Jul09

The Conversation: The looming crisis in science

In: science politics • Tags: , , , , ,

This is a slightly edited (amended, essentially) version of my article published today at The Conversation.

In cases where a problem within a community is detected and collective action is required to address the problem. one needs to strike a fine line or any efforts to convince the community that action is required will fail. If one describes the problem too cautiously, the message will be ineffective in rallying the community and collective action will not happen. Describe the problem too drastically, and the community will not be convinced by the alarmist rhetoric and also fail to take action.

Here are some data, together with a computed trend that indicates what I think would be best described as a looming crisis for the scientific community: not yet urgent, but if no action is taken, the trend will threaten the entire scientific enterprise within the coming 30 years.

Currently, the number of scientific papers retracted from PubMed is a mere 0.05%, an astonishingly low rate, given the vagaries of the job and the common .05 statistical significance level in biomedicine. However, recently this rate has been rising. The rise is exponential such that, if the trend were to continue, by about 2045 almost all scientific publications will have to be retracted. Apart from high-profile fraud cases which since recently also make it into the general news media, the numbers themselves are not yet alarming. Extrapolating the current trend, we will not reach the .05-level, i.e. 5% of all published articles in a given year will be retracted, before 2033 – it will take almost twenty years for this hundredfold increase, i.e. doubling about every three years. If the current trend were to continue that far into the future, 10% would be reached about 2036, 20% in 2039, 40% in 2042, 80% in 2045 and soon thereafter, for every new publication in PubMed, at least one older one would have to be retracted.

Causes

Usually, any problem at this scale will have a number of underlying causes. Science, like any enterprise, is a complex affair. In this special case, however, a large part of these causes can be traced to the reward structure that scientists have built around them to make this enterprise work. They are related to how scientists choose to publish their results and how fellow scientists reward this publishing behavior.

Unfortunately, even with a clearly identifiable cause, in this case there is no easy fix.

History

Starting in the 1960s, the rising number of scholarly journals increased subscription costs for libraries too quickly. Institutional libraries and university faculty were faced with the problem of deciding which journals to read and subscribe, keeping their budgets in mind. One solution, it seemed, was to rank journals according to how many citations each of its publication garnered on average.

Back then only a few realized that a generation later their future colleagues would not only adjust their reading habits to journal rank, but that those reading habits will translate into new publishing habits. After all, every one wants their work to be read by as many as possible.

Today, where you publish matters more than what you publish. This behavior may vary from country to country and field to field, but it is quite widely known that tenure, promotion, grant funding, etc. all depends on where in the hierarchy of journals one’s research results have been published.

What makes it worse is this feedback loop: more citations means more attention. More attention more citations. As long as space is scarce, more manuscript submissions mean higher rejection rates, for some journals the rejection rates can be as high as 90%. Like long lines in front of hip clubs, higher rejection rates mean more validation for the few researchers that actually manage to get published in these journals and hence more citations.

Publishers

Not surprisingly, as researchers adjusted their behavior, so did publishers. The top journals did not increase space for the increased demand. Instead, they spawned ever more lower ranking offspring to reinforce the ratchet and keep the demand high.

With the arrival of the internet, publishers went through a complete reversal of their role in knowledge dissemination. Before the internet, publishers would heed their profession, investing in printing presses and delivery systems for a wide and efficient system of dissemination to the public. Today, academic publishers have become the opposite. These corporations are now “hiders”: they invest in paywalls, hiding the research from the public that paid for it.

But perhaps this is all fine and well? After all, publishers select the very best science using professional editors and need to protect their investment.

Rankings

Superficially, one may assume that such strong selection would only enable the most groundbreaking, methodologically sound research to clear such monumental hurdles. However, the data speak a different language. While indeed quantifications of ‘novelty’ and ‘importance’ have been found to correlate significantly with journal rank, the correlation is so weak, that for every publication correctly published in a high-ranking journal, there is one that should not have been published there. Conversely, such a large percentage of research findings that did not manage to get published in a top journal end up being recognized as deserving after being published in a lower journal, that the practical value of journal rank as an evaluation signal is negligible, despite the statistics. Even more damaging, however, quality-related metrics such as technical quality, methodological soundness, reproducibility and so on either failed to show any correlation with journal rank, or correlate negatively. These data support the observation of decreasing intervals between prominent scientific fraud scandals and the increasing range and scope of each case, mostly based on fraudulent work published in top journals.

