neurodudes

Haim Sompolinsky has written an excellent book chapter on the scientific view of free will and choice, pulling in good ideas from physics and neuroscience along with contemporary philosophical commentary.

I think this chapter might be helpful for neuroscientists outside of the lab. Often a dinner table discussion has moved to the idea of “quantum consciousness” or “quantum free will”. Often, someone will mention Roger Penrose, who has become something of a poster boy for this idea that quantum indeterminacy (eg. Heisenberg’s uncertainty principle) is one possible way that free will is really free. And then, people look around and say, “Well, you’re a neuroscientist. Do we have free will?” (And that’s when I take another big drink or bite while I figure out something semi-coherent to say.)

Sompolinsky does a nice job of evaluating such claims (in the end, he says we cannot rule out the possibility that the brain is an indeterministic system but it seems unlikely) and provides nice scientific insight. In his view, it is far more likely that the brain’s apparent randomness (eg. individual cell spike rasters vary across repeated presentations of the same stimulus) is more simply explained by thermal noise (think of varying channel gating properties) and chaotic brain dynamics. (Recall, a chaotic system is still deterministic; it simply exhibits aperiodic behavior due to exquisite sensitivity to initial conditions. It is difficult to predict the long-term behavior of chaotic systems. The more we know the initial conditions in detail, the better our prediction.) On the other hand, he argues that the relevant length and time scales for neurons (micrometers and milliseconds) are far larger by many orders of magnitude than those of quantum noise. Chaos might amplify such quantum events, but this is far from being the simplest, most parsimonious explanation. Given the current level of neuroscience understanding, this is almost idle speculation. Regardless of the (in)determinacy of the world, Sompolinsky effectively argues against any non-physical, purely mental (ie. dualistic) agent of causation.

Thus, in sum, the world and our brains might not be determined but, even given that, there’s no reason to believe we have any causative ability to change things in the sense of traditional free will. These observations seem right on the mark to me. I hope they bring some insight for others. Or at least a way to fend off the dinner-table-free-will-conversation barrage of questions.

Jonathon Keats (no, not that one) has written a scorching review of neuro grad student Jonah Lehrer’s new book, Proust was a Neuroscientist.

I saw this somewhat more favorable review a few weeks in the NYT and was intrigued by the book. As an undergrad, I majored in cognitive science and English and, naturally, was fascinated by the cultural differences of academics in these disparate fields.

As in the Salon article, I also think attempts to unify the “two cultures” (ie. arts and sciences) are misguided. A work like Lehrer’s book (which I have not read) will need to work hard to “prove” its thesis and likely sound very forced. What can we really say about arts vs. sciences? For that matter, is it important to make value judgments on this topic? I’d say, no. We seem to have a natural urge to categorize our activities and then try to order them. Science is more worthwhile. Art is a more creative endeavor. Are these blanket generalizations productive?

But there is overlap between the two cultures and those regions seem more and more important to me. And I think neuroscience in particular has a lot to say here, too. If we know what makes good art good (in a scientific way), will we stop appreciating it or enjoying it? (This is similar to the idea that if someone told you free will was simply an illusion would the illusion be any less powerful than it is right now?) Often, the surprise of creative thought underlies the best science and the best art. Okay, there’s my attempt at a unification!

On a separate note, there certainly seems to be a hunger amongst the reading public for neuroscience books, despite our incomplete picture of how the brain works. For those frustrated with slow progress in research, maybe we should just go write a book.

Salon features an interview today with Steve Pinker and Rebecca Goldstein:

Proud atheists: Steven Pinker, Rebecca Goldstein interview | Salon Books

After reiterating the physicalist view of the mind, the article ends with this quote from Pinker (reminiscent of Marr’s levels of analysis):

[...] But just by looking at the brain itself, will you ever be able to understand the creative mind?

PINKER: I suspect not. In fact, the reason I’m not a neurobiologist but a cognitive psychologist is that I think looking at brain tissue is often the wrong level of analysis. You have to look at a higher level of organization. For the same reason that a movie critic doesn’t focus a magnifying glass on the little microscopic pits in a DVD, even though a movie is nothing but a pattern of pits in a DVD. I think there’s a lot of insight that you’ll gain about the human mind by looking at the whole human behaving, thinking and reporting on his own consciousness. And that might be true of creativity as well. It may be that the historian, the cognitive psychologist and the biographer working together will give us more insight than someone looking at neurons and brain chemistry.

