Curr Opin Neurobiol. 23(3): 318-323
  58. Huang Q, Sun P, Zhou X, Lei C (2012): Characterization of Head Transcriptome and Analysis of Gene Expression Involved in Caste Differentiation and Aggression in Odontotermes formosanus (Shiraki). PLoS One. 7(11):e50383
  59. Neckameyer WS, Argue KJ (2012): Comparative Approaches to the Study of Physiology: Drosophila as a Physiologic Tool. Am J Physiol Regul Integr Comp Physiol. 304(3):R177-188
  60. Zwarts L, Clements J, Callaerts P (2012): Deciphering the Adult Brain: From Neuroanatomy to Behavior. In: Hassan BA (ed.):The Making and Un-Making of Neuronal Circuits in Drosophila. Neuromethods 69, pp 3-48 ISBN 978-1-61779-829-0
  61. Stevenson PA, Rillich J (2012): The decision to fight or flee – insights into underlying mechanism in crickets. Front Neurosci. 6:118
  62. Zwarts L, Clements J, Callaerts P (2012): Deciphering the Adult Brain: From Neuroanatomy to Behavior. Neuromethods, 69(1): 3-48, DOI: 10.1007/978-1-61779-830-6_1
  63. Selcho M, Pauls D, Jundi BE, Stocker RF, Thum AS (2012): The role of octopamine and tyramine in Drosophila larval locomotion. J Comp Neurol. 2012 May 24. doi: 10.1002/cne.23152
  64. Zwarts L, Versteven M, Callaerts P (2012): Genetics and neurobiology of aggression in Drosophila. Fly (Austin). 6(1):35-48
  65. Cossío-Bayúgar R, Miranda-Miranda E, Narváez Padilla V, Olvera-Valencia F, Reynaud E (2012): Perturbation of tyraminergic/octopaminergic function inhibits oviposition in the cattle tick Rhipicephalus (Boophilus) microplus. J Insect Physiol. 58(5):628-633
  66. Zwarts L, Magwire MM, Carbone MA, Versteven M, Herteleer L, Anholt RR, Callaerts P, Mackay TF (2011): Complex genetic architecture of Drosophila aggressive behavior. Proc Natl Acad Sci U S A. 108(41):17070-17075
  67. Brooks ES, Greer CL, Romero-Calderón R, Serway CN, Grygoruk A, Haimovitz JM, Nguyen BT, Najibi R, Tabone CJ, Steven de Belle J, Krantz DE (2011): A Putative Vesicular Transporter Expressed in Drosophila Mushroom Bodies that Mediates Sexual Behavior May Define a Neurotransmitter System. Neuron. 72(2):316-329.
  68. Sharon G, Segal D, Zilber-Rosenberg I, Rosenberg E. (2011): Symbiotic bacteria are responsible for diet-induced mating preference in Drosophila melanogaster, providing support for the hologenome concept of evolution. Gut Microbes. 2(3):190-192
  69. Pflüger HJ, Duch C (2011): Dynamic Neural Control of Insect Muscle Metabolism Related to Motor Behavior. Physiology 26:293-303
  70. Jonsson T, Kravitz EA, Heinrich R (2011): Sound production during agonistic behavior of male Drosophila melanogaster. Fly (Austin) 5(1):29-38
  71. Strauss R, Berg C (2010): The Central Control of Oriented Locomotion in Insects – Towards a Neurobiological Model. The 2010 International Joint Conference on Neural Networks (IJCNN), doi: 10.1109/IJCNN.2010.5596461
  72. Bolduc FV, Valente D, Nguyen AT, Mitra PP, Tully T (2010): An assay for social interaction in Drosophila fragile X mutants. Fly (Austin) 4(3).
  73. Verlinden H, Vleugels R, Marchal E, Badisco L, Pflüger HJ, Blenau W, Broeck JV (2010): The role of octopamine in locusts and other arthropods. J Insect Physiol. 56(8):854-867
  74. Börner J, Duch C (2010): An average shape standard atlas for the adult Drosophila ventral nerve cord. J comp. Neurol. 518(13): 2437-2455
  75. Wang L, Anderson DJ (2010): Identification of an aggression-promoting pheromone and its receptor neurons in Drosophila. Nature 463(7278):227-231
  76. Ueda A, Wu CF (2009): Effects of social isolation on neuromuscular excitability and aggressive behaviors in Drosophila: altered responses by Hk and gsts1, two mutations implicated in redox regulation. J. Neurogenet. 23(4):378-294
  77. Edwards AC, Ayroles JF, Stone EA, Carbone MA, Lyman RF, Mackay TF (2009): A transcriptional network associated with natural variation in Drosophila aggressive behavior. Genome Biol. 10(7): R76
  78. Avanesian A, Semnani S, Jafari M (2009): Can Drosophila melanogaster represent a model system for the detection of reproductive adverse drug reactions? Drug Discovery Today 14(15-16): 761-766
  79. Cholewa J, Pflüger HJ (2009): Descending unpaired median neurons with bilaterally symmetrical axons in the suboesophageal ganglion of Manduca sexta larvae. Zoology 112(4): 251-262
  80. Pain SP (2009): Signs of anger: Representation of agonistic behaviour in invertebrate cognition. Biosemiotics 2(2): 181-191
  81. Edwards A, Mackay TF (2009): Quantitative Trait Loci for Aggressive Behavior in Drosophila melanogaster. Genetics. 182(3): 889-897
  82. Edwards AC, Zwarts L, Yamamoto A, Callaerts P, Mackay TF (2009): Mutations in many genes affect aggressive behavior in Drosophila melanogaster. BMC Biol. 7(1):29
  83. Kim YK (2009): Sexual Selection and Aggressive Behavior in Drosophila. In: Kim YK (ed.) Handbook of Behavior Genetics. Springer ISBN 978-0-387-76726-0 (Print) 978-0-387-76727-7 (Online), 317-330
  84. Börner J (2009): Standardized Drosophila ventral nerve cord morphology: Atlas generation and atlas applications. PhD thesis, Freie Universität Berlin, Germany
  85. Kotsyuba, EP (2009): Effect of temperature stress on activities of nitric oxide synthase and tyrosine hydroxylase in the central nervous system of bivalve molluscs. Zh Evol Biokhim Fiziol. 45(1):122-129
  86. Serway CN, Kaufman RR, Strauss R, de Belle JS (2009): Mushroom bodies enhance initial motor activity in Drosophila. J Neurogenet. 23(1):173-184
  87. Iliadi KG (2009): The genetic basis of emotional behavior: has the time come for a Drosophila model? J Neurogenet. 23(1):136-146
  88. Vierk R, Pflueger HJ, Duch C (2009): Differential effects of octopamine and tyramine on the central pattern generator for Manduca flight. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 195(3): 265-277
  89. Johnson O, Becnel J, Nichols CD (2009): Serotonin 5-HT(2) and 5-HT(1A)-like receptors differentially modulate aggressive behaviors in Drosophila melanogaster. Neuroscience 158(4): 1292-1300
  90. Nishimura K, Kitamura Y, Inoue T, Umesono Y, Yoshimoto K, Taniguchi T, Agata K. (2008): Characterization of tyramine beta-hydroxylase in planarian Dugesia japonica: Cloning and expression. Neurochem Int. 53(6-8):184-192
  91. Paquette C, Joplin KH, Seier E, Peyton JT, Moore D (2008): Sex-specific differences in spatial behaviour in the flesh fly Sarcophaga crassipalpis. Physiol. Entomol. 33 (4): 382-388
  92. Potter CJ, Luo L (2008): Octopamine fuels fighting flies. Nat Neurosci. 11: 989-990
  93. Zhou C, Rao Y, Rao Y. (2008): A subset of octopaminergic neurons are important for Drosophila aggression. Nat Neurosci. 11: 1059-1067
  94. Paquette C (2008): Gender-Specific Differences in Spatial Behavior of the Flesh Fly, Sarcophaga crassipalpis. Master’s thesis, East Tennessee State University. USA
  95. Cabral LG, Foley BR, Nuzhdin SV (2008): Does Sex Trade with Violence among Genotypes in Drosophila melanogaster? PLoS ONE 3(4): e1986
  96. Wang L, Dankert H, Perona P, Anderson DJ (2008): A common genetic target for environmental and heritable influences on aggressiveness in Drosophila. Proc Natl Acad Sci USA. 105(15): 5657-5663
  97. Dierick HA. (2008): Fly fighting: octopamine modulates aggression. Curr Biol. 18(4):R161-163
  98. Hoyer SC, Eckart A, Herrel A, Zars T, Fischer SA, Hardie SL, Heisenberg M. (2008): Octopamine in male aggression of Drosophila. Curr Biol. 18(3):159-167.
  99. Dierick HA. (2007): A method for quantifying aggression in male Drosophila melanogaster. Nat Protoc. 2(11):2712-2718.
  100. Chan YB, Kravitz EA (2007): Specific subgroups of FruM neurons control sexually dimorphic patterns of aggression in Drosophila melanogaster. Proc Natl Acad Sci USA. 104(49): 19577-19582
  101. Simon AF, Krantz DE. (2007): Road rage and fruit flies. Nat Genet. 39(5): 581-582
  102. Kaun KR, Hendel T, Gerber B, Sokolowski MB. (2007): Natural variation in Drosophila larval reward learning and memory due to a cGMP-dependent protein kinase. Learn Mem. 14(5): 342-349
  103. Dierick HA, Greenspan RJ. (2007): Serotonin and neuropeptide F have opposite modulatory effects on fly aggression. Nat Genet. 39(5):678-682.
  104. Certel SJ, Savella MG, Schlegel DC, Kravitz EA. (2007): Modulation of Drosophila male behavioral choice. Proc Natl Acad Sci USA. 104(11): 4706-4711.
