I’m a fan of it because it is an open-access journal featuring a “tiered system” and more.  From their website:

The Frontiers Journal Series is not just another journal. It is a new approach to scientific publishing. As service to scientists, it is driven by researchers for researchers but it also serves the interests of the general public. Frontiers disseminates research in a tiered system that begins with original articles submitted to Specialty Journals. It evaluates research truly democratically and objectively based on the reading activity of the scientific communities and the public. And it drives the most outstanding and relevant research up to the next tier journals, the Field Journals.

I’m a big fan of the variety of specialty journals they have:

• Aging Neuroscience
• Behavioral Neuroscience
• Cellular Neuroscience
• Computational Neuroscience
• Enteric Neuroscience
• Evolutionary Neuroscience
• Human Neuroscience
• Integrative Neuroscience
• Molecular Neuroscience
• Neural Circuits
• Neuroanatomy
• Neuroenergetics
• Neuroengineering
• Neurogenesis
• Neurogenomics
• Neuroinformatics
• Neuromethods
• Neuropharamacology
• Neuroprosthetics
• Neurorobotics
• Synaptic Neuroscience
• Systems Neuroscience

I think he might be right that we can simulate the brain before we understand it, however.

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.

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.

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.

You’ll recognize the name Sandra Blakeslee from her co-authorship with Jeff Hawkins in On Intelligence and with V.S. Ramachandran in Phantoms in the Brain. This new book continues in the spirit of illustrating the broader significance of surprising findings in neuroscience. It covers a lot of recent neuroscience research, including mirror neurons, place cells and grid cells, the insular cortex and neuroprosthetics. For anyone looking to get the quick picture of these frontier research areas, this book serves as an excellent primer. It does an excellent job of making connections to socially relevant topics such as the secrets of athletic excellence, underlying causes of eating disorders and the modern obsession with plastic surgery. I have come to believe that neuroscience will eventually provide concrete explanations for the metaphors we use and the spooky phenomena we believe in but science cannot prove. Along those lines, this book does a great job of describing brain mechanisms that may underly paranormal phenomena like auras and out-of-body experiences.

One of my favorite parts is chapter six, a short chapter with a Phantoms in the Brain feel that presents some extremely jarring clinical examples of neurological problems potentially caused by body map disorders. It describes cases of individuals who want to have their limbs amputated because they feel like they don’t belong to them, individuals who no longer get feedback from their limbs as if they have disappeared, as well as cases of one woman who felt like she had three arms and three legs. That these cases exist are fascinating in their own regard; that there exists a systems-level conceptual framework with which we might understand the underlying causes for them is utterly incredible.

The implications of these ideas to AI are significant. What kinds of intelligent systems can we build by assuming that they have ego-centric representations of objects in their peripersonal space, or by assuming that their motor intentions are tickled by watching the movements of other creatures? The implications for computational neuroscience are also significant. What kind of system of neuronal processors is capable of producing cells that are sensitive to peripersonal space? What information must flow into those cells, and where is that information available from in the brain? Along what channels and using which “algorithms” does your brain map the visual information of a person moving their limbs to the motor areas that control your limbs? Perhaps I’ll be able to read about these things in the next Blakeslee neuroscience tour de force.

The Body Has a Mind of Its Own: How Body Maps in Your Brain Help You Do (Almost) Everything Better
by Sandra Blakeslee (Author), Matthew Blakeslee (Author)
Random House Publishing Group

(Full disclosure: Sandra Blakeslee and Random House kindly sent us a copy of the book to review before their release date…thanks guys!)

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.

This is best demonstrated in a recent talk that Goertzel gave at Google on his approach to AGI. His company, Novamente, has entered the interesting niche market of “creating intelligent agents for virtual worlds and MMOGs.” If you are surprised that a market exists for such a thing, you aren’t alone, but the company boasts a client list including “Northrop-Grumman, the NIH Clinical Center, the CDC, Global Health Exchange, CACI, Object Sciences Corporation, Zero Degrees, Think Passenger and [the] Electric Sheep Company.” The basic idea is to use the embodied intelligence approach in simulated environments to construct virtual agents that progress through stages of cognitive development.

After spending some time on Second Life (only to cancel my premium account after the unfortunate but inevitable gambling ban), I can almost see how a company might finance itself in the short term by selling Eliza-like virtual pets and automated shopkeepers to Second Life citizens (after all, Sony’s now defunct AIBO project managed to finance such an endeavor for real world virtual pets). What’s more interesting is that the advent of massively multiplayer virtual worlds provides a novel opportunity to access limitless amounts of training data from humans for a virtual agent..the kind of thing that researchers building real world robots have to recruit undergraduates to get. Taking advantage of this resource for the purposes of AI is a good idea, and the incentive structure of the company is such that incremental improvements in the intelligence of their agents ought to translate to greater profits. Anyone who figures out how to drive AI research with a short-term profit motive (rather than vague promises of long-term profit) gets my attention.

Goertzel’s presentation is notable for its modesty. He acknowledges the classic problems of the AI enterprise, like the habit of promising AI algorithms failure to scale up due to combinatorial explosion, and of AI presentations, like hiding inconvenient details behind complex Powerpoint presentations. Refreshingly, he makes fun of these bad patterns as cliches to reassure the audience that he wants to avoid falling into these traps. It pays off, and he wins my respect for doing so. He lays out some of the details of his architecture, but my attention is drawn more to his basic philosophy and approach more than anything else. He makes some interesting points about combinatorial complexity of AI programs, and, in the QA period, offers his views on competing architectures like that of Jeff Hawkins at Numenta.

The other thing I like about Novamente is that they sponsor a research institute called the Artificial General Intelligence Research Institute, whose goals are roughly the same as Novamente, but not for profit. Clearly there’s a conflict of interest here, but again, in the name of progress I’m willing to accept that. The institute is the organizing hub of Novamente’s ‘in silico embodiment’ virtual environment, AGISim, which is built on the Crystal Space 3D game platform and is open source. Unfortunately, real newtonian physics integration is still on the to do list, making AGISim more limited of a platform that Breve. But then again, AGISim is being built specifically as an environment to integrate with the Novamente Cognition Engine (their ‘brain’), and as such is already more customized for creating environments for cognitive agents.

My biggest critique of this approach is that Novamente doesn’t seem to be integrating enough of brain science into its work. This is revealed in Goertzel’s writings for the fringe journal, Dynamical Psychology, edited by Goertzel himself. The goals of the journal are quite good, to understand “the patterns by which psychological processes unfold through time [and] the emergent, persistent structures which arise as a consequence of this unfolding”. However, not being grounded in neuroscience leads Goertzel and others to describe psychological processes with impenetrable statements like the following:

There are elegant abstract-algebraic symmetries lurking within the social substructures of the self. The internal structure of the self may well be that of a tetrahedral mirrorhouse and related more complex packing structures; and the Fulleresque vision of an iterating dynamical system of adjacent tetrahedral mirrorhouses may well be an accurate model of critical aspects of the emergent cognitive dynamics of societies of social minds.

Nonetheless, I wish Goertzel and Novamente luck, and look forward to seeing what they can accomplish.

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.