Marketing

Apparently, as the pressure mounts to publish in top journals, authors race to find a way to present their work as important and groundbreaking, no matter the actual content and quality. Science today has become a rat race between authors marketing their research and professional editors struggling to see through the fluff. It is the perfect arrangement to bring our the worst in all participants: scientists fear for their livelihoods and do what is necessary to survive, with little regard to science. Publishers fear their business model and do what is necessary to survive, with little regard to science. And librarians are caught in the middle.

Multiplicators

This straightforward, evidence-based analysis of the current state of affairs suggests a slightly more alarmist suspicion. Exponential effects are typical for social phenomena, where feedback is driving much of the dynamics of the system. The already described, relatively fast feedback loop propped up by journal rank supports a second, slower loop: after a generation of increasing pressure to publish in top journals, many of the now leading scientists are excellent at marketing their research to top journals. After all, this is how they were selected. It may of course happen that these researchers are also excellent scientists, but this was often enough not the selection criterion. These scientists are now training the next generation of scientists in how to be successful in science. The anecdotal evidence suggests that – intentional or not – marketing one’s research to top journals may play a dominant role in this training. If this were indeed the case, it would help explain the exponentially increasing retraction rates in the scientific literature and constitute cause for grave concern with respect to the looming crisis in science.

Reform

Of course, laziness, vanity, ambition, desperation, hubris, self-aggrandizement, sleep deprivation or bad time management are not going to disappear any time soon. Scientists are human too. The realistic task can thus not be to altogether eliminate shoddy, unreliable science, but to reform our infrastructure which currently almost appears to be purposefully designed to exacerbate aforementioned traits and bring out the worst in scientists, thereby wasting resources and threatening lives. Scientific discoveries are unreliable enough even under the best of circumstances, given the complexity of the matter, there surely is no need to worsen the situation. Instead, we must design an infrastructure that brings out the best in scientists and aligns their incentives with that of science and the public.

Technicalities

Given the current status quo, this is technically rather straightforward: one has to remove the incentives for scientists that encourage and reward marketing at the expense of science and instead encourage and reward actions of scientists that benefit both science and scientists. Given that scholarly communication is at the heart of the scientific endeavor, this is where we should place most emphasis in our infrastructure reform. What we need is to abandon the traditional idea of journal publishing altogether, in favor of an institution-based platform that allows every tax-payer, scientist or not, to access all the literature, data and software that is being paid for out of the public purse. For the past two decades, corporate publishers have proven to have become exceedingly poor custodians of the public good that is research results. From their continued and often shamefully backstabbing and cunning resistance to change their business model to provide even simple read-only access to the scientific literature to those who paid for the research in the first place, to the current prohibition of text- and data-mining access for scientists to their own literature, corporate publishers have proven beyond the shadow of a doubt that they have forfeited every right to be perceived as partners of scientists. Instead, the evidence weighs heavy that many if not most of these corporations are now enemies of science.

Solutions

Small versions of such open access platforms exist in many university libraries today, in various forms. They need to be combined and made interoperable using common standards. In less fortunate parts of the world, where research billions are not as abundant, governments felt forced, long before us, to realize how wastefully corporate academic publishing treats tax-funds. These countries have very successfully been running a multi-national platform, SciELO, which, if implemented on a global scale and funded with only a single digit fraction of what corporate publishing costs today, would eliminate the pernicious incentives currently in place and provide full open access to the public. Recent initiatives like SHARE, the DPLA or the LPC could serve as nucleation points for such developments in the rich countries. Provided that the reputation system built into this platform is guided by the same evidence-based reasoning and tested with the same scientific rigor we commonly apply to our experiments, this kind of reform would not only come for free, it would save billions in tax-funds every year and, by virtue of its public accessibility, literally save countless lives.