  105. Robin C, Daborn PJ, Hoffmann AA. (2006): Fighting fly genes. Trends Genet. 23(2):51-54
  106. Scott MP. (2006): The role of juvenile hormone in competition and cooperation by burying beetles. J Insect Physiol. 52(10):1005-1011
  107. Edwards AC, Rollmann SM, Morgan TJ, Mackay TFC (2006): Quantitative Genomics of Aggressive Behavior in Drosophila melanogaster. PLoS Genet 2(9): e154
  108. Beaver KM (2006): The Intersection of Genes, the Environment, and Crime and Delinquency: A Longitudinal Study of Offending. Doctoral thesis, University of Cincinnati, Ohio, USA.
  109. Dierick HA, Greenspan RJ. (2006): Molecular analysis of flies selected for aggressive behavior. Nat Genet. 38(9):1023-1031
  110. Yuan Q, Joiner WJ, Sehgal A. (2006): A sleep-promoting role for the Drosophila serotonin receptor 1A. Curr Biol. 16(11):1051-1062
  111. Gonzales E, Hamrick JL, Smouse PE, Dyer RJ. (2006): Pollen-mediated gene dispersal within continuous and fragmented populations of a forest understorey species, Trillium cuneatum. Mol Ecol. 15(8):2047-2058.
  112. Fox LE, Soll DR, Wu CF. (2006): Coordination and modulation of locomotion pattern generators in Drosophila larvae: effects of altered biogenic amine levels by the tyramine Beta hydroxlyase mutation. J Neurosci. 26(5):1486-1498.
  113. Sinakevitch I, Strausfeld NJ. (2006): Comparison of octopamine-like immunoreactivity in the brains of the fruit fly and blow fly. J Comp Neurol. 494(3):460-475
  114. Hoyer SC, Liebig J, Rossler W (2005): Biogenic amines in the ponerine ant Harpegnathos saltator: serotonin and dopamine immunoreactivity in the brain. Arth. Struct. Dev. 34(4): 429-440
  115. Carbone MA, Llopart A, Deangelis M, Coyne JA, Mackay TF. (2005): Quantitative Trait Loci Affecting the Difference in Pigmentation Between Drosophila yakuba and D. santomea.Genetics. 171(1): 211-325.
  116. Blenau W, Baumann A. (2005): Molecular characterization of the ebony gene from the American cockroach, Periplaneta americana. Arch Insect Biochem Physiol. 59(3):184-95.
  117. Svetec N, Ferveur JF. (2005): Social experience and pheromonal perception can change male-male interactions in Drosophila melanogaster. J Exp Biol. 208(Pt 5):891-8.
  118. Stevenson PA, Dyakonova V, Rillich J, Schildberger K. (2005): Octopamine and experience-dependent modulation of aggression in crickets. J Neurosci. 25(6):1431-1441.
  119. Pagé MP, Cooper RL (2004): Novelty stress and reproductive state alters responsiveness to sensory stimuli and 5-HT neuromodulation in crayfish. Comp Biochem Physiol A Mol Integr Physiol. 139(2):149-158
  120. Fox LE, Ueda A, Berke B, Peng IF, Wu CF (2004): Movement disorders in Drosophila mutants of potassium channels and biogenic amine pathways . In: Animal models of movement disorders (LeDoux MS, ed.) , pp. 487–504. San Diego: Academic/Elsevier.
  121. Zhang B, Lu H, Xi W, Zhou X, Xu S, Zhang K, Jiang J, Li Y, Guo A. (2004): Exposure to hypomagnetic field space for multiple generations causes amnesia in Drosophila melanogaster. Neurosci Lett. 371(2-3):190-195.
  122. Banerjee S, Lee J, Venkatesh K, Wu CF, Hasan G (2004): Loss of flight and associated neuronal rhythmicity in inositol 1,4,5-trisphosphate receptor mutants of Drosophila. J. NEUROSCI. 24 (36): 7869-7878
  123. Ye Y, Xi W, Peng Y, Wang Y, Guo A. (2004): Long-term but not short-term blockade of dopamine release in Drosophila impairs orientation during flight in a visual attention paradigm. Eur J Neurosci. 20 (4):1001-1007.
  124. Knaden M, Wehner R (2004): Path integration in desert ants controls aggressiveness. SCIENCE 305 (5680): 60-60
  125. Park DK, Han M, Kim YC, Han KA, Taghert PH (2004): Ap-let neurons – a peptidergic circuit potentially controlling ecdysial behavior in Drosophila. DEV BIOL 269 (1): 95-108
  126. Saraswati S, Fox LE, Soll DR, Wu CF (2004): Tyramine and octopamine have opposite effects on the locomotion of Drosophila larvae. J NEUROBIOL 58 (4): 425-441
  127. Dasari S, Cooper RL (2004): Modulation of sensory-CNS-motor circuits by serotonin, octopamine, and dopamine in semi-intact Drosophila larva. NEUROSCI RES 48 (2): 221-227
  128. Libersat F, Pflueger HJ (2004): Monoamines and the orchestration of behavior. BIOSCIENCE 54 (1): 17-25
  129. Kravitz EA, Huber R (2003): Aggression in invertebrates. CURR OPIN NEUROBIOL 13 (6): 736-743
  130. Monastirioti M (2003): Distinct octopamine cell population residing in the CNS abdominal ganglion controls ovulation in Drosophila melanogaster. DEV BIOL 264 (1): 38-49
  131. Manev H, Dimitrijevic N, Dzitoyeva S (2003): Techniques: Fruit flies as models for neuropharmacological research. TRENDS PHARMACOLSCI 24 (1): 41-43
  132. Chen S, Lee AY, Bowens NM, Huber R, Kravitz EA (2002): Fighting fruit flies: A model system for the study of aggression. PROC NATL ACAD SCI USA 99 (8): 5664-5668
Brembs B.; Wilkinson E.; Reyes F.; Baxter D.A. and Byrne J.H. (2001): Operant conditioning of feeding behavior in Aplysia using self-stimulation. Soc. Neurosci. Abstr. 644.19.
Citations:
  1. Susswein AJ, Hurwitz I, Thorne R, Byrne JH, Baxter DA (2002): Mechanisms underlying fictive feeding in Aplysia: Coupling between a large neuron with plateau potentials activity and a spiking neuron. J. Neurophys. 87 (5): 2307-2323.
Brembs B. (2001): Hamilton’s Theory. In: Brenner, S. and Miller, J. (eds) Encyclopedia of Genetics, Academic Press, London, New York; pp. 906-910.
Citations:
  1. Barr A, Dekker M, Fafchamps M (2015): The Formation of Community-Based Organizations: An Analysis of a Quasi-Experiment in Zimbabwe. World Development, 66: 131–153, DOI: 10.1016/j.worlddev.2014.08.003
  2. Tokumitsu M, Ishida Y (2012): A systemic payoff in a self-repairing network. Artif Life Robotics 16:563–566
  3. Tokumitsu M, Ishida Y (2011): An Adaptive Control Technique for a Connection Weight of Agents in a Self-repairing Network. Self-Organizing Systems. In: Lecture Notes in Computer Science 6557, 44-55
  4. Bar A, Dekker M, Fafchamps M (2010): The formation of community based organizations in sub-Saharan Africa: An analysis of a quasi-experiment. The Centre for the Study of African Economies Working Paper Series: WPS/2010/21
  5. Fafchamps M (2009): Household Separation and Child Well-Being. The Centre for the Study of African Economies Working Paper Series: WPS/2009-12. The Berkeley Electronic Press (bepress).
  6. Bar A, Dekker M, Fafchamps M (2008): Risk Sharing Relations and Enforcement Mechanisms. The Centre for the Study of African Economies Working Paper Series: Paper 294. The Berkeley Electronic Press (bepress).
  7. Fokker J, de Ridder H, Westendorp P, Pouwelse J (2007): Psychological Backgrounds for Inducing Cooperation in Peer-to-Peer Television. Lect. Notes Comp. Sci. 4471, 136-145
  8. Fafchamps M, Wahba J (2006): Child labor, urban proximity, and household composition. J. dev. Econ. 79(2): 374-397.
Heisenberg M.; Wolf R. and Brembs B. (2001): Flexibility in a single behavioral variable of Drosophila. Learn. Mem. 8:1-10.
Citations:
  1. Le Neindre P, Bernard E, Boissy A, Boivin X, Calandreau L, Delon N, Deputte B, et. al. (2017): Animal Consciousness. EFSA Supporting Publications. 14(4): 1196E
  2. Waller BN (2017): The Injustice of Punishment. Routledge Research in Applied Ethics. 8. ISBN: 978-113850639
  3. Dylla KV, Raiser G, Galizia CG, Szyszka P (2017): Trace Conditioning in Drosophila Induces Associative Plasticity in Mushroom Body Kenyon Cells and Dopaminergic Neurons. Front Neural Circ. 11. DOI: 10.3389/fncir.2017.00042
  4. Guo A, Gong Z, Li H, Li Y, Liu L, Liu Q, Lu H, Pan Y, Ren Q,Wu Z, Thang K, Yan Z (2017): Vision, Memory, and Cognition in Drosophila. In: Byrne JH (Eds): Learning and Memory: A Comprehensive Reference. 483–503. Elsevier. DOI: 10.1016/B978-0-12-809324-5.21029-8
  5. Bronfman ZZ, Ginsburg S, Jablonka E (2016): The Transition to Minimal Consciousness through the Evolution of Associative Learning. Front Psychol. 7. DOI: 10.3389/fpsyg.2016.01954
  6. Taylor G (2015): Unravelling the sensory control of behaviour in honeybees using virtual reality paradigms. PhD thesis, University of Queensland. DOI: 14264/uql.2015.332
  7. Leung JC, Taylor-Kamall RW, Hilliker AJ, Rezai P (2015): Agar-polydimethylsiloxane devices for quantitative investigation of oviposition behaviour of adult Drosophila melanogaster. Biomicrofluidics, 9(3):034112, DOI: 10.1063/1.4922737
  8. Giurfa M (2015): Learning and cognition in insects. Wiley Interdisciplinary Reviews: Cognitive Science, 6(4): 383–395, DOI: 10.1002/wcs.1348
  9. Ghimire S, Kim MS (2015): Defensive Behavior against Noxious Heat Stimuli Is Declined with Aging Due to Decreased Pain-Associated Gene Expression in Drosophila. Biomol Ther (Seoul) 23: 290–295, DOI: 10.4062/biomolther.2014.147
  10. Avargués-Weber A, Lihoreau M, Isabel G, Giurfa M (2015): Information transfer beyond the waggle dance: observational learning in bees and flies. Front Ecol Evol, 3, DOI: 10.3389/fevo.2015.00024
  11. Tabone CJ, De Belle JS (2014): Olfactory learning and memory assays, In: Josh Dubnau (ed.) Behavioral Genetics of the Fly (Drosophila melanogaster). pp. 231-249. Cambridge Handbooks in Behavioral Genetics. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511920585.007.
