Faster fMRI?

A paper demonstrating a new technique for "ultrafast fMRI" has been getting some buzz on the blogosphere. Although movies often depict fMRI showing real-time activity in the brain, in fact typical methods only collect from one slide of the brain at a time, taking a fair amount of time to cover the entire brain (Neuroskeptic puts this at about 2-3 seconds). This new technique (GIN) can complete the job in 50 ms, and without sacrificing spatial resolution (which is the great advantage of fMRI relative to other neuroimaging techniques like EEG or MEG).

Does this mean fMRI is about to get 50 times faster?

Not exactly. What fMRI is measuring is the change in blood oxygenation in areas of your brain. When a particular area starts working harder, more oxygen-rich blood is sent in its direction, and that can be detected using MRI. The limitation is that it takes a while for this blood to actually get there (around 5-10 seconds). One commenter on the Neuroskeptic post (which is where I heard about this article) wrote "making fMRI 50 times faster is like using an atomic clock to time the cooking of a chicken."

The basic fact is that fMRI is never going to compete with EEG or MEG in terms of temporal resolution, because the latter directly measure the electrical activity in the brain and can do so on very fine time-scales. But that doesn't mean that speeding up fMRI data acquisition isn't a good idea. As the authors of the paper write:

fMRI studies, especially related to causality and connectivity, would benefit from reduced repetition time in terms of better statistics and physiological noise characteristics...

They don't really say *how* these studies would achieve this benefit. The rest of the discussion is mostly about how their technique improves on other attempts at ultra-fast fMRI, which tend to have poor spatial resolution. They do mention that maybe ultra-fast fMRI would help simultaneous EEG-fMRI studies to strengthen the link between the EEG signal and the fMRI signal, but it's obvious to me just how helpful this would be, given the very different timing of EEG and fMRI.

But that's not going to stop me from speculating as to how faster data-acquisition might improve fMRI. (Any readers who know more about fMRI should feel free to step in for corrections/additions).

Speculations

The basic problem is that what you want to do is model the hemodynamic response (the change in blood oxygenation levels) due to a given trial. This response unfolds over a time-course of 5-10 seconds. If you are only measuring what is happening every couple seconds, you have pretty sparse data from which to reconstruct that response. Here's an example of some reconstructed responses (notice they seem to be sampling once every second or so):

Much faster data-collection would help with this reconstruction, leading to more accurate results (and conclusions). The paper also mentions that their technique helps with motion-correction. One of the basic problems in fMRI is that if somebody moves their head/brain even just a few millimeters, everything gets thrown off. It's very hard to sit in a scanner for an hour or two without moving even a smidge (one technique, used by some hard-core researchers, is a bite bar, which is perfectly fitted to your jaw and keeps you completely stabilized). Various statistical techniques can be used to try to mitigate any movement that happens, but they only work so well. The authors of the paper write:

Obviously, all InI-based and comparable imaging methods are sensitive to motion especially at the edges of the brain with possible incorrect estimation of prior information. However, due to the large amount of data, scan times are currently short (4 min in teh current study), which mitigates the motion problem.

I take this to mean that because their ultra-rapid scanning technique collects so much data from each trial, you don't need as many trials, so the entire experiment can be shortened. Note that they are focused on the comparison between their technique and other related techniques, not the comparison between their technique and standard fMRI techniques. But it does seem reasonable that more densely sampling the hemodynamic response for an individual trial should mean you need fewer trials overall, thus shortening experiments.

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Boyacioğlu, R., & Barth, M. (2012). Generalized iNverse imaging (GIN): Ultrafast fMRI with physiological noise correction Magnetic Resonance in Medicine DOI: 10.1002/mrm.24528

Wait -- Jonah Lehrer Wants Reading to be Harder?

Recently Jonah Lehrer, now at Wired, wrote a ode to books, titled The Future of Reading. Many people are sad to see the slow replacement of physical books by e-readers -- though probably not many people who have lugged 50 pounds of books in a backpack across Siberia, though that's a different story. The take-home message appears 2/3 of the way down:

So here’s my wish for e-readers. I’d love them to include a feature that allows us to undo their ease, to make the act of reading just a little bit more difficult. Perhaps we need to alter the fonts, or reduce the contrast, or invert the monochrome color scheme. Our eyes will need to struggle, and we’ll certainly read slower, but that’s the point: Only then will we process the text a little less unconsciously, with less reliance on the ventral pathway. We won’t just scan the words – we will contemplate their meaning.

