Category Archives: Neuroscience

Neuroscience, Popularization

Brain Damage and Journalism

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Dan Hurley writes of Katherine P. Rankin’s neurological research on sarcasm,

To her surprise, though, the magnetic resonance scans revealed that the part of the brain lost among those who failed to perceive sarcasm was not in the left hemisphere of the brain, which specializes in language and social interactions, but in a part of the right hemisphere previously identified as important only to detecting contextual background changes in visual tests.

That’s from a New York Times piece, “The Science of Sarcasm (Not That You Care),” 3 June 2008. The abstract for Rankin et al.‘s presentation says, in part,

This study provides lesion data suggesting that the right posterior temporal lobe and dorsomedial frontal cortex are associated with recognizing and interpreting sarcastic irony using paralinguistic vocal and facial cues, consistent with functional imaging research examining neural correlates of voice prosody, facial emotion recognition, and perspective taking.

Trust the alchemy of science journalism to turn a result consistent with prior research into a great surprise. As Vaughan Bell points out, by the early 1980s people had already found out that damage to the brain’s right hemisphere can cause “disorders of affective language,” i.e., problems with recognizing emotion in speech. More recently, Shamay-Tsoory et al. (2005) found that lesions in the ventromedial section of the right prefrontal cortex impaired test subjects’ abilities to handle tasks which required understanding sarcasm.

This is the sort of gaffe which makes neurocurmudgeons file a story under “chaff” instead of “wheat.” I wonder: can fMRI detect a cortical lesion which makes all interesting and worthwhile research be perceived as revolutionary? The problem is not just restricted to neuro-journalism, of course — revolution disease is a general trope, right up there with “Think of the children!” and “David vs. the Scientific Goliath.” One begins to appreciate why Eric Roston, author of The Carbon Age (2008), said of his research practices, “I wanted to avoid secondary literature, media,” even though this meant a masochistic journey through peer-reviewed articles.

As for the research itself. . . . To my knowledge (and that of the Neurocritic), Rankin et al.‘s results have not yet appeared in a journal, only at an American Academy of Neurology conference, so pickings are as yet rather thin. No doubt more details will be available anon.

Evolution, Neuroscience, Plectics, Video

Genetics of Brain Evolution

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Even buried as I am under a stack of PDFs talking about PDEs, I would be remiss if I didn’t point out some juicy videos describing actual, factual cutting-edge science, namely the talks from Rockefeller’s recent evolution symposium. I’m currently in the middle of Bruce T. Lahn’s (U Chicago) talk, “Probing Human Brain Evolution at the Genetic Level.” Click here and scroll down to find the link. What could be more appropriate for an elitist bastard than an explanation of genes which control brain size?

(Thanks go out to Abbie.)

Neuroscience, Quantum mechanics, Statistical mechanics, String Theory

An Unusual Occurrence

So there I was, quietly standing in Lobby 10, queuing to buy myself and a few friends advance tickets to Neil Gaiman’s forthcoming speech at MIT, when a strange odor proturbed onto my awareness. “That’s odd,” thought I, “it smells like backstage at my high school’s auditorium. [snif snif] Or the bathroom at Quiz Bowl state finals. . . And it’s not even 4:20. Something very unusual is going on, here on this university campus.”

I became aware of a, well, perhaps a presence would be the best way to describe it: the sort of feeling which people report when their temporal and parietal lobes are stimulated by magnetic fields. Something tall and imposing was standing. . . just. . . over. . . my. . . right. . . shoulder! But when I turned to see, I saw nothing there.

Feeling a little perturbed, I bought my tickets and tried to shrug it off. Not wanting to deal with the wet and yucky weather currently sticking down upon Cambridge, I descended the nearest staircase and began to work my way eastward through MIT’s tunnel system, progressing through the “zeroth floors” of the classroom and laboratory buildings, heading for Kendall Square and the T station. Putting my unusual experience in the ticket queue out of my mind, I returned to contemplating the junction of physics and neuroscience:

“So, based on the power-law behavior of cortical avalanches, we’d guess that the cortex is positioned at a phase transition, a critical point between, well, let’s call them quiescence and epileptic madness. This would allow the cortex to sustain a wide variety of functional patterns. . . but at a critical point, the Wilson-Cowan equations should yield a conformal field theory in two spatial dimensions. . . .