I think the analogy with the DVD is disingenuous. In the case of the DVD, we know precisely how the low-level pits are combined to form the high-level representation (the movie). The system is not mysterious. To be fair, Pinker doesn’t say that neurobiology is always the wrong level of analysis. Maybe he would have been correct 50 or 100 years ago, but I think it’s clear now that neurobiology is on the path to providing a complete synthesis (certainly, with the help of cognitive psychology) that cannot be achieved without it.

The concept that the brain holds maps of the surface of the body in the primary sensory and motor cortex is a fascinating but well known fact to the field of neuroscience since the early work of Wilder Penfield. What is less broadly appreciated is the concept of “peripersonal space”. A new book by Sandra and Matthew Blakeslee describes peripersonal space in the following way:

The maps that encode your physical body are connected directly, immediately, personally to a map of every point in that space and also map out your potential to perform actions in that space. Your self does not end where your flesh ends, but suffuses and blends with the world, including other beings. [...] Your brain also faithfully maps the space beyond your body when you enter it using tools. Take hold of a long stick and tap it on the ground. As far as your brain is concerned, your hand now extends to the tip of that stick. [...] Moreover, this annexed peripersonal space is not static, like an aura. It is elastic. [...] It morphs every time you put on or take off clothes, wear skis or scuba gear, or wield any tool. [...] When you eat with a knife and fork, your peripersonal space grows to envelop them. Brain cells that normally represent space no farther out than your fingertips expand their fields of awareness outward, along the length of each utensil, making them part of you.

What I appreciate about this, besides the stretchy comic book characters that it makes me think about, is that it provides a powerful perspective to begin piecing together a mass of disparate neuroscience data, which the Blakeslee’s capitalize on.

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If there’s one lesson to be learned from almost 60 years of AI research it’s almost certainly to be skeptical of anyone who says they have found THE ANSWER to producing human-level intelligence from computers. Even in the face of this, however, I am intrigued by a new company’s approach to developing Artifical General Intelligence (AGI), a term which is meant to indicate Strong AI rather than Weak AI. That’s probably because its founder, Ben Goertzel, manages to skillfully walk the tightrope between staying conservative about how much they can realistically accomplish and still managing to inspire hope that their methodology has the potential to get close to AGI.

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Interview with Steve Grand on building human level artificial intelligence at Machines Like Us. Really interesting. Via Chris Chatham at (the excellent) Developing Intelligence.

In particular, MLU asks why his current project to create an android was done as a physical robot rather than as a simulation. The answer, that you can cheat too much in a simulation, is familiar to those from the Brooksian school of embodied intelligence. He says that simulations still aren’t good enough to provide the kinds of physical constraints, like gravity and friction, etc, that you get when building real robots .

However, with the availability of free 3D simulation environments that handle physics, like Breve, we are getting a lot closer. Building a robot within a simulation like this, particularly where you don’t modify the code of the the simulation environment itself, is a terrific way to balance the competing interests of keeping yourself honest and avoiding the painstaking mechanical engineering required to construct complicated robots. This kind of environment allows you to build a body with primary sensory systems and primary motor outputs in a similar fashion as one would with real robots.

Why there aren’t more who have adopted this kind of “in silico embodiment” philosophy I think is the result of taking Brooks’ a bit too seriously. Brooks idea of embodiment is very well founded, but back in the day when he first made those statements, there really were no good ways to simulate the physics of an embodied creature very faithfully. Today that is not the case. Moreover, building real physical robots is great if you have a lot of time, or an engineering team, but it’s a huge investment that distracts from the real problem of understanding the nature of intelligence. The fact that the world has extremely few labs that can make that investment is one of the many reasons there aren’t more serious strong AI researchers any more.

Update: Steve apparently received a few comments along these lines and replies.

The man had a normal job and is a married father of two children.