It is a collective disgrace for the entire scientific community that saved money and saved lives are apparently not sufficient incentives to drive forceful and rationally designed reform right now. Instead, as in many other communities, vested, not exclusively corporate, interests are still keeping an upper hand.
This must change.

Posted on July 9, 2013 at 02:40 Comments Off on The Conversation: The looming crisis in science
Jul08

Flashback: The neurobiology of self-learning

In: blogarchives • Tags: , , , , , ,

During my flyfishing vacation last year, pretty much nothing was happening on this blog. Now that I’ve migrated the blog to WordPress, I can actually schedule posts to appear when in fact I’m not even at the computer. I want to use this functionality to re-blog a few posts from the archives during the month of august while I’m away. This is the first post in this series, just to see if it works and what needs to be tweaked. This post is from October 31, 2011:

 

It’s been a while since I’ve last been so excited about a new finding by someone else And until today, this paper from last week even flew completely under my radar. I had seen the title and decided it’s not relevant. A collaborator of mine sent it to me after she found it searching for a current affiliation of a former postdoc of hers – which was how she realized how pertinent this work was to our research and sent it to me (which says something about the way scientists are able to stay on top of the literature. Note to self: write separate post!).

This paper detailing experiments in transgenic mice joins a pair of papers in invertebrate model systems ( Aplysia and Drosophila), suggesting that brains have two distinct molecular learning mechanisms, one to learn about relationships among events in the world around them and one to learn about the effects of their own behavior on the world. This distinction shares several conceptual features with the distinctions that have been made between operant conditioning and classical conditioning or between declarative and procedural memory, and several other related dichotomies, but is yet slightly different.

Here’s a drastically simplified diagram of what the current canonical pathway looks like for ‘synaptic plasticity’, the kind of physiological process that modifies the connections between neurons in order to store memories (screenshot from one of my talks):

canonical_small.png

Briefly, the to-be-remembered information is translated into neuronal signals which are eventually translocated into the memory-storing neuron, where an adenylyl cyclase (encoded by the rutabaga gene in flies) generates cAMP, which activates Protein Kinase A (PKA), which in turn eventually activates a protein with the acronym CREB. CREB is a transcription-factor switching on genes which modify the neuron, storing the memory. Not shown is how PKA can itself also modify the neuron to allow memories to form almost instantaneously, without the need for protein synthesis (which takes a while). OK, this is really extremely simplified, but the important point here is that there is no Protein Kinase C (PKC) involved. In fact, PKC has been shown to either not be involved at all, or only to maintain the memory, long after it’s been formed. The cool thing about this learning mechanism (and why its discovery got the Nobel Prize in 2000) is that you find it in all bilaterian animals, e.g. flies, snails and mice.

In 2008 I wrote here about one of our publications that we had discovered a ‘Skinnerian‘ learning mechanism, which did not require the rutabaga gene, but PKC. Back then we couched the discovery in terms of the 70-something year-old debate about whether operant and classical conditioning share a common learning mechanism or not. The idea was that operant conditioning involves learning about the consequences of one’s behavior while classical conditioning involves learning about the ring of a bell being followed by food For this experiment, we used the genetic toolkit of Drosophila to express an inhibitor of PKC (PKCi) in all cells of the fly only during the experiment. These flies had trouble learning an operant task in which all external cues had been removed, but as soon as ‘classical’ cues were added, they learned just fine.

This discovery was followed in the same year by a paper from my postdoctoral lab that showed basically the analogous outcomes in the marine snail Aplysia. This got me very excited: flies and snails? What about the chordates?

conservation_small.png

In their new paper, Rochefort et al. express the same PKCi peptide that we had used in our fly study in the cerebellum of mice. They use these mice to perform orientation and navigation experiments in which the animals either have to rely on self-motion cues (procedural learning) or on the position and identity of external cues (declarative learning) to find a particular location. It turned out that in all three of their experiments, whenever the animals could rely on external cues, they learned to find the location just fine. However, when the cues either were removed or arranged in a way to conflict with each other, the mice showed a severe decrement in performance. In other words, also these colleagues found a PKC-dependent form of learning which is mainly concerned with the behavior of the animal itself and less with learning about events in its environment.