“But if you reinterpret the classical partition function as a quantum path integral, a field theory in 2D becomes a quantum field theory in one spatial and one temporal dimension. And the central charge of the quantum conformal field theory is equal to the normalized entropy density. . . so we should be able to apply gauge/gravity duality and model the cortex as a black hole in anti-de Sitter spacetime —”

Suddenly, a tentacle wrapped around my chest, and constricted, and pulled, and lifted — not up, but in a direction I had never moved before. Like a square knocked out of Flatland, I had been displaced.
Continue reading An Unusual Occurrence →

Neuroscience, Transhumanism

Transhuman Science Begins Today?

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A while back, we noted an interesting exchange which Neil Shubin had with Stephen Colbert on The Colbert Report.

COLBERT: If I used to be a fish, and then I was a monkey, and now I’m a man, then what’ll be next?

SHUBIN: That’s a good question, ’cause we humans are actually now controlling our own evolution. So, if you’re worried about steroids in baseball now, come back in twenty-five years, because our technologies are fundamentally going to change our bodies. It’s gonna change how we work; medications are going to change how our bodies actually function and so forth. So really I think if you come back, we’re going to be sort of a product of technology and biology.

COLBERT: So you’re saying we’re wresting the steering wheel away from Darwin?

SHUBIN: I’m afraid with our ability to generate new technologies, essentially we are.

COLBERT: Can we turn ourselves back into fish? ‘Cause I’d love to be a shark.

These things have a way of becoming relevant sooner than we’d think. Bora Zivkovic and Jonathan Eisen report on an interesting and, for some, disturbing development from the National Institutes of Health:
Continue reading Transhuman Science Begins Today? →

Information Theory, Neuroscience

Aaronson on Turing, Gödel and Searle

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Computer-science guru Scott Aaronson has begun to put lecture notes for his “Great Ideas In Theoretical Computer Science” course online. (That’s 6.080 in MIT-speak: words are for the weak.) Prepared by the students and edited by the instructors, the notes are terse but clear and enjoyable. I particularly like lecture 6, “Minds and Machines,” of which the following is a taste:

We already established that no Turing Machine exists can solve the halting problem. If we had a proof system that could analyze any Turing machine and prove if it halted or did not halt, we could use this system to solve the halting problem by brute force (also known as the “British Museum algorithm”) by trying every possible string that might be a proof. You would either terminate and find a proof that it halts or terminate and find a proof that it doesn’t halt. If this proof system was sound and complete, it would violate the unsolvability of the halting problem. Therefore, there is no such sound and complete proof system.

I also like this bit:
Continue reading Aaronson on Turing, Gödel and Searle →

Favorites, Neuroscience, Plectics, Statistical mechanics

Physics on the Brain, Part 1

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Blogging on Peer-Reviewed ResearchCan physics tell us about ourselves?

To phrase the question more narrowly: can the statistical tools which physicists have developed to understand the collective motion of large agglutinations of particles help us figure out what our brains are doing?

If Jack Cowan and his colleagues are correct, ideas from statistical physics can tell us important facts about our own brains. By studying the recurring motifs of hallucinations, we can construct a geometry of the mind.

"Honeycomb" form constant generated by marijuana
“Honeycomb” form constant,
from Bresloff, Cowan et al. (2002)It’s hard to imagine any sort of regularity in a phenomenon as eccentric as visual hallucinations. Our culture is brimming with psychedelia, music and art produced “under the influence” of one or another infamous chemical. Yet the very fact that we can label artwork as “psychedelic” suggests that the effects of those mind-bending substances have a certain predictability. In the 1920s, long before the days of review boards and modern regulations for human experimentation, the neurologist Heinrich Klüwer ingested mescaline and recorded his observations. He reported visual hallucinations of four distinct types, which he called “form constants.” These form constants included tunnels and funnels, spirals, honeycomb-like lattices and cobweb patterns. Similar structures have been reported with other drugs, like LSD; these same form constants also appear during migraines, in “hypnogogic” (falling asleep) and “hypnopompic” (waking up) states, when pressure is applied to closed eyes, and even in ancient cave paintings.

