neurodudes

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.

A patient who had been in a “minimally conscious state” for six years regained responsiveness after stimulation via electrodes implanted in the thalamus. Now he can “name objects on request, make precise hand gestures, and chew food without the aid of a feeding tube”.

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This study provides fMRI evidence that, after forgetting some memories, the brain has to work less hard.

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This isn’t news but is rather an interesting thing I learned today. There is a family with an inherited form of frontotemporal dementia. In this family, the onset of dementia occurred between 57-63 years of age. A study was done which did psychological tests on members of this family. It was found that young people (younger than 35) who carried the gene for the disorder had measurable frontal-executive dysfunction (whereas controls, young people in the same family who did not carry the gene, did not have dysfunction).

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A set of 6 subjects with bilateral damage to the ventromedial prefrontal cortex (VMPC) answered ethical questions in a way more consistent with utilitarian ethical philosophy than the control subjects. For example, they would be more willing to kill someone by pushing them off a bridge if that would save 5 other people. This supports the view that social emotions underly ethical judgments.

Michael Koenigs, Liane Young, Ralph Adolphs, Daniel Tranel, Fiery Cushman, Marc Hauser and Antonio Damasio.Damage to the prefrontal cortex increases utilitarian moral judgements. Nature. Published online 21 March 2007

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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!