Are these experiments in three model systems enough to make a strong claim there we are in the process of opening up a new field of research, the study of ‘self-learning‘? I wouldn’t think so if we wouldn’t have yet another piece of evidence up our sleeves: we are currently in the process of submitting a manuscript that details our results on the fly gene most closely related to the ‘language gene‘ (that wasn’t), FOXP2. Briefly, language acquisition can be thought of as an operant process: babies babble and use the auditory feedback of what it sounded like when they babbled to change their babbling – eventually into language. Songbirds learn their songs in a quite similar way. Both humans and songbirds have trouble learning their respective vocalizations if the gene FoxP2 is not intact. So we went and looked for a homologous gene in Drosophila, found it (dFoxP), manipulated it and found that the manipulations had the same effect as the PKCi expression: self-learning was affected and world-learning wasn’t.

Thus, we (several different labs independently) now appear to have discovered not one, but two components of this new self-learning mechanism, PKC and FoxP:

nuplast_small.png

In fact, evidence from Aplysia suggests that this mechanism also includes cAMP, but form a different cyclase and activating a different sort of PKA. However, this has not been tested in the other systems, so far.
Thus, I think there now are too many converging results from very disparate experiments to just be chance. I now have the very strong suspicion that we are on the cusp of the birth of a new research field: the neurobiology of self-learning.

Rochefort, C., Arabo, A., Andre, M., Poucet, B., Save, E., & Rondi-Reig, L. (2011). Cerebellum Shapes Hippocampal Spatial Code Science, 334 (6054), 385-389 DOI: 10.1126/science.1207403

Posted on July 8, 2013 at 19:41 Comments Off on Flashback: The neurobiology of self-learning
Jul05

Tweetlog: neuroscience and #openaccess

In: Tweetlog • Tags: , ,

This is the tweetlog covering July 3-5:

Posted on July 5, 2013 at 15:06 Comments Off on Tweetlog: neuroscience and #openaccess
Jul05

…and now for some lock-picking cockatoos

In: random science video • Tags: , , , ,

Yesterday, Alex Kacelnik published yet another fascinating discovery – one of many over the years out of his lab. This time, they show how birds can pick even five consecutive locks to get to a food reward:

According to the authors, the birds solve this problem by trial and error, i.e., in the operant, goal-directed way, which is the learning mechanism we study in our lab.

Posted on July 5, 2013 at 13:23 Comments Off on …and now for some lock-picking cockatoos
Jul04

The dysfunctionality of the scholarly literature: hyperlinks

In: science politics • Tags: , , ,

This morning I was reminded of the age of some of the technology we’re using. Hyperlinks were developed at Stanford University and first demonstrated by their inventor Douglas Engelbart (using the first mouse) in 1968:

The Mother of All Demos, presented by Douglas Engelbart (1968)
The Mother of All Demos, presented by Douglas Engelbart (1968)

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On Tuesday, Douglas Engelbart died, even before the scholarly literature was able to fully implement the technology he invented, 45 years and counting. You might wonder if I could provide you with evidence for the outrageous claim that such a standard technology that the internet (also invented by scientists) has been using for over 20 years cannot be used in the scholarly literature. Well, just go to any experimental paper and search for the methods section. Very often, you will find references there to previous work such as “experiments were performed as previously described (ref)”. If you read this in a PDF file, most likely all you will see then is a reference to the other paper. If you are lucky and read it in the HTML version online, you might get to see a link at the reference, sort of like this one (click for larger version):

hyperlinks

If you’re even more lucky, that link takes you to a paper that you can read and search for the actual passage where they describe the method. If you’re less lucky, you hit a paywall. But even if you get to read the paper, there may be just a reference to yet another paper and so on. In short, chances are, that you will have to spend considerable amount of time and effort (and perhaps money) if you want to find out what the authors actually did.