  12. Anholt RRH, Mackay TFC, Stone EA (2014): Systems Genetics of Behavior in Drosophila, In: Josh Dubnau (ed.) Behavioral Genetics of the Fly (Drosophila melanogaster). pp. 217-230. Cambridge Handbooks in Behavioral Genetics. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511920585.007.
  13. Guo C, Du Y, Yuan D, Li M, Gong H, Gong Z, Liu L (2014) A conditioned visual orientation requires the ellipsoid body in Drosophila. Learn Mem 22: 56–63, DOI: 10.1101/lm.036863.114
  14. Ros T, J Baars B, Lanius RA, Vuilleumier P (2014): Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework. Front Hum Neurosci 8,1008. DOI: 10.3389/fnhum.2014.01008
  15. Moritz JM (2014): Animal suffering, evolution, and the origins of evil: toward a “free creatures” defense. Zygon 49: 348–380. DOI: 10.1111/zygo.12085
  16. Paparo GD, Dunjko V, Makmal A, Martin-Delgado MA, Briegel HJ (2014): Quantum speed-up for active learning agents. arXiv:1401.4997v1
  17. Dickinson MH (2014): Death Valley, Drosophila, and the Devonian Toolkit. Annu Rev Entomol. 59: 51–72
  18. Giurfa M, Menzel R (2013): Cognitive components of insect behavior. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p14-25
  19. Tse PU (2013): The Neural Basis of free will: criterial causation. MIT Press, 472p, 978-0-262-01910-1
  20. Giurfa M (2013): Cognition with few neurons: higher-order learning in insects. Trends Neurosci. 36(5):285-294
  21. Zhang X, Ren Q, Guo A (2013): Parallel pathways for cross-modal memory retrieval in Drosophila. J Neurosci. 33(20):8784-8793
  22. Heisenberg, M. (2013): The Origin of Freedom in Animal Behaviour. 95–103 In: Suarez, Antoine; Adams, Peter (Eds.) Is Science Compatible with Free Will? Is Science Compatible with Free Will? Exploring Free Will and Consciousness in the Light of Quantum Physics and Neuroscience. Springer 312p ISBN 978-1-4614-5212-6
  23. Bekinschtein TA, Peeters M, Shalom D, Sigman M (2012): Sea slugs, subliminal pictures, and vegetative state patients: boundaries of consciousness in classical conditioning. Front Psychol. 2:337
  24. Giurfa M (2012): Social learning in insects: a higher-order capacity? Front Behav Neurosci. 6:57
  25. Iliadi KG, Knight D, Boulianne GL (2012): Healthy aging – insights from Drosophila. Front Physiol. 3:106
  26. Tomina Y, Takahata M (2012): Discrimination learning with light stimuli in restrained American lobster. Behav Brain Res. 229(1):91-105
  27. Valente A, Huang KH, Portugues R, Engert F (2012): Ontogeny of classical and operant learning behaviors in zebrafish. Learn Mem. 19(4):170-177
  28. Giurfa M, Sandoz JC (2012): Invertebrate learning and memory: Fifty years of olfactory conditioning of the proboscis extension response in honeybees. Learn Mem. 19(2):54-66
  29. Bekinschtein TA, Peeters M, Shalom D, Sigman M (2011): Sea slugs, subliminal pictures, and vegetative state patients: boundaries of consciousness in classical conditioning. Front Psychol. 2:337
  30. Kahsai L, Zars T (2011): Learning and memory in Drosophila: behavior, genetics, and neural systems. Int Rev Neurobiol. 99:139-167
  31. van Swinderen B (2011): Attention in Drosophila. Int Rev Neurobiol. 99:51-85
  32. Young JM, Wessnitzer J, Armstrong JD, Webb B (2011): Elemental and non-elemental olfactory learning in Drosophila, Neurobiol Learn Mem. doi: 10.1016/j.nlm.2011.06.009
  33. Sorribes A, Armendariz BG, Lopez-Pigozzi D, Murga C, de Polavieja GG (2011): The Origin of Behavioral Bursts in Decision-Making Circuitry. PLoS Comput Biol 7(6): e1002075
  34. Wu Z, Guo A (2011): A model study on the circuit mechanism underlying decision-making in Drosophila. Neural Netw. 24(4):333-344
  35. Zars T (2010): Short-term memories in Drosophila are governed by general and specific genetic systems. Learn. Mem. 17: 246-251
  36. Schnaitmann C, Vogt K, Triphan T and Tanimoto H (2010): Appetitive and aversive visual learning in freely moving Drosophila. Front. Behav. Neurosci. 4:10. doi:10.3389/fnbeh.2010.00010
  37. Dunlap-Lehtilä AS (2009): Change and Reliability in the Evolution of Learning and Memory. PhD dissertation, University of Minnesota
  38. Pan Y, Zhou Y, Guo C, Gong H, Gong Z, Liu L. (2009): Differential roles of the fan-shaped body and the ellipsoid body in Drosophila visual pattern memory. Learn Mem. 16(5): 289-295
  39. Gross HJ, Pahl M, Si A, Zhu H, Tautz J, Zhang S (2009): Number-based visual generalisation in the honeybee. PLoS ONE. 4(1):e4263
  40. Iliadi KG (2009): The genetic basis of emotional behavior: has the time come for a Drosophila model? J Neurogenet. 23(1):136-146
  41. Menzel R (2009): Working memory in bees: also in flies? J Neurogenet. 23(1):92-99
  42. Pitman JL, Dasgupta S, Krashes MJ, Leung B, Perrat PN, Waddell S. (2009): There are many ways to train a fly. Fly (Austin). 3(1): 3-9
  43. Mustard JA, Edgar EA, Mazade RE, Wu C, Lillvis JL, Wright GA (2008): Acute ethanol ingestion impairs appetitive olfactory learning and odor discrimination in the honey bee. Neurobiol Learn Mem. 90(4):633-643
  44. Xi W, Peng Y, Guo J, Ye Y, Zhang K, Yu F, Gu A (2008): Mushroom bodies modulate salience-based selective fixation behavior in Drosophila. Eur. J. Neurosci 27(6): 1441-1451
  45. Maimon G, Straw AD, Dickinson MH (2008): A Simple Vision-Based Algorithm for Decision Making in Flying Drosophila. Curr. Biol. 18 (6): 464-470
  46. Isabel G, Comas D, Preat T (2007): From Molecule to Memory System: Genetic Analyses in Drosophila. In: Bontempi B, Silva AJ, Christen Y (eds.): Research and Perspectives in Neurosciences: Memories: Molecules and Circuits, 41-57. Springer Berlin Heidelberg
  47. Riemensperger T (2006): Analysis of predictive features in the dopaminergic System of Drosophila melanogaster using genetically encoded Calcium Sensors.  PhD Thesis, University of Würzburg https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/year/2006/docId/1637
  48. Yurkovic A, Wang O, Basu AC, Kravitz EA. (2006): Learning and memory associated with aggression in Drosophila melanogaster. Proc Natl Acad Sci U S A. 103(46):17519-17524
  49. Dupuy F, Sandoz JC, Giurfa M, Josens R (2006): Individual olfactory learning in Camponotus ants. Anim. Behav. 72: 1081-1091
  50. Zars M, Zars T. (2006): High and low temperatures have unequal reinforcing properties in Drosophila spatial learning. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 192(7):727-735.
  51. Katsov A, Clandinin TR. (2006): Insect vision: remembering the shape of things. Curr Biol. 16(10):R369-371.
  52. Guo J, Guo A. (2005): Crossmodal interactions between olfactory and visual learning in Drosophila. Science. 309(5732):307-310.
  53. Polavieja, GG (2005): Inteligencia en cerebros de un milímetro cúbico. Apuntes de Ciencia y Tecnología, N°16, septiembre de 2005, 28-36
  54. Manev H, Dimitrijevic N. (2005): Fruit flies for anti-pain drug discovery. Life Sci. 76(21):2403-2407.
  55. Zhang B, Lu H, Xi W, Zhou X, Xu S, Zhang K, Jiang J, Li Y, Guo A. (2004): Exposure to hypomagnetic field space for multiple generations causes amnesia in Drosophila melanogaster. Neurosci Lett. 371(2-3):190-195.
  56. Ye Y, Xi W, Peng Y, Wang Y, Guo A. (2004): Long-term but not short-term blockade of dopamine release in Drosophila impairs orientation during flight in a visual attention paradigm. Eur J Neurosci. 20(4):1001-1007.