If the same hallucinatory images appear from many causes, might they be indicative of some more general property of brain structure?
Continue reading Physics on the Brain, Part 1 →

Neuroscience, Transhumanism, Video

Kurzweil’s Predictions for 2009

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Apropos an announcement from the AAAS annual meeting, Steve Novella ponders the task of reverse-engineering the human brain. For those of us who share a materialistic view of the brain — i.e., for people who subscribe to actual science instead of woo — this task is likely to seem possible in principle, although daunting in practice. If the mind is the activity of the brain, and a finite number of genes can direct the growth of a brain in a finite amount of time, and the molecules which make up the brain are being exchanged in and out all the time anyway, it’s reasonable to speculate that we’ll be able to mimic the process in another medium. Novella argues that the “software” part of this task will be harder than the “hardware” side:

Sure, we may run into unexpected technological hurdles, but so far we have been able to develop new approaches to computing technology to keep blasting through all hurdles and keep Moore’s Law on track. So while there is always uncertainty in predicting future technology, predicting this level of computer advancement at the least can be considered highly probable.

The software extrapolation I think is more difficult to do, as conceptual hurdles may be more difficult to solve and may stall progress for a undetermined amount of time.

Broadly speaking, I agree. The exact amount of processing power needed to implement the brain in a Linux box is as yet unknown; it depends on things like the complexity of an individual synapse, and how much data is required to represent the state of a neuron. Then, too, for every hardware advance on Moore’s side of the ledger, Gates is there to bloat the software by a corresponding amount, and the applications of computer technology which have most radically affected life in recent years have depended not on raw cycles-per-second, but on networking and mass storage, neither of which necessarily improves at the same rate as processor speed.

Ray Kurzweil may be the most famous evangelist of the view that explosive increases in computer power will give us artificial intelligence on a par with our own in the near future. He has elaborated upon this idea in several books, a couple of which I used to have on my shelf; a commenter at NeuroLogica, Sciolist, still has The Age of Spiritual Machines (1999) close at hand.

Kurzweil claims that man’s merger with machine is inevitable, because the pace of evolution has been increasing exponentially — when we reach the edge of biological evolution, we must transition into artificial substrates so that can continue traveling up that exponential curve into binary godliness. This, he predicts, is inevitable. That’s at least a misreading of the theory of evolution; I’d argue it’s also a bit kooky.

Indeed, Kurzweil’s attempts to anchor his “Law of Accelerating Returns” in geological deep time are singularly silly, to steal PZ Myers’ phrase. They rely upon condensing multiple historical events into single data points to get a pretty curve, and instead of reflecting any deep truth about evolutionary processes, the curve you get reveals a recentist bias — the “proximity of the familiar.”

I recall that bothering me when I read the book, eight or so years ago, but eight years have gone by since then, making my memory only slightly more reliable than that of a HAL 9000 unit being fed a tapeworm. Thus it was with surprise and glee that I read Sciolist’s recounting of the predictions Kurzweil makes for one decade after the book’s publication, 2009:
Continue reading Kurzweil’s Predictions for 2009 →

BPSDB, Evolution, Neuroscience, Pseudoscience

Panglossing Over the Dirty Bits

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BPSDBThe evilutionary superscientist P-Zed has just finished debating a horrid simpleton (i.e., a professional creationist) on talk radio. Being a professor, P-Zed knew to read up in advance, which in this case was a laugh riot in itself, because it meant reading his opponent’s book, What Darwin Didn’t Know. One chapter, “Purposeful Design,” argues (among other things) that the sexual organs of the human female were designed to maximize the pleasure of the missionary position.