Why can’t we just link to the passage in the paper where the procedure is actually explained and then, when anybody clicks on that link, the pertinent section of the reference pops up? After all, this is what everybody else but scientists have been doing for over twenty years. When will scientists catch up to the rest of the world?

Posted on July 4, 2013 at 10:54 1 Comment
Jul03

Trying a new feature: Tweetlog

In: Tweetlog • Tags:

Following the example of Glyn Moody, I thought I’d start a log on the tweets I send around. One never knows what’ll happen to Twitter and besides, this provides a neat place to store and find everything. So here are the tweets for July first and second:

That’s that for now. We’ll see how frequently I’ll be updating this category and for how long I manage to do it.

Posted on July 3, 2013 at 09:19 Comments Off on Trying a new feature: Tweetlog
Jun29

Amazing bead chain experiment

In: random science video • Tags: , ,
Amazing Slow Motion Bead Chain Experiment | Slow Mo | BBC Earth Explore
Amazing Slow Motion Bead Chain Experiment | Slow Mo | BBC Earth Explore

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via io9

Posted on June 29, 2013 at 14:49 Comments Off on Amazing bead chain experiment
Jun27

#icanhazpdf more public than a publication?

In: science politics • Tags: , , ,

This anecdote made my day today. On a Drosophila researcher mailinglist, someone asked if anybody on the list had access to the Landes Bioscience journal ‘Fly‘. I replied by wondering that if on Twitter didn’t work, the days of ‘Fly’ are probably counted, with nobody subscribing. A few minutes later, the author of the original email replied that he hadn’t dared using before emailing the list because the idea in the paper he was interested in was so easy to scoop, that he didn’t want people to know about the paper. He feared that the “broadcast approach” of would alert people to the paper!

In other words, at least in the perception of this one colleague, as long as nobody would draw attention to a peer-reviewed publication using Twitter, chances are low that anybody would pay attention to it. Obviously, the fact that a niche journal is behind a paywall contributes to this perception:

It is testament to our dysfunctional communication system that Twitter is perceived as a better medium to make a discovery public than a publication in a peer-reviewed, scientific journal. In a variation of an old saying, one could say: “if it isn’t on Twitter, it isn’t published”.

Posted on June 27, 2013 at 13:03 Comments Off on #icanhazpdf more public than a publication?
Jun21

Funder mandates: Are scientists like junkies?

In: science politics • Tags: , , ,

Mike Taylor wrote about how frustrated he is that funders don’t issue stronger open access mandates with sharper teeth. He acknowledges that essentially, the buck stops with us, the scientists, but mentions that pressures on scientists effectively prevent them from driving publishing reform. Obviously, from the scientist’s perspective, this is a classic collective action problem: every scientist who would start boycotting corporate publishers would be risking their livelihood. On the other hand, if we all started to publish exclusively in a world-wide, federated scholarly communication system, based on a collective of SciELO or SHARE-like platforms, we would not only save billions in publishing costs every year and provide fully open access as an added benefit, but also no scientist would risk anything.

As I see it, there are two (clearly not mutually exclusive) approaches to this problem:

1. Ask for outside help. One can see scientists like junkies: they are addicted to publishing in the journals of parasitic publishers and can’t possibly wean themselves from their fix. This appears to be Mike’s position and Stevan Harnad‘s (although they probably might disagree on green vs. gold details). There is no doubt that this would work, if implemented as Mike and Stevan (and many others) argue. Thus, of course, it would be foolish to not embrace and welcome funder mandates.

2. Work on removing the pressures on scientists that prevents them from collective action. The fix is essentially mediated by the hierarchy of journals which bestows prestige on scientists and which decides who gets to keep their livelihoods and who don’t. To address this issue, we recently published a paper in which we outline that there is no empirical foundation for journal rank, in an attempt to effectively remove the fix.

