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2 More Reasons Why Big Brain Projects Are Premature

The views expressed are those of the author and are not necessarily those of Scientific American.


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In a recent post I raised doubts about two big brain-mapping projects, one in the U.S. (to which Obama just committed $100 million) and the other in Europe. I suggested that these projects might be premature, given our basic ignorance of how brains make minds. I’d like to provide two addendums to my post, which provoked some blowback, including a rant from Henry Markram, conceiver of Europe’s Human Brain Project. (I responded to Markram in a Post-postscript.)

First addendum: Some critics of my criticism pointed out that my arguments against the brain initiatives could be arguments for them. In other words, big, coordinated programs could help neuroscience advance not only by boosting funding but also by encouraging sharing of data and theories, development of common methods and terminology and so on. I asked for a response to this point from a critic of the U.S. brain initiative, Donald Stein, a neuroscientist at Emory University. He replied:

“We won WWII with a big organized (more or less) collaborative project. So, some of them do work.  It’s really about the concepts and paradigms that underlie this particular project. This notion of mapping the circuitry goes back to the middle of the 19th century, and the localizationist paradigm these folks are applying is basically the same albeit with some better equipment. They completely ignore the multiple levels of organization, signaling and functions that are ever changing—not to mention no mention of the tremendously important role of all the trillions of glial cells also hanging around in the brain with no specificity of connections but with huge effects on brain dynamic.  So, it’s not about big science, its about good (or bad) science. As Americans we love to think we can just throw technology at all the worlds problems and all will be well.  But at its best, the technology should follow the concept(s) and not the other way around. Hope this helps, Don.”

Second addendum: My Scientific American colleague Gary Stix just blogged on a new study, in Nature Reviews Neuroscience, that casts doubt on the reliability of published neuroscience findings. The study’s seven authors include epidemiologist John Ioannidis, who over the past decade or so has uncovered profound flaws in peer-reviewed reports in biomedicine and other fields. (See Ioannidis’s 2011 Scientific American article “An Epidemic of False Claims.”) The report by Ioannidis and other researchers (the lead author is Katherine Button of the University of Bristol) claims that many neuroscience results lack statistical significance and hence may be false or unreplicable.

The report states that “the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful. Improving reproducibility in neuroscience is a key priority and requires attention to well-established but often ignored methodological principles.”

This finding bolsters the argument that the Big Brain Projects–by funneling precious resources toward paradigms supported by flimsy findings–are premature.

Image: http://www.rsc.org/chemistryworld/

 

John Horgan About the Author: Every week, hockey-playing science writer John Horgan takes a puckish, provocative look at breaking science. A teacher at Stevens Institute of Technology, Horgan is the author of four books, including The End of Science (Addison Wesley, 1996) and The End of War (McSweeney's, 2012). Follow on Twitter @Horganism.

The views expressed are those of the author and are not necessarily those of Scientific American.





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  1. 1. jipkin 3:26 pm 04/10/2013

    what.

    1) Donald Stein misrepresents what the project is about – it’s not “mapping circuitry”. That’s anatomical connectomics. This is about developing tools for measuring activity from large numbers of neurons simultaneously – the precise techniques we need to bridge the gap between the cell-scale world and the higher levels of organization. See Michael Carroll’s excellent dissection of Stein’s views here: http://nucambiguous.wordpress.com/2013/04/08/the-moon-is-not-made-of-cheese-and-other-hypotheses/

    2. That meta-analysis focuses on studies of fMRI and “animal models” which seems to mean behavior. I skimmed it and saw nothing about the kinds of studies that would come from the technologies being proposed in BRAINI. (nothing on systems, physiology, etc).

    Link to this
  2. 2. tuned 6:09 pm 04/10/2013

    It all begs the question (to me):
    Is this future the ultimate death of privacy?
    Can it and will it eventually lead to the “hive mind” society?
    I would lie to anyone I suspected of stealing my thoughts for the rebellion of it.
    Of course I see the short term benefits for the paralyzed, etc.
    I wouldn’t want to be around for the final act of the play however.