  57. Tang SM, Wolf R, Xu SP, Heisenberg M (2004): Visual pattern recognition in Drosophila is invariant for retinal position. SCIENCE 305 (5686): 1020-1022
  58. Fentrop N (2003): Auswirkiungen eines defizits des neuronalen Zelladhäsionsmoleküls (NCAM) im Telencephalon auf Lernen, Ged?chtnis und Individualit?t bei einer gentechnisch veränderten Labormaus. PhD thesis, Universität Hamburg, Germany
  59. Schwärzel M (2003): Localizing engrams of olfactory memories in Drosophila. Subcellular organization of appetitive, aversive and extinguished memories? Dissertation, Julius-Maximilians-Universität Würzburg
  60. Siwicki KK, Ladewski L (2003): Associative learning and memory in Drosophila: beyond olfactory conditioning. BEHAV PROCESS 64 (2): 225-238
  61. Wang SP, Li Y, Feng CH, Guo AK (2003): Dissociation of visual associative and motor learning in Drosophila at the flight simulator. BEHAV PROCESS 64 (1): 57-70
  62. Wang SP, Li Y, Feng CH, Guo AK (2003): Behavioral modification in choice process of Drosophila. SCI CHINA SER C 46 (4):399-413
  63. Scherer S, Stocker RF, Gerber B (2003): Olfactory learning in individually assayed Drosophila larvae. Learn. Mem. 10(3): 217-225 MAY-JUN 2003
  64. Heisenberg M (2003) Mushroom Body Memoir: From maps to models. Nat Rev Neurosci 4: 266-275
  65. Schubert M, Lachnit H, Francucci S, Giurfa M (2002): Nonelementalvisual learning in honeybees. ANIM BEHAV 64: 175-184
  66. Wen A, Liu L (2002): Molecular mechanism of learning and memory in Drosophila. PROG BIOCHEM BIOPHYS 29 (5):670-673
  67. Tang SM, Guo A (2001): Choice behavior of Drosophila facing contradictory visual cues. Science 294 (5546):1543-1547
Brembs B. and Heisenberg M. (2001): Conditioning with compound stimuli in Drosophila at the flight simulator. J. Exp. Biol. 204 (16): 2849-2859.
Citations:
  1. Bostock E (2015): Megaselia scalaris (Diptera: Phoridae), a fly of forensic interest: advances in chronobiology and biology. PhD dissertation , University of Huddersfield.
  2. Avargués-Weber A, Lihoreau M, Isabel G, Giurfa M (2015): Information transfer beyond the waggle dance: observational learning in bees and flies. Front Ecol Evol, 3, DOI: 10.3389/fevo.2015.00024
  3. Terao K, Matsumoto Y, Mizunami M (2015): Critical evidence for the prediction error theory in associative learning. Sci. Rep., 5, 8929, DOI: 10.1038/srep08929
  4. Schubert M, Sandoz JC, Galizia G, Giurfa M (2015): Odourant dominance in olfactory mixture processing: what makes a strong odourant? Proc Biol Sci 282(1802). pii: 20142562, DOI: 10.1098/rspb.2014.2562
  5. Sanderson CE, Cook P, Hill PSM, Orozco BS, Abramson CI, Wells H (2013): Nectar quality perception by honey bees (Apis mellifera ligustica). J Comp Psychol. 127:341–351
  6. Heisenberg M (2013): Action Selection: The Brain as a Behavioral Organizer. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p9-13
  7. Guo A, Lu H, Zhang K, Ren Q, Wong YNC (2013): Visual learning and decision making in Drosophila melanogaster. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p378-394
  8. Matsumoto Y, Hirashima D, Mizunami M (2013): Analysis and modeling of neural processes underlying sensory preconditioning. Neurobiol Learn Mem. 101C:103-113
  9. Paulk A, Millard SS, van Swinderen B (2012): Vision in Drosophila: Seeing the World Through a Model’s Eyes. Annu Rev Entomol. 58:313–332
  10. Milinkeviciute G, Gentile C, Neely GG (2012): Drosophila as a tool for studying the conserved genetics of pain. Clin Genet. 82(4):359-366
  11. van Swinderen B (2011): Attention in Drosophila. Int Rev Neurobiol. 99:51-85
  12. Young JM, Wessnitzer J, Armstrong JD, Webb B (2011): Elemental and non-elemental olfactory learning in Drosophila. Neurobiol Learn Mem. 96(2):339-352
  13. Cammaerts M-C, Rachidi Z, Beke S, Essaadi Y (2011): Use of olfactory and visual cues for orientation by the ant Myrmica ruginodis (Hymenoptera: Formicidae). Myrmecol. News 16: 45-55
  14. Tabone CJ, de Belle JS (2011): Second-order conditioning in Drosophila. Learn Mem.18(4): 250-253
  15. LaBrecque A (2010): Compound Conditioning in Honeybees: No Evidence for Overshadowing in Honeybee Classical Conditioning. Thesis, New College of Florida
  16. Abramson CI, Nolf SL, Mixson TA, Well H (2010): Can Honey Bees Learn the Removal of a Stimulus as a Conditioning Cue? Ethology 116(9): 843–854
  17. Guo AK, Zhang K, Peng YQ, Xi W (2010): Research progress on Drosophila visual cognition in China. SCIENCE CHINA-Life Sciences 53 (3): 374-384
  18. Mizunami M, Unoki S, Mori Y, Hirashima D, Hatano A, Matsumoto Y (2009): Roles of octopaminergic and dopaminergic neurons in appetitive and aversive memory recall in an insect. BMC Biol. 7:46
  19. Dunlap-Lehtilä AS (2009): Change and Reliability in the Evolution of Learning and Memory. PhD dissertation, University of Minnesota
  20. Bolduc FV, Tully T. (2009): Fruit Flies and Intellectual Disability. Fly (Austin). 3(1): 91-104
  21. Smith D, Wessnitzer J, Webb B. (2008): A model of associative learning in the mushroom body. Biol Cybern. 99(2): 89-103
  22. Schubert M (2007): A Comprehensive Study of Olfactory Coding in the Insect Brain, Doctoral thesis, FU Berlin, Germany
  23. Hussaini SA, Komischke B, Menzel R, and Lachnit H (2007): Forward and backward second-order Pavlovian conditioning in honeybees. Learn. Mem. 14:678-683
  24. Hazlett BA (2007): Conditioned reinforcement in the crayfish Orconectes rusticus. Behaviour 144: 847-859
  25. van Swinderen B, Flores KA. (2007): Attention-like processes underlying optomotor performance in a Drosophila choice maze. Dev Neurobiol. 67(2):129-145.
  26. Goel P, Gelperin A. (2006): A neuronal network for the logic of Limax learning. J Comput Neurosci. 21(3):259-270
  27. Yarali A, Hendel T, Gerber B. (2006): Olfactory learning and behaviour are ‘insulated’ against visual processing in larval Drosophila. J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 192(10):1133-1145.
  28. Guo J, Guo A. (2005): Crossmodal interactions between olfactory and visual learning in Drosophila. Science. 309(5732):307-310.
  29. Guerrieri F, Lachnit H, Gerber B, Giurfa M. (2005): Olfactory blocking and odorant similarity in the honeybee. Learn Mem. 12(2): 86-95.
  30. van Swinderen B (2005): The remote roots of consciousness in fruit-fly selective attention? Bioessays, 27 (3): 321-330
  31. Greenspan RJ, van Swinderen B (2004): Cognitive consonance: complex brain functions in the fruit fly and its relatives. Trends Neurosci. 27(12): 707-711.
  32. Siwicki KK, Ladewski L (2003): Associative learning and memory in Drosophila: beyond olfactory conditioning. BEHAV PROCESS 64 (2): 225-238
Baxter D.A.; Cai Y.; Brembs B. and Byrne J.H. (2000): Simulating physiological and morphological properties of neurons with SNNAP (Simulator for Neural Networks and Action Potentials). Soc. Neurosci. Abstr. 26:21.64.
Citations:
  1. Cai, Y; Baxter, DA; Crow, T (2003): Computational Study of Enhanced Excitability in Hermissenda: Membrane Conductances Modulated by 5-HT J Comp Neurosci. 15: 105-121
  2. M Flynn, Y Cai, DA Baxter, T Crow (2003): A Computational Study of the Role of Spike Broadening in Synaptic Facilitation of Hermissenda. J Comp Neurosci. 15, 29-41.
Brembs B. (2000): An Analysis of Associative Learning in Drosophila at the Flight Simulator. Dissertation, Julius Maximilians Universität Würzburg.
Citations:
  1. Raja S (2013): The neuronal basis of spontaneous flight behavior in Drosophila. PhD dissertation, FU Berlin
  2. Ginsburg S, Jablonka E (2007): The Transition to Experiencing: II. The Evolution of Associative Learning Based on Feelings. Biol Theor, 2(3): 231-243
  3. Diegelmann S, Zars M, Zars T. (2006): Genetic dissociation of acquisition and memory strength in the heat-box spatial learning paradigm in Drosophila. Learn Mem. 13(1):72-83.
Brembs B. and Heisenberg M. (2000): The Operant and the classical in conditioned orientation of Drosophila melanogaster at the flight simulator. Learn. Mem. 7:104–115.