While both approaches need to be pursued, personally, I strongly favor the second route. It annoys the hell out of me that we scientists creep and crawl on all fours to politicians, funders, publishers asking them to force us to do something we should bloody well be able to do ourselves: we broke the system, we fix it. Begging others to save us from the hell we created for ourselves is probably the one single most annoying aspect of the entire situation. We’re already living and researching off of people’s taxes and now we ask yet more for help – isn’t there anything we can do ourselves? Can’t we even get our own house in order without the help from someone who doesn’t have any direct responsibility for the quagmire?

I just can’t get over the humiliation that urging funders to do what we should be doing is essentially like saying: “we’re too weak to do it ourselves, please, in addition to all the money we’re already getting from you, could you please also do the mandates for us and, while you’re at it, shell out the dough to police and enforce the mandates?”

Funder mandates are great. They have been instrumental in getting us as far as we have gotten and while they are humiliating, they get the job done and work as advertised. Mike is correct in that they could have more teeth, but at least the funders have gotten the ball rolling with approach . When will we start to do our part and launch approach #2? Where’s the response from scientists saying: “thank you funders, here’s what we will do!” Instead, we keep pleading for yet more help.

Where’s the quid pro quo from us scientists? Does it always have to be a one-way highway of public service to the scientific community and none out of it? Is the scientific community really such a black-hole of public goods? Or is that just my myopic perspective?

Posted on June 21, 2013 at 15:27 2 Comments
Jun20

Free will: it’s not what you think it is

In: science • Tags: , , ,

To my knowledge, no neuroscientist hypothesizes that there is magic in our heads. However, it appears this is a hypothesis that flies by the editors at the New York Times. The title of this op-ed piece says it all: “beyond the brain”. The author, David Brooks, claims: “The brain is not the mind.” Last I looked (which was a few seconds ago, I admit), beyond the brain was the Pia mater, the subarachnoid space, the Arachnoid, the dura mater and the skull. I wonder, just where precisely does the magic mind sit, if it’s not the brain? In the subarachnoid space, squeezed between layers of connective tissue and blood vessels? Or is it even beyond the skull, hovering above our heads? Now, Mr. Brooks doesn’t mention the Psychokinetic Energy Meter, but he makes it sound as if in his world this is the scientific instrument with which one would measure the capacity of the mind to move the body. Probably most disappointingly, Mr. Brooks bolsters his magic-mind hypothesis with the classic argument from incredulity: ‘I don’t understand it, so it must be magic’: “It is probably impossible to look at a map of brain activity and predict or even understand the emotions, reactions, hopes and desires of the mind.” This is like saying “it’s probably impossible to build a heavier-than-air flying machine” before the Wright brothers’ first flight. More disturbingly, it’s like saying: “I don’t understand no evilution, therefore magic man dunnit”.

Mr. Brooks caps his magic-mind hypothesis off with a few short paragraphs essentially saying “we have free will because I think so, free will is magic, so there’s magic in the head – and science is too limited to get into magic, don’t you forget that!” Given that his main point is that the mind is magic, one can only assume that he means neuroscience is too limited to understand free will sort of like medicine is too limited to understand homeopathy and physics is too limited to understand astrology. This final point is probably the only accurate statement of the entire piece: magic in the head is about as thoroughly debunked as homeopathy or astrology.

What we call ‘mind’ exists in a similar way as colors exist: our brain creates it. Colors are real in the sense that our brain makes colors real, it constructs a reality with colors, but spectral properties of light are not colors. Just like colors, the mind, free will, are real, but not in the way Mr. Brooks apparently thinks: they’re not magic. Neural activity makes our minds just as real as colors, but neither are magic nor do they exist outside of our heads. The fact that we don’t understand, yet, how the brain does that, is not a valid reason to explain our ignorance away with magic, but a boon to neuroscientists (or we’d be unemployed). The correct answer to the question: “what is the mind?” is not “magic”, but “we don’t know how, but all the evidence says it’s our brain that somehow creates it”.