As someone whose to-read list grows several times faster than I actually do any reading, I've never wished to read more slowly. But Lehrer is a science writer, and (he thinks) there's more to this argument than just aesthetics. As far as I can tell, though, it's based on a profound misunderstanding of the science. Since he manages to get through the entire post without ever citing a specific experiment, it's hard to tell for sure, but here's what I've managed to piece together. 

Reading Research

Here's Lehrer:

Let me explain. Stanislas Dehaene, a neuroscientist at the College de France in Paris, has helped illuminate the neural anatomy of reading. It turns out that the literate brain contains two distinct pathways for making sense of words, which are activated in different contexts. One pathway is known as the ventral route, and it’s direct and efficient, accounting for the vast majority of our reading. The process goes like this: We see a group of letters, convert those letters into a word, and then directly grasp the word’s semantic meaning. According to Dehaene, this ventral pathway is turned on by “routinized, familiar passages” of prose, and relies on a bit of cortex known as visual word form area (VWFA).

So far, so good. Dehaene is a brilliant researcher who has had an enormous effect on several areas of cognition (I'm more familiar with his work on number). I'm a bit out-of-date on reading research (and remember Lehrer doesn't actually cite anything to back up his argument), but this looks like an updated version of the old distinction between whole-word reading and real-time composition. That is, it goes without saying that you must "sound out" novel words that you've never encountered before, such as gafrumpenznout. However, it seems that as you become more familiar with a particular word (maybe Gafrumpenznout is your last name), you can recognize the word quickly without sounding it out.

Here's the abstract from a relevant 2008 Dehaene group paper:

Fast, parallel word recognition, in expert readers, relies on sectors of the left ventral occipito-temporal pathway collectively known as the visual word form area. This expertise is thought to arise from perceptual learning mechanisms that extract informative features from the input strings. The perceptual expertise hypothesis leads to two predictions: (1) parallel word recognition, based on the ventral visual system, should be limited to words displayed in a familiar format (foveal horizontal words with normally spaced letters); (2) words displayed in formats outside this field of expertise should be read serially, under supervision of dorsal parietal attention systems. We presented adult readers with words that were progressively degraded in three different ways (word rotation, letter spacing, and displacement to the visual periphery).

When the words are degraded in these various ways, participants had a harder time reading and recruited different parts of the brain. A (slightly) more general public-friendly version of this story appears in this earlier paper. This appears to be the paper that Lehrer is referring to, since he says that Dehaene, in experiments, activates the dorsal pathways "in a variety of ways, such as rotating the letters or filling the prose with errant punctuation."

And the Vision Science Behind It

This work makes a lot of sense, given what we know about vision. Visual objects -- such as letters -- "crowd" each other. In other words, when there are several that are close together, it's hard to see any of them. This effect is worse in peripheral vision. Therefore, to see all the letters in a long-ish word, you may need to fixate on multiple parts of the word.

However, orthography is heavily redundant. One good demonstration of this is rmvng ll th vwls frm sntnc. You can still read with some of the letters missing (and of course some languages, like Hebrew, never print vowels). Moreover, sentence context can help you guess what a particular word is. So if you're reading a familiar word in a familiar context, you may not need to see all the letters well in order to identify it. The less certain you are of what the word is, the more carefully you'll have to look at it.

The Error

So far, this research appears to be about visual identification of familiar objects. Lehrer makes a big leap, though:

When you are a reading a straightforward sentence, or a paragraph full of tropes and cliches, you’re almost certainly relying on this ventral neural highway. As a result, the act of reading seems effortless and easy. We don’t have to think about the words on the page ...  Deheane’s research demonstrates that even fluent adults are still forced to occasionally make sense of texts. We’re suddenly conscious of the words on the page; the automatic act has lost its automaticity.