Yes, it’s another entry in the department of “you couldn’t make this up if you tried.” Better still, for my money, is this bit:
Continue reading Panglossing Over the Dirty Bits →

Network theory, Neuroscience, Plectics

In Happier News, the ArXivotubes

Luciano da Fontoura Costa, “Communities in Neuronal Complex Networks Revealed by Activation Patterns” (arXiv:0801.4684):

Recently, it has been shown that the communities in neuronal networks of the integrate-and-fire type can be identified by considering patterns containing the beginning times for each cell to receive the first non-zero activation. The received activity was integrated in order to facilitate the spiking of each neuron and to constrain the activation inside the communities, but no time decay of such activation was considered. The present article shows that, by taking into account exponential decays of the stored activation, it is possible to identify the communities also in terms of the patterns of activation along the initial steps of the transient dynamics. The potential of this method is illustrated with respect to complex neuronal networks involving four communities, each of a different type (Erdös-Rény, Barabási-Albert, Watts-Strogatz as well as a simple geographical model). Though the consideration of activation decay has been found to enhance the communities separation, too intense decays tend to yield less discrimination.

The “simple geographical model” is one I’ve played with myself, since it’s so easy to implement (and serves as a null hypothesis for some problems of interest). Throw [tex]N[/tex] nodes into a box of [tex]d[/tex] dimensions, and connect two nodes if they are closer than some fixed threshold. In this case, the box was 2D, but a 3D version is just as easy to implement.

Group Theory, Neuroscience, Topology

On the arXivotubes

Michael Schnabel, Matthias Kaschube, Fred Wolf, “Pinwheel stability, pattern selection and the geometry of visual space” (arXiv:0801.3832).

It has been proposed that the dynamical stability of topological defects in the visual cortex reflects the Euclidean symmetry of the visual world. We analyze defect stability and pattern selection in a generalized Swift-Hohenberg model of visual cortical development symmetric under the Euclidean group E(2). Euclidean symmetry strongly influences the geometry and multistability of model solutions but does not directly impact on defect stability.

Note to self: file alongside Bressloff, Cowan et al. for future reference.

Neuroscience, Pseudoscience, Quantum mechanics

The Unbinding Problem

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We human folk are pretty good at taking information from different sensory channels and combining it into unified impressions. When I watch a video recording of Richard Feynman, for example, my optic nerves carry a flood of data pulses, signals which somehow arrive in my brain and sync up with the voice which sounds like a Brooklyn gangster (but which actually came from Far Rockaway, of course). A unified whole then emerges, without my conscious effort.

Like they’ve done with all the other odd aspects of brain function, people have invoked quantum mechanics to “explain” this: the mind is mysterious, quantum physics is mysterious, and so the two must be related. Only your blind devotion to linear, Western, patriarchal science prevents you from seeing the Truth! (Oddly enough, the Oprah–Chopra-woo crowd never seem to remark on how the original developers of quantum physics were, almost all of them, White Males who are now Dead.) The “binding problem” is no exception.

However, as both Max Tegmark and Ray F. Streater have pointed out, the proponents of what we might call “quantum binding” — Henry Stapp in particular — fail to consider that correlations are perfectly possible in classical physics. The invocation of quantum physics is only a maladroit solution to a non-problem. In Tegmark’s words,

For instance, oscillations in a guitar string are local in Fourier space, not in real space, so in this case the “binding problem” can be solved by a simple change of variables. As Eddington remarked [77], when observing the ocean we perceive the moving waves as objects in their own right because they display a certain permanence, even though the water itself is only bobbing up and down. Similarly, thoughts are presumably highly non-local excitation patterns in the neural network of our brain, except of a non-linear and much more complex nature.

Now, a patient has turned up in whose brain binding does not occur. G. Lee and H. B. Coslett write of the patient “K.E.,”

He was unable to report more than one attribute of a single object. For example, he was unable to name the color of the ink in which words were written despite naming the word correctly. Several experiments demonstrated, however, that perceptual attributes that he was unable to report influenced his performance.

K.E. had suffered stroke damage to his parietal lobes on both sides of his brain, or in technical terms, “bilateral posterior parietal infarcts.” In addition to his binding difficulties, he experienced simultanagnosia, an inability to see more than one object out of several presented to his view at once.