Citations:
  1. Patanè L, Strauss R, Arena P (2018): Controlling and Learning Motor Functions. In: SpringerBriefs in Applied Sciences and Technology. Nonlinear Circuits and Systems for Neuro-inspired Robot Control (pp 45-65). Springer, Cham. DOI: 1007/978-3-319-73347-0_4
  2. rena E, Arena P, Strauss R, Patané L (2017): Motor-Skill Learning in an Insect Inspired Neuro-Computational Control System. Frontiers in Neurorobotics. 11. DOI: 10.3389/fnbot.2017.00012
  3. Geissmann Q, Garcia-Rodriguez L, Beckwith EJ, French AS, Jamasb AR, Gilestro GF (2017): Ethoscopes: An open platform for high-throughput ethomics. PLOS Biology. 15(10): e2003026. DOI: 10.1371/journal.pbio.2003026
  4. Schultheiss P, Buatois A, Avarguès-Weber A, Giurfa M (2017): Using virtual reality to study visual performances of honeybees. Current Opinion in Insect Science. 24:43–50. DOI: 10.1016/j.cois.2017.08.003
  5. Avarguès-Weber A, Mota T (2016): Advances and limitations of visual conditioning protocols in harnessed bees. Journal of Physiology-Paris. 110(3):107–118. DOI: 10.1016/j.jphysparis.2016.12.006
  6. Bronfman ZZ, Ginsburg S, Jablonka E (2016): The Transition to Minimal Consciousness through the Evolution of Associative Learning. Frontiers in Psychology. 7. DOI: 10.3389/fpsyg.2016.01954
  7. Lucon-Xiccato T, Dadda M, Gatto E, Bisazza A (2016): Development and testing of a rapid method for measuring shoal size discrimination. Animal Cognition. 20(2):149–157. DOI: 10.1007/s10071-016-1050-x
  8. Ljubicic I, Hyland Bruno J, Tchernichovski O (2016): Social influences on song learning. Curr Op Behav Sci, 7: 101–107, DOI: 10.1016/j.cobeha.2015.12.006
  9. Taylor GJ, Paulk AC, Pearson TW, Moore RJ, Stacey JA, Ball D, van Swinderen B, Srinivasan MV (2015): Insects modify their behaviour depending on the feedback sensor used when walking on a trackball in virtual reality. J Exp Biol, 218, 3118–3127, DOI: 10.1242/jeb.125617
  10. Paulk AC, Kirszenblat L, Zhou Y, van Swinderen B (2015): Closed-Loop Behavioral Control Increases Coherence in the Fly Brain. J Neurosci 35: 10304–10315, DOI: 10.1523/JNEUROSCI.0691-15.2015
  11. Peckmezian T, Taylor PW (2015) A virtual reality paradigm for the study of visually mediated behaviour and cognition in spiders. Anim Behav, 107: 87–95, DOI: 10.1016/j.anbehav.2015.06.018
  12. Roth G (2014): The Long Evolution of Brains and Minds, Springer, ISBN 978-94-007-6259-6, pp. 1-320.
  13. Mirwan HB, Mason GJ, Kevan PG (2015): Complex operant learning by worker bumblebees (Bombus impatiens): detour behaviour and use of colours as discriminative stimuli. Insectes Sociaux, 62: 365–377, DOI: 10.1007/s00040-015-0414-6
  14. Schleyer M, Reid SF, Pamir E, Saumweber T, Paisios E, Davies A, Gerber B, Louis M (2015): The impact of odor–reward memory on chemotaxis in larval Drosophila . Learn Mem 22: 267–277,DOI: 10.1101/lm.037978.114
  15. Giurfa M (2015): Learning and cognition in insects. Wiley Interdisciplinary Reviews: 6, 383–395, DOI: 10.1002/wcs.1348
  16. Tabone CJ, De Belle JS (2014): Olfactory learning and memory assays, In: Josh Dubnau (ed.) Behavioral Genetics of the Fly (Drosophila melanogaster). pp. 231-249. Cambridge Handbooks in Behavioral Genetics. Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511920585.007.
  17. Dasgupta S, Wörgötter F, Manoonpong P (2014): Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control. Front Neural Circuits, 8:126, DOI: 10.3389/fncir.2014.00126
  18. Klowden MJ (2013): Behavioral Systems. In: Physiological Systems in Insects, 696p, Elsevier, ISBN-13: 978-0124158191
  19. Guo A, Lu H, Zhang K, Ren Q, Wong YNC (2013): Visual learning and decision making in Drosophila melanogaster. In: Menzel R, Benjamin P (eds.) Invertebrate Learning and Memory. Elsevier Science. ISBN-10: 012398260X ISBN-13: 9780123982605, p378-394
  20. Perry CJ, Barron AB, Cheng K (2013): Invertebrate learning and cognition: relating phenomena to neural substrate. Wiley Interdisciplinary Reviews: Cognitive Science 4: 561–582
  21. Panoonpong P, Kolodziejski C, Wörgötter F (2013): Combining correlation-based and reward-based learning in neural control for policy improvement. Advs. Complex Syst. 16: 1350015
  22. Giurfa M (2013): Cognition with few neurons: higher-order learning in insects. Trends Neurosci. 36(5):285-294
  23. Zwarts L, Clements J, Callaerts P (2012): Deciphering the Adult Brain: From Neuroanatomy to Behavior. In: Hassan BA (ed.):The Making and Un-Making of Neuronal Circuits in Drosophila. Neuromethods 69, pp 3-48 ISBN 978-1-61779-829-0
  24. Mery F (2012): Natural variation in learning and memory. Curr Opin Neurobiol. 23(1):52-56
  25. Nuwal N, Stock P, Hiemeyer J, Schmid B, Fiala A, Buchner E (2012): Avoidance of Heat and Attraction to Optogenetically Induced Sugar Sensation as Operant Behavior in Adult Drosophila. J Neurogenet. 26 (3-4):298-305
  26. Miller SM, Ngo TT and van Swinderen B (2012): Attentional switching in humans and flies: rivalry in large and miniature brains. Front. Hum. Neurosci. 5:188. doi: 10.3389/fnhum.2011.00188
  27. Guo AK, Zhang K, Peng YQ, Xi W (2010): Research progress on Drosophila visual cognition in China. SCIENCE CHINA-Life Sciences 53 (3): 374-384
  28. Zars T (2010): Short-term memories in Drosophila are governed by general and specific genetic systems. Learn. Mem. 17: 246-251
  29. Sokolowski MBC, Disma G, Abramson CI (2010): A paradigm for operant conditioning in Blow Flies (Phormia terrae novae Robineau-Desvoidy, 1830). J exp. Anal. Behav. 93 (1): 81-89
  30. Claridge-Chang A, Roorda RD, Vrontou E, Sjulson L, Li H, Hirsh J, Miesenböck G. (2009): Writing memories with light-addressable reinforcement circuitry. Cell 139(2):405-415
  31. Bolduc FV, Tully T (2009): Fruit flies and intellectual disability. Fly (Austin). 3(1):91-104
  32. Mizunami M, Unoki S, Mori Y, Hirashima D, Hatano A, Matsumoto Y (2009): Roles of octopaminergic and dopaminergic neurons in appetitive and aversive memory recall in an insect. BMC Biol. 7:46
  33. Dayan P, Huys QJ. (2009): Serotonin in Affective Control. Annu Rev Neurosci. 32: 95-126
  34. Wurbel, H (2009): Ethology applied to animal ethics. Appl Anim Behav Sci. 118 (3-4): 118-127
  35. Seugnet L, Suzuki Y, Stidd R, Shaw PJ. (2009): Aversive Phototaxic Suppression: evaluation of a short-term memory assay in Drosophila melanogaster. Genes Brain Behav. 8(4): 377-389
  36. Pan Y, Zhou Y, Guo C, Gong H, Gong Z, Liu L. (2009): Differential roles of the fan-shaped body and the ellipsoid body in Drosophila visual pattern memory. Learn Mem. 16(5): 289-295
  37. Menzel R (2009): Working memory in bees: also in flies? J Neurogenet. 23(1):92-99
  38. Pitman JL, Dasgupta S, Krashes MJ, Leung B, Perrat PN, Waddell S. (2009): There are many ways to train a fly. Fly (Austin). 3(1): 3-9
  39. Krylov AK, Aleksandrov YI (2007): “Situatedness in an environment” as alternative to stimuli presentation: Model study. Psykhologicheskii Zhurnal 28(2): 106-113
  40. Dupuy F, Sandoz JC, Giurfa M, Josens R (2006): Individual olfactory learning in Camponotus ants. Anim. Behav. 72: 1081-1091
  41. Liu G, Seiler H, Wen A, Zars T, Ito K, Wolf R, Heisenberg M, Liu L. (2006): Distinct memory traces for two visual features in the Drosophila brain. Nature. 439(7076): 551-556
  42. Hayden A (2005): The Role of Learning in the Feeding Behavior of Antlions. PhD thesis, Mount Holyoke College, USA http://hdl.handle.net/10090/4017
  43. Giurfa M, Malun D (2004): Associative mechanosensory conditioning of the proboscis extension reflex in honeybees. Learn. Mem. 11 (3): 294-302
  44. Siwicki KK, Ladewski L (2003): Associative learning and memory in Drosophila: beyond olfactory conditioning. Behav. Process. 64 (2): 225-238
  45. Wang SP, Li Y, Feng CH, Guo AK (2003): Dissociation of visual associative and motor learning in Drosophila at the flight simulator. Behav. Process. 64 (1): 57-70
  46. Wang SP, Tang S, Li Y, Guo AK (2003): Behavioral modification in choice process of Drosophila. SCI CHINA SER C 46 (4): 399-413
  47. Tracey WD, Wilson RI, Laurent G, Benzer S (2003): painless, a Drosophila gene essential for nociception . Cell 113(2): 261-273
  48. Le Bourg E, Buecher C (2002): Learned suppression of photopositive tendencies in Drosophila melanogaster. Anim. Learn. Behav. 30(4): 330-341
  49. Wen A, Liu L (2002): Molecular mechanism of learning and memory in Drosophila. PROG BIOCHEM BIOPHYS 29 (5):670-673
  50. Kisch J (2001): Verhaltens- und elektrophysiologische Untersuchungen zur operanten Konditionierung von Antennenbewegungen der Honigbiene. Doctoral thesis, FU Berlin, Germany.
Cutts C.J.; Brembs B.; Metcalfe N.B. and Taylor A.C. (1999): Prior residence, territory quality and life-history strategies in juvenile Atlantic salmon (Salmo salar L.). J. Fish. Biol. 55: 784-794.