This suggests that the act of reading observes a gradient of awareness. Familiar sentences printed in Helvetica and rendered on lucid e-ink screens are read quickly and effortlessly. Meanwhile, unusual sentences with complex clauses and smudged ink tend to require more conscious effort, which leads to more activation in the dorsal pathway. All the extra work – the slight cognitive frisson of having to decipher the words – wakes us up.

It's based on this that he argues that e-readers should make it harder to read, because then we'd pay more attention to what we're reading. The problem is that he seems to have confused the effort expended in recognizing the visual form of a word -- the focus of Dehaene's work -- with effort expended in interpreting the meaning of the sentence. Moreover, he seems to think that the harder it is to understand something, the more we'll understand it -- which seems backwards to me. Now it is true that the more deeply we process something the better we remember it, but it's not clear that making something hard to see necessarily means we process it more deeply. In any case, we'd want some evidence that this is so, which Lehrer doesn't cite.

Which brings me back to citation. Dehaene did just publish a book on reading, which I haven't read because it's (a) long, and (b) not available on the Internet. Maybe Dehaene makes the claim that Lehrer is attributing to him in that book. Maybe there's even evidence to back that claim up. As far as I can tell, that work wasn't done by Dehaene (as Lehrer implies) since I can't find it on Dehaene's website. Though maybe it's there under a non-obvious title (Dehaene publishes a lot!). This would be solved if Lehrer would cite his sources.

Caveat


I like Lehrer's writing, and I've enjoyed the few interactions I've had with him. I think occasional (frequent?) confusion is a necessary hazard of being a science writer. I have only a very small number of topics I feel I understand well enough to write about them competently. Lehrer, by profession, must write about a very wide range of topics, and it's not humanly possible to understand many of them very well.


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DEHAENE, S., COHEN, L., SIGMAN, M., & VINCKIER, F. (2005). The neural code for written words: a proposal Trends in Cognitive Sciences, 9 (7), 335-341 DOI: 10.1016/j.tics.2005.05.004

Cohen L, Dehaene S, Vinckier F, Jobert A, & Montavont A (2008). Reading normal and degraded words: contribution of the dorsal and ventral visual pathways. NeuroImage, 40 (1), 353-66 PMID: 18182174

Photos: margolove, kms !

Is psychology a science, redux

Is psychology a science? I see this question asked a lot on message boards, and it's time to discuss it again here. I think the typical response by a researcher like myself is an annoyed "of course, you ignoramus." But a more subtle response is deserved, as the answer depends entirely on what you mean by "psychology" and what you mean by "science."

Two Psychologies

First, if by "psychology" you mean seeing clients (like in Good Will Hunting or Silence of the Lambs), then, no, it's probably not a science. But that's a bit like asking whether engineers or doctors are scientists. Scientists create knowledge. Client-visiting psychologists, doctors and engineers use knowledge. Of course, you could legitimately ask whether client-visiting psychologists base their interventions on good science. Many don't, but that's also true about some doctors and, I'd be willing to bet, engineers.

Helpfully, "engineering" and "physics" are given different names, while the research and application ends of psychology confusingly share the same name. (Yes, I'm aware that engineering is not hte application of physics writ broadly -- what's the application of string theory? -- and one can be a chemical engineer, etc. I actually think that makes the analogy to the two psychologies even more apt). It doesn't help that the only psychologists who show up in movies are the Good Will Hunting kind (though if paleoglaciologists get to save the world, I don't see why experimental psychologists don't!), but it does exist.

A friend of mine (a physicist) once claimed psychologists don't do experiments (he said this un-ironically over IM while I was killing time in a psychology research lab). My response now would be to invite him to participate in one of these experiments. Based on this Facebook group, I know I'm not the only one who has heard this.

Methods

There are also those, however, who are aware that psychologists do experiments, but deny that it's a true science. Some of this has to do with the belief that psychologists still use introspection (there are probably some somewhere, but I suspect there are also physicists who use voodoo dolls somewhere as well, along with mathematicians who play the lottery).

The more serious objection has to do with the statistics used in psychology. In the physical sciences, typically a reaction takes place or does not, or a neutrino is detected is not. There is some uncertainty given the precision of the tools being used, but on the whole the results are fairly straight-forward and the precision is pretty good (unless you study turbulence or something similar).

