neurodudes

No, not that.

Neurodudes reader Deanna Saunders from the Sloman lab at Brown wants survey participants for a brief cognitive psychology survey. I took it and I must say it was kind of fun. She tells me that it’s about the effects of decision making on learning. (I’ve got to say I always appreciate the surveys that give you a little debriefing after the survey explaining some of the stimuli and the intended effects. Sadly, this survey doesn’t seem to have that.) Here it is for those of you with a few extra minutes for science: Click here for the survey. Better than the Colbert bump is the Neurodudes bump!

The Atlantic‘s Joshua Shenk has a fascinating story about a long-running study, started in the 1930s (!), that attempts to discern what makes people happy in life. The study has collected extensive data on subjects over a 70 year period. I couldn’t stop reading the article… what an amazing dataset. But, before I say more about that, here is Shenk’s synopsis of a single case file (ie. actual data) from the study:

Case No. 158

An attractive, amiable boy from a working-class background, you struck the study staff as happy, stable, and sociable. “My general impression is that this boy will be normal and well-adjusted—rather dynamic and positive,” the psychiatrist reported.

After college, you got an advanced degree and began to climb the rungs in your profession. You married a terrific girl, and you two played piano together for fun. You eventually had five kids. Asked about your work in education, you said, “What I am doing is not work; it is fun. I know what real work is like.” Asked at age 25 whether you had “any personal problems or emotional conflicts (including sexual),” you answered, “No … As Plato or some of your psychiatrists might say, I am at present just ‘riding the wave.’” You come across in your files as smart, sensible, and hard-working. “This man has always kept a pleasant face turned toward the world,” Dr. Heath noted after a visit from you in 1949. From your questionnaire that year, he got “a hint … that everything has not been satisfactory” at your job. But you had no complaints. After interviewing you at your 25th reunion, Dr. Vaillant described you as a “solid guy.”

Two years later, at 49, you were running a major institution. The strain showed immediately. Asked for a brief job description, you wrote: “RESPONSIBLE (BLAMED) FOR EVERYTHING.” You added, “No matter what I do … I am wrong … We are just ducks in a shooting gallery. Any duck will do.” On top of your job troubles, your mother had a stroke, and your wife developed cancer. Three years after you started the job, you resigned before you could be fired. You were 52, and you never worked again. (You kept afloat with income from stock in a company you’d done work for, and a pension.)

Seven years later, Dr. Vaillant spoke with you: “He continued to obsess … about his resignation,” he wrote. Four years later, you returned to the subject “in an obsessional way.” Four years later still: “It seemed as if all time had stopped” for you when you resigned. “At times I wondered if there was anybody home,” Dr. Vaillant wrote. Your first wife had died, and you treated your second wife “like a familiar old shoe,” he said.

But you called yourself happy. When you were 74, the questionnaire asked: “Have you ever felt so down in the dumps that nothing could cheer you up?” and gave the options “All of the time, some of the time, none of the time.” You circled “None of the time.” “Have you felt calm and peaceful?” You circled “All of the time.” Two years later, the study asked: “Many people hope to become wiser as they grow older. Would you give an example of a bit of wisdom you acquired and how you came by it?” You wrote that, after having polio and diphtheria in childhood, “I never gave up hope that I could compete again. Never expect you will fail. Don’t cry, if you do.”

What fascinates me is the absolute novelty of this kind of data. Normally, when someone relates their “life story,” we willingly participate in something of a shared lie. Both listener and story-teller know that the “life story” is being told in hindsight: Memory is not perfect and humans sometimes (often, perhaps) add meaning and create unifying themes in stories where they may be none. We emphasize the good parts and try to forget the not-so-good parts. In a sense, history recounted is never truly veridical but instead tainted with everything that happened after. Which is precisely why the availability of an objective history than spans an entire lifetime (or, as objective as possible) of both a qualitative (interview) and quantitative (medical) nature is so novel.

As you might expect, the data is confusing and hard conclusions are not easy to come by. There are however some tangible factors that seemed to correlate/predict success in life, which I’ve included after the jump. (more…)

Although I’ve been a longtime fan of Ramachandran’s excellent book Phantoms in the Brain, this TED talk is like a compressed summary of the highlight’s of his research. He’s a great speaker and he covers in 20 minutes my two favorite examples in the book (Capgras delusion and mirror treatment for phantom limb syndrome). Perhaps the best part of the talk is that, after listening to it, I was convinced more than ever before of the statistical nature of sensory perception (ie. the brain attempts to find the most likely explanation for sensory observations) and the integrative nature of central processing of multiple modalities. 

Atul Gawande also recently wrote a New Yorker article about treating phantom itch with Ramachandran’s mirror box. I found this part of Gawande’s article on statistical inference in perception most interesting:

You can get a sense of this from brain-anatomy studies. If visual sensations were primarily received rather than constructed by the brain, you’d expect that most of the fibres going to the brain’s primary visual cortex would come from the retina. Instead, scientists have found that only twenty per cent do; eighty per cent come downward from regions of the brain governing functions like memory. Richard Gregory, a prominent British neuropsychologist, estimates that visual perception is more than ninety per cent memory and less than ten per cent sensory nerve signals. When Oaklander theorized that M.’s itch was endogenous, rather than generated by peripheral nerve signals, she was onto something important.

I’m not familiar with this field but I wonder if anyone has tried to quantify what percent of our conscious experience that we normally believe to be 100% due to sensory input is actually recall from memory/inference based on past observation. Also, can this percentage adaptively change? Perhaps there are situations where the brain chooses to rely more heavily on memory and other cases where it relies more on primary sensory input.

Nature is reporting on potential flaw in multiple imaging (fMRI) studies of social neuroscience. Ed Vul (a graduate student in my dept) and colleagues have a paper in press that says that many of the high correlations between brain regions and social behavior are implausible, given the inherent variability/noise in fMRI. Furthermore, based on a survey of methods from individual investigators, they created a list of papers that commit, in their view, a statistical mistake (non-independence). Naturally, the authors named in the paper aren’t happy and, according to the Nature article, several rebuttals are in the works. At the very least, to my non-expert eyes, this seems like an important discussion to have about data analysis and methodology.

Stanislas Dehaene, Véronique Izard, Elizabeth Spelke, and Pierre Pica. Log or linear? Distinct intuitions of the number scale in Western and Amazonian indigene cultures. Science, 320(5880):1217–1220, May 2008.

The Mundurucu are an indigenous culture whose language does not contain exact words for numbers above 5. Dehaene, Izard, Spelke, and Pica basically gave subjects an empty horizontal line and then gave them a bunch of numbers and told them to place the numbers where they belong on the line (the line was not entirely empty; the left and right hand sides were labeled with a small number and a big number).

Western adults tend to place the numbers linearly, whereas the Mundurucu tend to place them logarithmically. Western children also place them logarithmically, and even Western adults place them logarithmically if the numbers are presented as larger numbers of dots (10-100) or if they are presented as tones.

This suggests that there is an innate logarithmic representation of number which is used to populate the number line, but that with training a linear representation can be created.

From March. Actually, the topic of the article is Dehaene, but it talks about some studies too. Excerpts after the break, interspersed with hyperlinks to citations that I looked up.

http://www.newyorker.com/reporting/2008/03/03/080303fa_fact_holt?currentPage=all

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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.