Citations:
  1. Thorn MW, Morbey YE (2017): Egg size and the adaptive capacity of early life history traits in Chinook salmon (Oncorhynchus tshawytscha). Evolutionary Applications. 11(2):205–219. DOI: 10.1111/eva.12531
  2. Bolliet V, Bardonnet A (2017): Impact of Embeddedness on Salmo trutta at Different Periods of their Early Ontogenesis. In: Lobon-Cervia J, Sanz N (Eds.): Brown Trout (pp. 201–225). John Wiley & Sons. DOI: 10.1002/9781119268352.ch9
  3. Berg OK, Fleming IA (2017): Energetic Trade-Offs Faced by Brown Trout During Ontogeny and Reproduction. In: Lobon-Cervia J, Sanz N (Eds.): Brown Trout (pp. 179–199). John Wiley & Sons. DOI: 10.1002/9781119268352.ch8
  4. Chifamba PC, Mauru T (2016): Comparative aggression and dominance of Oreochromis niloticus (Linnaeus, 1758) and Oreochromis mortimeri (Trewavas, 1966) from paired contest in aquaria. Hydrobiologia. 788(1): 193–203. DOI: 10.1007/s10750-016-2997-y
  5. Näslund J, Sandquist L, Johnsson JI (2016): Is behaviour in a novel environment associated with bodily state in brown trout Salmo trutta fry? Ecology of Freshwater Fish. 26(3):462–474. DOI: 10.1111/eff.12291
  6. Winberg S, Höglund E, Øverli Ø (2016): Variation in the Neuroendocrine Stress Response. In: Schreck CB, Tort L, Farrell AP, Brauner CJ (Eds.): Fish Physiology (pp. 35–74). Elsevier. DOI: 10.1016/B978-0-12-802728-8.00002-3
  7. Näslund J, Sandquist L, Johnsson JI (2016): Is behaviour in a novel environment associated with bodily state in brown trout Salmo trutta fry? Ecology of Freshwater Fish. DOI: 10.1111/eff.12291
  8. Tiira K, Primmer CR (2015): Genetic diversity and fitness-related traits in endangered salmonids. In: Population Genetics for Animal Conservation. pp. 241-268. Conservation Biology. (No. 17). Cambridge: Cambridge University Press. Available from: Cambridge Books Online http://dx.doi.org/10.1017/CBO9780511626920.012
  9. Régnier T, Labonne J, Chat J, Yano A, Guiguen Y, Bolliet V (2015): No early gender effects on energetic status and life history in a salmonid. R. Soc. open sci., 2, DOI: 10.1098/rsos.150441
  10. Solberg MF, Fjelldal PG, Nilsen F, Glover KA (2014): Hatching Time and Alevin Growth Prior to the Onset of Exogenous Feeding in Farmed, Wild and Hybrid Norwegian Atlantic Salmon. PLoS ONE, 9, DOI: 10.1371/journal.pone.0113697
  11. Moreau DTR, Gamperl AK, Fletcher GL, Fleming IA (2014): Delayed Phenotypic Expression of Growth Hormone Transgenesis during Early Ontogeny in Atlantic Salmon (Salmo salar)? PLoS ONE, 9, e95853.
  12. Warnock WG, Rasmussen JB (2014): Comparing competitive ability and associated metabolic traits between a resident and migratory population of bull trout against a non-native species. Environ Biol Fish 97:415–423
  13. Sørensen C, Johansen IB, Øverli Ø (2013): Physiology of Social Stress in Fishes, p289-325 In: Evans DH, Claiborne JB, Currie S (Eds.): The Physiology of Fishes, CRC Press, 491p, ISBN 9781439880302
  14. Sigourney, D. B., Letcher, B. H., Obedzinski, M. and Cunjak, R. A. (2013): Interactive effects of life history and season on size-dependent growth in juvenile Atlantic salmon. Ecology of Freshwater Fish. 22: 495–507
  15. Simmons RK, Quinn TP, Seeb LW, Schindler DE, Hilborn R (2013): Summer emigration and resource acquisition within a shared nursery lake by sockeye salmon (Oncorhynchus nerka) from historically discrete rearing environments. Can J Fish Aquat Sci. 70(1): 57-63
  16. Mogensen S, Hutchings JA (2012): Maternal fitness consequences of interactions among agents of mortality in early life of salmonids. Can J Fish Aquat Sci. 69(9): 1539-1555, doi: 10.1139/f2012-071
  17. Jönsson B, Jönsson N (2011): Population Enhancement and Population Restoration. In: Ecology of Atlantic Salmon and Brown Trout (pp. 567–632). Springer Netherlands. DOI: 10.1007/978-94-007-1189-1_11
  18. van Leeuwen TE, Rosenfeld JS, Richards JG (2011): Effects of food ration on SMR: influence of food consumption on individual variation in metabolic rate in juvenile coho salmon (Onchorhynchus kisutch). J Anim Ecol. 81(2): 395-402
  19. van Leeuwen TE, Rosenfeld JS, Richards JG (2011): Failure of physiological metrics to predict dominance in juvenile pacific salmon (Oncorhynchus spp.): Habitat effects on the allometry of growth in dominance hierarchies. Can. J. Fish. Aquat. Sci. 68(10): 1811-1818
  20. Reid D, Armstrong JD, Metcalfe NB (2011): Estimated standard metabolic rate interacts with territory quality and density to determine the growth rates of juvenile Atlantic salmon. Functional Ecology. 25(6): 1360-1367
  21. Kim JW, Grant JWA, Brown GE (2011): Do juvenile Atlantic salmon (Salmo salar) use chemosensory cues to detect and avoid risky habitats in the wild? Can. J. Fish. Aquat. Sci. 68:655-662, 10.1139/f2011-011
  22. Moreau DTR, Fleming IA, Fletcher GL, Brown JA (2011): Growth hormone transgenesis does not influence territorial dominance or growth and survival of first-feeding Atlantic salmon Salmo salar in food-limited stream microcosms. J Fish Biol. DOI: 10.1111/j.1095-8649.2010.02888.x
  23. Kvingedal E, Einum S (2011): Prior residency advantage for Atlantic salmon in the wild: effects of habitat quality. Behav Ecol Sociobiol 65(6): 1295-1303
  24. Jonsson B, Jonsson N (2009): Restoration and Enhancement of Salmonid Populations and Habitats with Special Reference to Atlantic Salmon. International Symposium on Challenges for Diadromous Fishes in a Dynamic Global Environment, JUN 18-21, 2007 Halifax, CANADA: Challenges for diadromius fishes in a dynamic global environment. 69: 497-535
  25. Seiler SM, Keeley ER (2009): Competition between native and introduced salmonid fishes: cutthroat trout have lower growth rate in the presence of cutthroat-rainbow trout hybrids. Can J Fish Aqu Sci. 66 (1): 133-141
  26. Montero D, Lalumera G, Izquierdo MS, Caballero MJ, Saroglia M, Tort L (2009): Establishment of dominance relationships in gilthead sea bream Sparus aurata juveniles during feeding: effects on feeding behaviour, feed utilization and fish health. J Fish Biol. 74 (4): 790-805
  27. Neregård L, Sundt-Hansen L, Björnsson BT, Johnsson JI (2008): Growth hormone affects behaviour of wild brown trout Salmo trutta in territorial owner-intruder conflicts. J Fish Biol. 73 (10): 2341-2351
  28. Jönsson M, Skov C, Kod A, Ander Nilsson P (2008): Temporal clumping of prey and coexistence of unequal interferers: experiments on social forager groups of brown trout feeding on invertebrate drift. Oikos 117(12): 1782-1787
  29. Lelong A, Bolliet V, Bancel D, Gaudin P (2008): Detection of elemental composition and caloric value variability at individual level in newly emerged brown trout Salmo trutta L. J Fish Biol.72 (10): 2695-2699
  30. Seppänen E, Kuukka H, Huuskonen H, Piironen J (2008): Relationship between standard metabolic rate and parasite-induced cataract of juveniles in three Atlantic salmon stocks. J Fish Biol. 72 (7): 1659-1674
  31. Martin AL, Moore PA (2008): The influence of dominance on shelter preference and eviction rates in the crayfish, Orconectes rusticus. Ethology 114 (4): 351-360.
  32. Martin AL (2007): Underlying mechanisms that affect crayfish agonistic interactions and resource acquisition. Doctoral thesis, Bowling Green State University, USA
  33. Schjolden J, Winberg S. (2007): Genetically determined variation in stress responsiveness in rainbow trout: behavior and neurobiology. Brain Behav Evol. 70(4):227-238.
  34. Beckman, BR; Gadberry, B; Parkins, P; Cooper, KA; Arkush, KD (2007): State-dependent life history plasticity in Sacramento River winter-run chinook salmon (Oncorhynchus tshawytscha): interactions among photoperiod and growth modulate smolting and early male maturation. Can. J. Fish. Aquat. Sci. 64 (2): 256-271
  35. Jönsson M (2006): Fluctuating prey availability and coexistence of unequal interferers: experiments on drifting invertebrates and social foraging groups of brown trout (Salmo trutta L.), Master thesis, Lund University, Sweden
  36. Hoffman JI, Trathan PN, Amos W. (2006): Genetic tagging reveals extreme site fidelity in territorial male Antarctic fur seals Arctocephalus gazella. Mol Ecol. 15(12):3841-3847
  37. Jonsson, B; Jonsson, N (2006): Cultured Atlantic salmon in nature: a review of their ecology and interaction with wild fish. ICES J. Mar. Sci. 63 (7): 1162-1181
  38. Johnsson JI, Winberg S, Sloman KA (2005): Social Interactions. In: Schreck CB, Tort L, Farrell AP, Brauner CJ (Eds.): Fish Physiology (pp. 151–196). Elsevier. DOI: 10.1016/S1546-5098(05)24005-0
  39. Hedger, RD; Dodson, JJ; Bergeron, NE; Caron, F (2005): Habitat selection by juvenile Atlantic salmon: the interaction between physical habitat and abundance. J. Fish Biol. 67 (4): 1054-1071
  40. DiBattista JD, Anisman H, Whitehead M, Gilmour KM. (2005): The effects of cortisol administration on social status and brain monoaminergic activity in rainbow trout Oncorhynchus mykiss. J Exp Biol. 208 (14): 2707-2718
  41. Gilmour, KM; DiBattista, JD; Thomas, JB (2005): Physiological Causes and Consequences of Social Status in Salmonid Fish. Int. Comp. Biol. 45 (2) 263273.