This very fundamental insight of the last 40 years or so of neuroscience, obviously entails that with every discovery we will be better able to predict future actions. If that seems disappointing, tough luck, live with it. Today, we clearly cannot “take pretty brain-scan images and […] use them to predict what product somebody will buy”, this is pop-neuroscience. However, much like we got better at predicting the weather by studying it, we will get better at predicting future actions by studying the brain – as we have already become much better over the last decades. Importantly, and I cannot stress this enough, we don’t need magic to understand that we will nevertheless, not even with unlimited time and resources, never be able to fully predict human behavior. Just like no neuroscientist postulates magic in our heads, no meteorologist would postulate that it’s magic that prevents us from making accurate weather forecasts and no astrophysicist would claim that magic messes with Pluto’s unpredictable orbit. Apparently, it will take a few more decades until it sinks in that the brain is a little more complex than the weather or our solar system. Anybody who thinks that the brain needs magic to bring about the mind with free will thoroughly underestimates it. Everybody and their grandma today has already realized that complex nonlinear dynamics (“butterfly effect”, “chaos” – coincidentally coined in the same decade that dualism essentially died) prevent accurate weather forecasts on a principle basis, not out of technical problems. These effects even make the orbit of Pluto unpredictable! The data from brain recordings and behavioral studies show mathematically analogous nonlinearities, which lead to the predictability of behavior to decay exponentially with the forecasting period even in flies. Clearly, one can assume that humans are less nonlinear and more predictable than flies as apparently Joshua Greene at Harvard seems to postulate, but even as a fly researcher, I find that somewhat hard to accept. But hey, what does a fly guy know? Be that as it may, as long as humans are equally or less predictable than fruit flies, the data from our own little lab alone already alleviate Mr. Brooks’ fears: brains will not become fully predictable with more neuroscience, only gradually more so.

It seems there is a deep-seated frustration that science explains away magic, even in otherwise science-o-phile individuals. More and more research (some of it reviewed here) is accumulating that demonstrates that not only our flies, but many, perhaps all animals have the capacity, given the right circumstances, to make different decisions under identical circumstances. In fact, as has often been argued (review here) before, such protean behavior is a prerequisite and an inevitable outcome of evolution. Why should animal brains possess this capacity and human brains not? If this kind of free will disappoints you, tough luck, live with it. Free will is the capacity of the brain to make decisions that are influenced by all the events leading up to the decision, but not determined by them. Free will is a brain capacity that is of course determined by neural activity, but the neural activity is no more deterministic than the weather is. In fact, I would postulate that our brains are even less deterministic than the weather. Call it wiggle-room, or elbow room, the nonlinearity of decision-making relegates the question of just how deterministic the brain really is to a (highly interesting!) academic debate: in practice, brains will always be less predictable than the weather, irrespective of any quantum effects playing a role or not. This modern, scientific concept of free will emphasizes that our freedom can of course not be absolute. Freedom is always a matter of degree, of shades of gray between the blacks and whites of determinism and stochasticity. In fact, this is precisely how such nonlinearities operate, by implementing deterministic and stochastic components to create phenomena that are neither fully deterministic nor completely stochastic. As we understand the deterministic components better, we get better at predicting nonlinear behavior, but the very nature of all of these systems fundamentally prevents fully accurate forecasts. In reality, we create robots with free will, we even start to understand the neurophysiological mechanisms by which neural processes become unpredictable, but Mr. Brooks writes in the NYT that because he doesn’t understand how the neurons are doing it, it must be magic.

For the life of me, I have no idea what is getting into people like Mr. Brooks who at least give off the very succinct impression that they fear that the human brain needs magic, or else we might one day understand it too well for our own good. Have they no respect for the lump of tissue between their ears? At least he gets a thorough bashing in the many of the comments and of course by the inimitable Neurocritic.

One of our graduate students might have just discovered the neural circuit that allows fly brains to decide which way to turn, even in a virtual environment without any cues. Now please excuse me while I go back to explaining away some magic by studying fly neurons.

Posted on June 20, 2013 at 19:30 8 Comments