    Link to this
  3. 3. nucAmbiguous 6:15 pm 04/10/2013

    As @jipkin mentions I have addressed several of Dr. Stein’s arguments in my blog. As I talk about in detail in my recent post, the argument that contemporary neuroscience (in particular, systems neuroscience, which is what is proposed in the BRAIN project) is somehow conceptually shackled by mindless 19th century localizationism is nonsense. Stein writes:

    “They completely ignore the multiple levels of organization, signaling and functions that are ever changing.”

    This claim that scientists who do circuit mapping ignore other levels of organization is so transparently wrong that I have to question Dr. Stein’s familiarity with the literature. There’s Steriade’s work on how thalamocortical circuits (and cellular properties) underlie seizure dynamics, Yuste’s work on different cortical inhibitory networks and cell phenotypes, McCormick, Connors, Sherman (yes, even Partha Mitra), and on and on and on. These researchers bridge different levels of analysis from individual ion channels to EEG rhythms. Perhaps individual papers are often constrained to one or two levels of brain organization, but the idea that the scientists associated with the BRAIN project ignore the other levels is easily falsified by actually reading their papers (check those of the senior researchers on the new planning committee).

    Second, the notion that neural circuits are so plastic as to be completely unmappable is also contradicted by evidence from hundreds of studies. Neural circuits are reasonably stable over the _behaviorally_relevant_ time scales that can be studied in the lab. Plasticity over longer time scales is not an argument against the BRAINI methods, but an argument for them, since they can be used to study exactly this sort of change.

    Third, yes, glia are important in brain function. They have a role in neurotransmitter processing and maintaining ion homeostasis. They likely have a role in large scale dynamic processes like seizures, and obviously in brain injury. Nonetheless, there is little evidence that glia play a _specific_ role in the _computational_ and _information_processing_ functions of the brain (about which the BRAIN project is concerned). Dr. Stein is right in a sense in pointing out that the role of glia has been somewhat neglected in the past, but if he wants to make the claim that glia are relevant to the questions posed by the BRAINI, then he should provide some references.

    So, yes, big science should be good science, and aside from some overselling on the clinical relevance issue, the BRAIN Initiative is important and timely.

    As @jipkin mentions, I have many posts on the BRAINI/BAM project that explore these issues in detail. I’ll repeat the link here:

    http://nucambiguous.wordpress.com/2013/04/08/the-moon-is-not-made-of-cheese-and-other-hypotheses/

    Link to this
  4. 4. Mythusmage 7:47 pm 04/10/2013

    Any project, regardless of funding, only works when you know what you’re doing.

    Link to this
  5. 5. tim333 8:30 pm 04/10/2013

    I guess it’s partly a question of value for money, whether it’s worth blowing 1bn or 4bn on the projects. In the case of Markram’s European project I think it’s quite easy to justify. 1bn euros between 500m european is 2 euros a head or the price of one coffee or similar. Already the project has produced enough pretty simulations and one possible real scientific insight to justify a coffee in my eyes. (http://actu.epfl.ch/news/blue-brain-project-accurately-predicts-connections/). And it seems to makes sense to have some sort of computer system to bring together the research.
    The US project is a bit less clear as they don’t seem to have figured what they’re actually planning to do.

    Link to this
  6. 6. zstansfi 10:30 pm 04/11/2013

    Well thank you again John, you’ve just provided more evidence for why your reasoning regarding large neuroscience projects is flawed. Previously you argued that we should first understand the brain better, then work on projects that would give us the tools to understand the brain better. Now you are arguing that because a great many neuroscience studies how low statistical power (almost entirely because they are too small) that therefore we should avoid promoting large collaborative neuroscience projects!

    Just brilliant. Next time read the paper and think about it for a moment before posting your 2 cents.

    Or maybe you are a secret fan of these large neuroscience projects after all, and this criticism is just a calculated enterprise to send the true critics down the wrong path?

    Like many others I blogged this most recent report (http://neuroautomaton.com/smells-like-neuroscience/).

    For those who have access I full recommend that you read the original paper, which is quite accessible and informative so long as you understand basic statistics (http://www.nature.com/nrn/journal/vaop/ncurrent/full/nrn3475.html). It’s also been discussed by others all over the web who don’t feel the need to jump to derisive criticisms regarding unrelated neuroscience projects.