  42. Letcher, BH; Dubreuil, T; O’Donnell, MJ; Obedzinski, M; Griswold, K; Nislow, KH (2004): Long-term consequences of variation in timing and manner of fry introduction on juvenile Atlantic salmon (Salmo salar) growth, survival, and life-history expression. Can. J. Fish. Aquat. Sci. 61 (12): 2288-2301
  43. Hoffman, JI; Boyd, IL; Amos, W (2004): Exploring the relationship between parental relatedness and male reproductive success in the antarctic fur seal Arctocephalus
    gazella.
    EVOLUTION, 58 (9): 2087-2099
  44. Weber ED, Fausch KD (2003): Interactions between hatchery and wild salmonids in streams: differences in biology and evidence for competition. CAN J FISH AQUAT SCI 60 (8): 1018-1036
  45. Vollestad LA, Quinn TP (2003): Trade-off between growth rate and aggression in juvenile coho salmon, Oncorhynchus kisutch. ANIM BEHAV 66: 561-568
  46. Harwood AJ, Griffiths SW, Metcalfe NB, et al. (2003): The relative influence of prior residency and dominance on the early feeding behaviour of juvenile Atlantic salmon. ANIM BEHAV 65: 1141-1149
  47. Lewis C, Olive PJW, Bentley MG (2003): Pre-emptive competition as a selective pressure for early reproduction in the polychaete Nereis virens. MARECOL-PROG SER 254: 199-211
  48. Jones M, Laurila A, Peuhkuri N, et al. (2003): Timing an ontogenetic niche shift: responses of emerging salmon alevins to chemical cues from predators and competitors. OIKOS 102 (1): 155-163
  49. Cutts CJ, Metcalfe NB, Taylor AC (2002): Fish may fight rather than feed in a novel environment: metabolic rate and feeding motivation in juvenile Atlantic salmon. J FISH BIOL 61 (6): 1540-1548
  50. Sloman KA, Armstrong JD (2002): Physiological effects of dominance hierarchies: laboratory artefacts or natural phenomena? J FISH BIOL 61: 1-23
  51. Cutts CJ, Metcalfe NB, Taylor AC (2002): Juvenile Atlantic Salmon (Salmo salar) with relatively high standard metabolicrates have small metabolic scopes. FUNCT ECOL 16 (1): 73-78.
  52. Johnsson JI, Forser A (2002): Residence duration influences the outcome of territorial conflicts in brown trout (Salmo trutta). BEHAV ECOL SOCIOBIOL 51 (3): 282-286.
  53. Railsback SF, Harvey, BC (2001): Individual-Based Model Formulation for Cutthroat Trout, Little Jones Creek, California, General Tech. Report PSW-GTR-182, U.S. Forest Service, Pacific Southwest Research Station, Albany, California.
  54. Brown C (2001): Familiarity with the test environment improves escape responses in the crimson spotted rainbowfish, Melanotaenia duboulayi. Anim. Cogn. 4(2): 109 – 113
  55. McCarthy ID (2001): Competitive ability is related to metabolic asymmetry in juvenile rainbow trout. J FISH BIOL 59: 1002-1014
  56. Griffiths SW, Armstrong JD (2001): The benefits of genetic diversity outweigh those of kin association in a territorial animal. P ROY SOC LOND B BIO 268 (1473): 1293-1296
  57. Sloman KA, Taylor AC, Metcalfe NB, Gilmour KM (2001): Effects of an environmental perturbation on the social behaviour and physiological function of brown trout. ANIM BEHAV 61: 325-333
  58. Berg OK, Hendry AP, Svendsen B, Bech C, Arnekleiv JV, Lohrmann A (2001): Maternal provisioning of offspring and the use of those resources during ontogeny: variation within and between Atlantic Salmon families. FUNCT ECOL 15 (1): 13-23
  59. Volpe JP, Anholt BR, Glickman BW (2001): Competition among juvenile Atlantic salmon (Salmo salar) and steelhead (Oncorhynchusmykiss): relevance to invasion potential in British Columbia. Can. J. Fish. Aquat. Sci. 58 (1): 197-207
Brembs B. (1996): Chaos, cheating and cooperation: potential solutions to the Prisoner’s Dilemma. OIKOS 76: 14-24.
Citations:
  1. Muegge, S. M. (2017): A game theory perspective on product development project charters: the project manager – project sponsor relationship as an iterated Prisoner’s Dilemma. International Journal of Project Organisation and Management, 9(1), 57. https://doi.org/10.1504/ijpom.2017.083115
  2. Noh MY, Koo B, Kramer KJ, Muthukrishnan S & Arakane Y (2016): Arylalkylamine N-acetyltransferase 1 gene (TcAANAT1) is required for cuticle morphology and pigmentation of the adult red flour beetle, Tribolium castaneum. Ins Biochem and Mol Biol. 79:119–129. DOI: 1016/j.ibmb.2016.10.013
  3. Grinsted L & Field J (2017): Biological markets in cooperative breeders: quantifying outside options. Proc Roy Soc B: Biol Sci. 284(1856), 20170904. DOI: 10.1098/rspb.2017.0904
  4. Kurokawa S (2016): Evolutionary stagnation of reciprocators. Anim Behav. 122: 217–225. DOI: 10.1016/j.anbehav.2016.09.014
  5. Sparks A, Burleigh T, Barclay P (2015): We can see inside: Accurate prediction of Prisoner’s Dilemma decisions in announced games following a face-to-face interaction. Evol Hum Behav, DOI: 10.1016/j.evolhumbehav.2015.11.003.
  6. Mendoza RL (2015): A Game-Theoretic Model of Marketing Skin Whiteners. Health Marketing Quarterly, 32: 367–381, DOI: 10.1080/07359683.2015.1093884
  7. Mariano P, Correia L (2015): The Give and Take Game: Analysis of a Resource Sharing Game. Int J Appl Math Comp Sci, 25, DOI: 10.1515/amcs-2015-0054
  8. Schroeder D A, Graziano WG, Barclay P, Van Vugt M (2015): The Evolutionary Psychology of Human Prosociality. The Oxford Handbook of Prosocial Behavior, DOI: 10.1093/oxfordhb/9780195399813.013.029
  9. Van den Berg P, Weissing FJ (2015): The importance of mechanisms for the evolution of cooperation. Proc Roy Soc B, 282, DOI: 10.1098/rspb.2015.1382
  10. Hartmann JA, Stetson S, Gaffney AM (2015): From turtles to tweets: a successful doctoral cohort reports on the development of within-group altruism. InSight: Rivier Academic Journal 11(1), p1
  11. Sparks A. (2015): Reputation Mechanisms and the Long-Term Consequences of Cooperative Behavior, PhD dissertation, The University of Guelph
  12. Enesco C. S. (2014): Tit-for-tat: La emergencia de la reciprocidad en niños y su relación
    con las conductas prosociales desde una perspectiva comparada, PhD dissertation, Universidad Complutense de Madrid
  13. Van Lange P, Balliet DP, Parks CD, van Vugt M (2014): Social Dilemmas: Understanding Human Cooperation. Oxford University Press, 208p, ISBN: 9780199897612
  14. Kemper KR (2013): Tribal Sovereignty Means Competition, Broadband Access, and Economic Development for Indian Country: A Law and Economics Analysis of the Efficiency of the efficiency of the FCC’s Standing Rock Sioux case. Journal of Information Policy 3: 442-463
  15. Franco JCA & de las Heras Camino D (2012): Cooperación en los dilemas sociales / Cooperation in Social Dilemmas. Revista Internacional de Ciencias Sociales. 1(2). http://journals.epistemopolis.org/index.php/csociales/article/view/1220
  16. Franco JCA (2011): La conservación de los recursos naturales renovables. Una aproximación desde el estudio de los dilemas sociales. PhD thesis, Universidad Rey Juan Carlos, Departamento de Fundamentos del Análisis Económico
  17. Pomianek C, Palmer CT, Wadley RL, Coe K (2011): Cultural Traditions and the Treatment of Freeriders. J Int Global Stud. 3(1): 1-20
  18. Li J, Hingston P, Kendall G (2011): Engineering Design of Strategies for Winning Iterated Prisoner’s Dilemma Competitions. IEEE Transactions on Computational Intelligence and AI in Games 3(4): 348-360, Article number 6004823
  19. Wang RW, Sun BF, Zheng Q, Shi L, Zhu L (2011): Asymmetric interaction and indeterminate fitness correlation between cooperative partners in the fig-fig wasp mutualism. J R Soc Interface. 8(63):1487-1496
  20. Stafford R Davies MS, Williams GA (2011): Cheats in a cooperative behaviour? Behavioural differences and breakdown of cooperative behaviour in aggregating, intertidal littorinids (Mollusca). Marine Ecology. 33(1): 66–74. doi: 10.1111/j.1439-0485.2011.00474.x
  21. Barclay P (2011): Competitive helping increases with the size of biological markets and invades defection. J Theor Biol. 281(1):47-55
  22. Wang RW, Sun BF, Zheng Q, Shi L, Zhu L (2011): Asymmetric interaction and indeterminate fitness correlation between cooperative partners in the fig-fig wasp mutualism. J R Soc Interface. 7, 1487–1496
  23. Dyer M, Mohanaraj V (2011): The Iterated Prisoner’s Dilemma on a Cycle. arXiv:1102.3822v1 [cs.GT]
  24. Riedel-Kruse IH, Chung AM, Dura B, Hamilton AL, Lee BC (2011): Design, engineering and utility of biotic games. Lab Chip. 11(1):14-22
  25. Bentley PJ (2009): The game of funding: modelling peer review for research grants. Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers, Montreal, Québec, Canada WORKSHOP SESSION: Evolutionary computation and multi-agent systems and simulation (ECoMASS) Pages 2597-2602
  26. Power C (2009): A Spatial Agent-Based Model of N-Person Prisoner’s Dilemma Cooperation in a Socio-Geographic Community. J Art Soc Soc Sim. 12(1)8
  27. Gardener T; Moffat J (2008): Changing behaviours in defence acquisition: a game theory approach. J. Op. Res. Soc. 59(2): 225-230
  28. Phillips T (2007): The evolution of human altruism towards non-kin through sexual selection. PhD thesis, University of Nottingham, UK
  29. Paolucci M, Conte R (2007): Roost Size for Multilevel Selection of Altruism Among Vampire Bats. In: Multi-Agent-Based Simulation VII, Springer Berlin / Heidelberg
  30. Thibert-Plante X, Charbonneau P. (2007): Crossover and Evolutionary Stability in the Prisoner’s Dilemma. Evol Comput. 15(3):321-344
  31. Thibert-Plante X, Parrott L (2007): Prisoner’s dilemma and clusters on small-world networks. Complexity 12 (6): 22-36
  32. Seip KL, Wenstøp F (2006): A primer on environmental decision-making. Springer, ISBN 1402040733, 9781402040733
  33. Galaz V (2006): Power in the Commons. The Politics of Water Management Institutions in Sweden and Chile. PhD thesis, Göterborgs Universitet, Sweden.