In psychology, however, the phenomena we study are noisy and the tools lack much precision. When studying a neutrino, you don't have to worry about whether it's hungry or sleepy or distracted. You don't have to worry about whether the neutrino you are studying is smarter than average, or maybe too tall for your testing booth, or maybe it's only participating in your experiment to get extra credit in class and isn't the least bit motivated. It does what it does according to fairly simple rules. Humans, on the other hand, are terrible test subjects. Psychology experiments require averaging over many, many observations in order to detect patterns within all that noise.

Science is about predictions. In theory, we'd like to predict what an individual person will do in a particular instance. In practice, we're largely in the business of predicting what the average person will do in an average instance. Obviously we'd like to make more specific predictions (and there are those who can and do), but they're still testable (and tested) predictions. The alternative is to declare much of human and animal behavior outside the realm of science.

Significant differences

There are some who are on board so far but get off the bus when it comes to how statistics are done in psychology. Usually an experiment consists of determining statistically whether a particular result was likely to have occurred by chance alone. Richard Feynman famously thought this was nuts (the thought experiment is that it's unlikely to see a license plate printed CPT 349, but you wouldn't want to conclude much from it).

That's missing the point. The notion of significant difference is really a measure of replicability. We're usually comparing a measurement across two populations. We may find population A is better than population B on some test. That could be because population A is underlyingly better at such tests. Alternatively, population A was lucky that day. A significant difference is essentially a prediction that if we test population A and population B again, we'll get the same results (better performance for population A). Ultimately, though, the statistical test is just a prediction (one that typically works pretty well) that the results will replicate. Ideally, all experiments would be replicated multiple times, but that's expensive and time-consuming, and -- to the extent that the statistical analysis was done correctly (a big if) -- largely unnecessary

So what do you think? Are the social sciences sciences? Comments are welcome.

Why is learning a language so darn hard (golden oldie)

I work in an toddler language lab, where we study small children who are breezing through the process of language acquisition. They don't go to class, use note cards or anything, yet they pick up English seemingly in their sleep (see my previous post on this).

Just a few years ago, I taught high school and college students (read some of my stories about it here) and the scene was completely different. They struggled to learn English. Anyone who has tried to learn a foreign language knows what I mean.

Although this is well-known, it's a bit of mystery why. It's not the case that my Chinese students didn't have the right mouth shape for English (I've heard people -- not scientists -- seriously propose this explanation before). It's also not just that you can learn only one language. There are plenty of bilinguals out there. Jesse Snedeker (my PhD adviser as of Monday) and her students recently completed a study of cross-linguistic late-adoptees -- that is, children who were adopted between the ages of 2 and 7 into a family that spoke a different language from that of the child's original home or orphanage. In this case, all the children were from China. They followed the same pattern of linguistic development -- both in terms of vocabulary and grammar -- as native English speakers and in fact learned English faster than is typical (they steady caught up with same-age English-speaking peers).

So why do we lose that ability? One model, posited by Michael Ullman at Georgetown University (full disclosure: I was once Dr. Ullman's research assistant), has to do with the underlying neural architecture of language. Dr. Ullman argues that basic language processes are divided into vocabulary and grammar (no big shock there) and that vocabulary and grammar are handled by different parts of the brain. Simplifying somewhat, vocabulary is tied to temporal lobe structures involved in declarative memory (memory for facts), while grammar is tied to procedural memory (memory for how to do things like ride a bicycle) structures including the prefrontal cortex, the basal ganglia and other areas.

As you get older, as we all know, it becomes harder to learn new skills (you can't teach an old dog new tricks). That is, procedural memory slowly loses the ability to learn new things. Declarative memory stays with us well into old age, declining much more slowly (unless you get Alzheimer's or other types of dementia). Based on Dr. Ullman's model, then, you retain the ability to learn new words but have more difficulty learning new grammar. And grammar does appear to be the typical stumbling block in learning new languages.

Of course, I haven't really answered my question. I just shifted it from mind to brain. The question is now: why do the procedural memory structures lose their plasticity? There are people studying the biological mechanisms of this loss, but that still doesn't answer the question we'd really like to ask, which is "why are our brains constructed this way?" After all, wouldn't it be ideal to be able to learn languages indefinitely?