    Link to this
  7. 7. zstansfi 10:52 pm 04/11/2013

    Also, with respect to Stein’s comment, he argues that the US project is:

    a) locationist
    b) neural connections are in constant flux
    c) glial cells move

    Really only the last criticism appears to hold much water.

    The current project is most certainly not “locationist” in the 19th century sense, which was pretty much about mapping specific functions to specific brain regions (often not even the right brain regions). Instead, it’s about mapping certain functions to distributed neurons (i.e. not locationist), but I don’t see why the project needs to be limited to a static picture as Stein appears to argue. The connections and patterns of neuronal activity may be in flux, that is to say, they are dynamic and constantly changing, but not to the point where we cannot hope to identify general patterns. In fact, it’s obvious that some highly consistent patterns exist: many large brain structures tend to be highly specialized (e.g. sensory cortices, motor areas, subcortical structures) and most other areas have fairly consistent functional roles at some level. Moreover, the individual connections within these structures may be highly plastic, but it’s very unlikely this plasticity means that most neurons are completely remapping their connections over very short time scales (otherwise, how would large brain regions retain consistent functions?). Then again, given vague Stein’s comment is it’s hard to guess whether he’s making the spurious point I address above, or something much more nuanced which is not readily apparent (and therefore, isn’t really an argument).

    The final point on the role of glia may be important. Glia cells tend not to be electrically excitable, and the US project is mostly about developing techniques to record electrical changes from individual cells on a massive scale. On the other hand, if we could develop these techniques by using nanotechnologies then it might be feasible to develop similar techniques in parallel to record changes in calcium ion concentrations or other glial signalling molecules.

    Regardless, the criticisms all seem to be off base. The biggest problems instead are the technical hurdles: is it possible to make thousands of nanorobots which can record from individual neurons in a live brain? Will other worthy projects lose their funds as a result? If this most recent study on poor power in neuroscience research is correct, then the second point may not be an issue: just redirect funds from the people conducting poor research. Thanks again for point out this excellent selling point for the BRAIN project :)

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  8. 8. Chryses 11:52 am 04/13/2013

    @6 zstansfi

    “redirect funds from the people conducting poor research.”

    If this most recent study on poor power in neuroscience research is correct, why should these redirected funds remain within the domain where the poor research is being done: Neuroscience?

    No sense it pouring more money down an experimental rathole where “the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful.”

    http://www.nature.com/nrn/journal/vaop/ncurrent/abs/nrn3475.html

    Link to this
  9. 9. marclevesque 7:26 pm 04/16/2013

    I hope the work done under the US project keeps realistic goals in mind, and I think that might be a given.

    If I’m worried, and I’m seeing inklings, it’s about the temptation to promote the project using wild speculation about where it might lead us. Of course speculation is ok, it’s just a question of being reasonable, and being reasonable about who and how that is decided.

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  10. 10. zstansfi 2:44 am 04/18/2013

    It looks like SciAm nuked by first comment. I will state it again.

    John Horgan is mis-representing this most recent paper in support of an unreasonable position. I have read the paper, so I think it’s fair to comment upon.

    If statistical power in neuroscience studies is indeed low, and this poor power is largely due to small study/sample sizes, then this suggests money would be better spent supporting large-scale collaborative projects like BRAIN which may be more capable of collected appropriately large samples of data. If Horgan had read the study he quotes, he should have understood this fact.

    (Also, that should answer Chryses’ question.)

    Link to this
  11. 11. Doublefrost 10:03 pm 05/14/2013

    Let me get this straight. This buffoon thinks that because we don’t understand how the brain works to any real detail, we should make no effort into figuring out how the brain works to any detail. BRILLIANT. By that GENIUS reasoning, we never should have mapped the human genome. After all, we didn’t know what went where. No need to find out until we already do.

    I’m going to spell this out in terms such an EMINENT mind can comprehend. If neuroscience is failing in ignorance, it makes it MORE important to establish it on a more secure scientific footing.

    Link to this

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