It may be a “dog bites man” report by now, but I think it’s worth noting that finding patients with neural dysfunctions is still a more productive way of gaining new neuroscientific knowledge than woolly-headed speculation about quantum mechanics, speculation which incidentally ignores big facts about physics.

(Tip o’ the fedora to Mind Hacks, and to Warren Ellis, whose “4am” provides my current background score.)

Neuroscience

Absinthe-Minded

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Jay Novella writes about absinthe, and how this classic beverage is really just another kind of booze: the “special ingredient,” thujone, isn’t really a hallucinogen after all. This is doubtless the cause of much heartbreak and disappointment, but I have a solution:

LSD-spiked absinthe.

What could possibly go wrong? This is serious psychiatry we’re talking about, here. I mean, a bottle in front of me is still better than a prefrontal lobotomy, right?

Network theory, Neuroscience, Popularization, Quantum mechanics

Yawn: More Abuse of the Quantum

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Binocular rivalry is a phenomenon which occurs when conflicting information is presented to each of our two eyes, and the brain has to cope with the contradiction. Instead of seeing a superimposition or “average” of the two, our perceptual machinery entertains both possibilities in turn, randomly flickering from one to the other. This presents an interesting way to stress-test our visual system and see how vision works. Unfortunately, talk of “perception” leads to talk of “consciousness,” and once “consciousness” has been raised, an invocation of quantum mechanics can’t be too far behind.

I’m late to join the critical party surrounding E. Manousakis’ paper, “Quantum theory, consciousness and temporal perception: Binocular rivalry,” recently uploaded to the arXiv and noticed by Mo at Neurophilosophy. Manousakis applies “quantum theory” (there’s a reason for those scare quotes) to the problem of binocular rivalry and from this hat pulls a grandiose claim that quantum physics is relevant for human consciousness.

A NOTE ON WIRES AND SLINKYS

First, we observe that there is a healthy literature on this phenomenon, work done by computational neuroscience people who aren’t invoking quantum mechanics in their explanations.

Second, one must carefully distinguish a model of a phenomenon which actually uses quantum physics from a model in which certain mathematical tools are applicable. Linear algebra is a mathematical tool used in quantum physics, but describing a system with linear algebra does not make it quantum-mechanical. Long division and the extraction of square roots can also appear in the solution of a quantum problem, but this does not make dividing 420 lollipops among 25 children a correlate of quantum physics.

Just because the same equation applies doesn’t mean the same physics is at work. An electrical circuit containing a capacitor, an inductor and a resistor obeys the same differential equation as a mass on a spring: capacitance corresponds to “springiness,” inductance to inertia and resistance to friction. This does not mean that an electrical circuit is the same thing as a rock glued to a slinky.

MIXING THE QUANTUM AND THE CLASSICAL

One interesting thing about this paper is that the hypothesis is really only half quantum, at best. In fact, three of the four numbers fed into Manousakis’ hypothesis pertain to a classical phenomenon, and here’s why:

Manousakis invokes the formalism of the quantum two-state system, saying that the perception of (say) the image seen by the left eye is one state and that from the right eye is the other. The upshot of this is that the probability of seeing the illusion one way — say, the left-eye version — oscillates over time as

[tex]P(t) = \cos^2(\omega t),[/tex]

where [tex]\omega[/tex] is some characteristic frequency of the perceptual machinery. The oscillation is always going, swaying back and forth, but every once in a while, it gets “observed,” which forces the brain into either the clockwise or the counter-clockwise state, from which the oscillation starts again.

The quantum two-state system just provides an oscillating probability of favoring one perception, one which goes as the square of [tex]\cos(\omega t)[/tex]. Three of the four parameters fed into the Monte Carlo simulation actually pertain to how often this two-state system is “observed” and “collapsed”. These parameters describe a completely classical pulse train — click, click, click, pause, click click click click, etc.

What’s more, the classical part is the higher-level one, the one which intrudes on the low-level processing. Crudely speaking, it’s like saying there’s a quantum two-state system back in the visual cortex, but all the processing up in the prefrontal lobes is purely classical.
Continue reading Yawn: More Abuse of the Quantum →