Nature news

Lionel Feuillet, Henry Dufour and Jean Pelletier. Brain of a white-collar worker. The Lancet, Volume 370, Issue 9583, 21 July 2007-27 July 2007, Page 262.

Science has a special online feature this week on behavioral science. One of the articles is a review by Paul Bloom and Deena Skolnick Weisberg (a fellow SymSys alum!) presents some interesting evidence about how dualistic ideas about mind/brain are present from an early age. They state:

Another consequence of people’s common-sense psychology is dualism, the belief that the mind is fundamentally different from the brain (5). This belief comes naturally to children. Preschool children will claim that the brain is responsible for some aspects of mental life, typically those involving deliberative mental work, such as solving math problems. But preschoolers will also claim that the brain is not involved in a host of other activities, such as pretending to be a kangaroo, loving one’s brother, or brushing one’s teeth (5, 17). Similarly, when told about a brain transplant from a boy to a pig, they believed that you would get a very smart pig, but one with pig beliefs and pig desires (18). For young children, then, much of mental life is not linked to the brain.

And,

For one thing, debates about the moral status of embryos, fetuses, stem cells, and nonhuman animals are sometimes framed in terms of whether or not these entities possess immaterial souls (20, 21). What’s more, certain proposals about the role of evidence from functional magnetic resonance imaging in criminal trials assume a strong form of dualism (22). It has been argued, for instance, that if one could show that a person’s brain is involved in an act, then the person himself or herself is not responsible, an excuse dubbed “my brain made me do it” (23).

The authors conclude that adult resistance to science is strongest in fields where scientific claims are contested by the society (that is, contested by non-science alternatives rather than by scientific uncertainty). They claim that this accounts for the difference in the United States (versus other countries with less vociferous advocacy of non-science) in the resistance to the central tenets of evolutionary biology and neuroscience.

I think this says something important about science education, namely that it should start earlier in life. And there’s no reason that neuroscience should be left as a “college-level” subject. I think modern neuroscience has progressed to the point where we can confidently teach some basics at a high-school or earlier stage. Judging from my own experiences, I think the desire to learn about neuroscience is certainly there in younger children.

The field of neuroscience naturally focuses its inquiry into neurons. This approach to understanding the brain by studying its parts has been thought to have a greater potential than that of psychology to understand how the brain works, a comment made by no less than Daniel L. Schacter, chair of Harvard’s Department of Psychology, in his book, The Seven Sins of Memory.

However promising the field has been thus far, even the most accomplished neuroscientists will admit that we still do not understand how the brain really works. I would submit that the current reductionist nature of neuroscience has shed much light on the dynamics of how neurons work, but has to a far lesser degree shed light on how neurons process information. The difference between these two lines of inquiry is important for making progress in understanding how the brain works.
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Entrepreneur-turned-cognitive neuroscientist Jeff Hawkins is distributing a “research release” of their experimental code base implementing his idea of hierarchical temporal memory described in his book, “On Intelligence”. Hawkins drew inspiration for the model from his own reading about the structure and function of the human neocortex and believes that it represents the foundation for developing intelligent machines.

Jeff explains this surprising move to open source the code for the Numenta Platform for Intelligent Computing (NuPIC) on the Numenta web site:

Why are we making NuPIC available now?

We have been contacted by dozens of researchers and scientists who are excited about HTM and by our work at Numenta. These people are anxious to work on HTM, are willing to be pioneers, and are willing to accept the uncertainty associated with a new technology. We are making our tools available so that these sophisticated developers can start building a community around HTM technology. NuPIC has been under development for 18 months, is pretty solid, and is well documented - including several examples to make it easy to get started - so we’re ready to open up to more developers, even while knowing that we do not yet have benchmarking data, and we cannot make guarantees about applicability to specific problems.

Here’s why Hawkins thinks that HTMs are new.

We have been covering Hawkins’ work for a while now. See these previous posts for more background info.

Neurodudes is actively soliciting code reviews of the newly released software. Is NuPIC the next big thing, or are you left feeling cold? Post your thoughts yourself using the instructions on the right-hand column, or let us know at contactus -AT- neurodudes.com!