I once put this question to Helen Neville, a professor at the University of Oregon and expert in the neuroscience of language. I'm working off of a 4-year-old memory (and memory isn't always reliable), but her answer was something like this:

Plasticity means that you can easily learn new things. The price is that you forget easily as well. For facts and words, this is a worthwhile trade-off. You need to be able to learn new facts for as long as you live. For skills, it's maybe not a worthwhile trade-off. Most of the things you need to be able to do you learn to do when you are relatively young. You don't want to forget how to ride a bicycle, how to walk, or how to put a verb into the past tense.

That's the best answer I've heard. But I'd still like to be able to learn languages without having to study them.

originally posted 9/12/07

Video games, rotted brains, and book reviews

Jonah Lehrer has an extended discussion of his review of The Shallows, a new book claiming that the Internet is bad for our brains. Lehrer is skeptical, pointing out that worries about new technology are as old as time (Socrates thought books would make people stupid, too). I am skeptical as well, but I'm also skeptical of (parts of) Lehrer's arguments. The crux of the argument is as follows:

I think it's far too soon to be drawing firm conclusions about the negative effects of the web. Furthermore, as I note in the review, the majority of experiments that have looked directly at the effects of the internet, video games and online social networking have actually found significant cognitive benefits.

That, so far as it goes, is reasonable. My objection is to some of the evidence given:

A 2009 study by neuroscientists at the University of California, Los Angeles, found that performing Google searches led to increased activity in the dorsolateral prefrontal cortex, at least when compared with reading a "book-like text." Interestingly, this brain area underlies the precise talents, like selective attention and deliberate analysis, that Carr says have vanished in the age of the Internet. Google, in other words, isn't making us stupid -- it's exercising the very mental muscles that make us smarter.

This cuts several ways. Extra activation of a region in an fMRI experiment is interpreted different ways by different researchers. It could be evidence of extra specialization ... or evidence that the brain network in question is damaged and so needs to work extra hard. Lehrer is at least partially aware of this problem:

Now these studies are all imperfect and provisional. (For one thing, it's not easy to play with Google while lying still in a brain scanner.)

This is the line I have a particular issue with. If the question is whether extra Internet use makes people stupid, why on Earth would anyone need to use a $600/hr MRI machine to answer that question? We have loads of cheap psychometric tests of cognition. All methodologies have their place, and a behavior question is most easily answered with behavioral methods. MRI is far more limited.

Lehrer's discussion of the 2009 study above underscores this point: the interpretation of the brain images rests on our understanding of what behaviors the dorsolateral prefrontal cortex has shown up with in other studies. The logic is: A correlates with B correlates with C, thus A correlates with C. This is, as any logician will tell you, an unsound conclusion. When you add that using MRI can cost ten thousand dollars for a single experiment, it's a very expensive middleman!

Which isn't to say that MRI is useless or such studies are a waste of time. MRI is particularly helpful in understanding how the brain gives rise to various types of behavior, and it's sometimes helpful for analyzing behavior that we can't directly see. Neither applies here. If the Internet makes us dumb in a way only detectable with super-modern equipment, I think we can breath easy and ignore the problem. What we care about is whether people in fact are more easily distracted, have worse memory, etc. That doesn't require any special technology -- even Socrates could run that experiment.



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Lehrer does discuss a number of good behavioral experiments. Despite my peevishness over the "Google in the scanner" line, the review is more than worth reading.

The military is making telepathic helmets. Sign me up.

It appears researchers at UC-Irvine, University of Maryland and Carnegie Mellon have a DOD grant to investigate the development of "though helmets": 

The devices would harness a person´s brain waves and transmit them as radio waves, where they would be translated into words in the headphones of other soldiers.

I need one of these.


Don't blink -- I'm reading your thoughts


The proposed technology (which they don't expect to be ready for a decade or two) relies on EEG technology -- that is, measuring brain waves. As it happens, this is a method I use to run experiments. It has its limitations.