  34. Garcia J, Hernandez G, Galeano JC (2006): Cooperation, Solution Concepts and Long-term Dynamics in the Iterated Prisoner’s Dilemma. IEEE Congress on Evolutionary Computation CEC 2006: 1618 – 1623
  35. Conte R, Paolucci M, Di Tosto G (2006): Vampire Bats & The Micro-Macro Link. In: Billari FC, Fent T, Prskawetz A, Scheffran J (eds.) Agent-Based Computational Modelling – Applications in Demography, Social, Economic and Environmental Sciences. Physica-Verlag HD, Springer.
  36. Fishman MA. (2006): Involuntary defection and the evolutionary origins of empathy. J Theor Biol. 242(4):873-879
  37. Petersen CW (2006): Sexual selection and reproductive success in hermaphroditic seabasses. Int. Comp. Biol. 46 (4): 439-448
  38. Anthes N, Putz A, Michiels NK (2006): Sex role preferences, gender conflict and sperm trading in simultaneous hermaphrodites: a new framework. Anim. Behav. 72: 1-12
  39. Kun A, Boza G, Scheuring I (2006): Asynchronous snowdrift game with synergistic effect as a model of cooperation. Behav. Ecol. 17 (4): 633-641
  40. Corning PA (2005): Holistic Darwinism: Synergy, Cybernetics, and the Bioeconomics of Evolution. University of Chicago Press, 546pp.
  41. Waisel DB (2005): Developing Social Capital in the Operating Room: The Use of Population-based Techniques. Anesthesiology. 103(6):1305-1310
  42. Doebeli M, Hauert C (2005): Models of cooperation based on the Prisoner’s Dilemma and the Snowdrift game. ECOLOGY LETTERS 8 (7): 748-766
  43. Kreft JU (2005): Conflicts of interest in biofilms. Biofilms 1: 265-276
  44. Green SP (2004): Cheating. Law Philosoph. 23(2): 137-185
  45. Daniels H (2004): Facultative butterfly-ant interactions – the role of variation in composition of nectar secretions. PhD thesis, University of Bayreuth, Germany
  46. Jang D. Whigham DA, Grant D (2004): On evolving fixed pattern strategies for Iterated Prisoner’s Dilemma. Proc. 27th Australasian conf. Comp. sci. – Vol 26. 241 – 247
  47. Gillinson S (2004): Why Cooperate? A Multi-Disciplinary Study of Collective Action. Working paper 234, Overseas Development Institute, London, UK
  48. Allen D, Griffiths L, Lyne P (2004): Understanding complex trajectories in health and social care provision. SOCIOLOGY OF HEALTH & ILLNESS 26 (7): 1008-1030
  49. Jang D, Wigham PA, Dick G (2004): On evolving fixed pattern strategies for Iterated Prisoner’s Dilemma. Proceedings of the 27th conference on Australasian computer science 26: 241-247
  50. Gutnisky DA, Zanutto BS (2004): Cooperation in the iterated prisoner’s dilemma is learned by operant conditioning mechanisms. ARTIFICIAL LIFE 10 (4): 433-461
  51. Foster KR. (2004): Diminishing returns in social evolution: the not-so-tragic commons. J Evol Biol. 17(5):1058-1072.
  52. McNamara JM, Barta Z, Houston AI (2004): Variation in behaviour promotes cooperation in the Prisoner’s Dilemma game. NATURE 428 (6984): 745-748
  53. Greig D, Travisano M (2004): The Prisoner’s Dilemma and polymorphism in yeast SUC genes. P ROY SOC LOND B BIO 271: S25-S26 Suppl. 3
  54. Wobser G (2003): Produktentwicklung in Kooperation mit Anwendern. In: Enke M (ed) Interaktivs Marketing – Wissenstransfer zwischen Theorie und Praxis. DUV Gabler Edition Wissenschaft.
  55. Mariano P, Correia L (2003): A resource sharing model to study social behaviours. LECT NOTES ARTIF INT 2902: 84-88
  56. Dubois F, Giraldeau LA (2003): The forager’s dilemma: Food sharing and food defense as risk-sensitive foraging options. AM NAT 162 (6): 768-779
  57. Gallanger, S, Park, S.H. (2003): Branching out. Potentials, IEEE 22(2): 20-21
  58. Lotem A, Fishman MA, Stone L (2003): From reciprocity to unconditional altruism through signalling benefits. P ROY SOC LOND B BIO 270(1511): 199-205
  59. Conte R, Paolucci M (2002): Reputation in Artificial Societies – Social Beliefs for Social Order ISBN: 978-1-4613-5421-5 (Print) 978-1-4615-1159-5 (Online)
  60. Simms EL, Taylor DL (2002): Partner choice in nitrogen-fixation mutualisms of legumes and rhizobia. INTEGR COMP BIOL 42:369-380
  61. Mariano P, Correia L (2002): The Effect of Agreements in a Game with Multiple Strategies for Cooperation. In: Artificial Life VIII, Standish, Abbass, Bedau (eds)(MIT Press) 2002. pp 375-378
  62. Bird RB, Bird DW, Smith EA, Kushnick GC (2002): Risk and reciprocity in Meriam food sharing. EVOLUTION AND HUMAN BEHAVIOR 23:297-321
  63. Hare JF, Atkins BA (2001): The squirrel that cried wolf: reliability detection by juvenile Richardson’s ground squirrels (Spermophilusrichardsonii). BEHAV ECOL SOCIOBIOL 51: 108-112
  64. Wakano JY, Yamamura N (2001): A simple learning strategy that realizes robust cooperation better than Pavlov in Iterated Prisoners’ Dilemma. J ETHOL 19: 1-8
  65. Flache, A, Torenvlied R (2001): Persistent instability in polarized opinion formation and collective decision-making. Paper presented at the fourth Summer School on Polarization and Conflict, July 23–27, San Sebastián, Spain.
  66. Bronstein JL (2001): The exploitation of mutualisms. ECOLLETT 4: 277-287
  67. Wilkinson DM, Sherratt TN. (2001): Horizontally acquired mutualisms, an unsolved problem in ecology? OIKOS 92:377-384
  68. Fishman MA, Lotem A, Stone L (2001): Heterogeneity stabilizes reciprocal altruism interactions J THEOR BIOL 209: 87-95
  69. Sigmund K, Nowak, MA (2000): A Tale of Two Selves. Science 290(5493): 949-950
  70. Sigmund K, Nowak, MA (2000): Shrewd Investments. Science 288(5467): 819-820
  71. Agrawal AA, Fordyce JA (2000): Induced indirect defence in a lycaenid-ant association: the regulation of a resourcein a mutualism. Proc. R. Soc. Lond. Ser. B-Biol. Sci., 267,1857-1861
  72. Bordini RH (1999): Contributions to an anthropological approach to the cultural adaptation of migrant agents. PhD thesis, University College London.
  73. Bazzan ALC, Bordini RH, Campbell JA (1999): Moral sentiments in multi-agent systems. Lect. Note. Artif. Intell.,1555, 113-131.
  74. Sherratt TN, Roberts G (1999): The evolution of quantitatively responsive cooperative trade. J. Theor. Biol., 200, 419-426.
  75. Wilkinson DM (1999): Bacterial ecology, antibiotics and selection for virulence. Ecol. Lett., 2, 207-209.
  76. Bazzan ALC, Bordini RH, Campbell JA (1998): Moral Sentiments in Multi-agent Systems. Paper presented at “Intelligent Agents V. Agent Theories, Architectures, and Languages”: 5th International Workshop, ATAL’98, Paris, France
  77. Doebeli M, Knowlton N (1998): The evolution of interspecific mutualisms. Proc. Natl. Acad. Sci. U. S. A., 95, 8676-8680.
  78. Sherratt, TN (1998): The evolution of generosity and choosiness in cooperative exchanges. J. Theor. Biol., 193, 167-177.
  79. Day T, Taylor PD (1998): The evolution of temporal patterns of selfishness, altruism, and group cohesion. Am. Nat.,152, 102-113.
  80. Borges RM (1998): Leviathan, natural selection, and ethics. Curr. Sci., 74, 750-758.
  81. Roberts G (1998): Competitive altruism: from reciprocity to the handicap principle. Proc. R. Soc. Lond. Ser. B-Biol. Sci.,265, 427-431
  82. Wedekind C (1998): Give and Ye Shall Be Recognized. Science 280(5372): 2070-2071