First off, it only really works if people are sitting still and not moving their eyes. EEG measures electrical activity. Ideally, it measure the brain's electrical activity, but muscles also produce electrical activity and the effects are hundreds of times larger than brain effects. People are working on snazzy new algorithms to factor out the thunderclaps of eye blinks (the huge mountains in this picture are individual blinks).

One-of-a-kind

Another problem is individual variation. While blinks are very easy to see in the raw waveforms, thoughts are hard. For instance, one of the best known EEG effects in language is the N400 -- a broadly-distributed negative deflection around 400 milliseconds after the participant sees a word. Unfortunately, the N400 is so small relative to all the noise in the signal that it's hard to see on a single trial. In a typical experiment, each participant sees 30-40 words (or more), and we average across those trials. Even then, each individual person's N400 looks very different, so we usually have to average across at least a dozen different people to get a good signal.

Thoughts

The bulk of EEG research employs a violation paradigm. We measure the brain's activity when something unexpected happens. For instance, a psycholinguist like myself might compare the two following sentences:

(1) Dog bit the man.

(2) The man bit the dog.

The second sentence is surprising relative to the first, and you can typically see a reasonably large effect in the brain waves (modulo the caveats above). Part of the reason we use violation paradigms is they produce large effects. Trying to compare two perfectly normal sentences is much, much harder.

Other typical effects people can find are differences between function words (e.g., prepositions) and content words (e.g., nouns) -- though, again, this is hard to see on a trial-by-trial basis.

Get me one

There are many, many other obstacles in the way of a mind-reading EEG helmet. That isn't to say that I don't think such a helmet will be built eventually, or that the government is wasting it's money. Technology constantly improves, and setting an on-the-face absurd goal can be excellent motivation.

But I wouldn't start saving up to buy one of your own just yet. Though I'd love one. A helmet that worked that well would make my research go much, much faster.

Lie detection

A few pioneering lawyers have been attempting to use fMRI-based lie detection tests in court. I don't have any broad numbers, but it seems most neuroimagers I talk to are deeply skeptical of such tests, at least at the current stage of technology (and whether such technology can ever catch pathological liars is yet another question).

At a recent talk at Harvard, Michael Gazzaniga related the following argument from a colleague on the law end of things: whether fMRI-based lie detection is "good enough" is not a scientific question but a legal one. After all, the law allows all kinds of scientifically-suspect "evidence" into the courtroom as is (eye-witness testimony, fingerprinting, etc.). Present all data (along with information about how reliable it is) to the jury and let the jury sort it out.

That's one conclusion that could be drawn. Another is that perhaps it's time to step back and come up with a broad policy for how evidence is introduced into the legal system.

Recent Findings Don't Prove there's a Ghost in the Machine (Sorry Saletan)

When I took intro to psychology (way too long ago), the graduate instructor posed the following question to the class: Does your brain control your mind, or does your mind control your brain? At first I thought this was a trick question -- coming from most neuroscientists or cognitive scientists it would be -- but she meant it seriously.

On Tuesday, William Saletan at Slate posed the same question. Bouncing off recent evidence that some supposedly vegetative patients are in fact still able to think, Saletan writes, "Human minds stripped of every other power can still control one last organ--the brain."

Huh?

Every neuroscientist I've talked to would read this as a tautology: "the brain controls the brain." Given the gazillions of feedback circuits in the brain, that's a given. Reading further, though, Saletan clearly has something else in mind:

We think of the brain as its own master, controlling or fabricating the mind ... If the brain controls the mind this way, then brain scanning seems like mind reading ... It's fun to spin out these neuro-determinist theories and mind-reading fantasties. But the reality of the European scans is much more interesting. They don't show the brain controlling the mind ... The scans show the opposite: the mind operating the brain."

Evidence Mind is Master

As I've already mentioned above, the paragraph quoted above is nonsensical in modern scientific theory, and I'll get back to why. But before that, what evidence is Saletan looking at?

In the study he's talking about, neuroscientists examined 54 patients who show limited or no awareness and no ability to communicate. Patients brains were scanned while they were asked to think of motor activities (swinging a tennis racket) or navigation activities (moving around one's home town). 5 of the 54 were able to do this. They also tried to ask the patients yes-no questions. If the answer was 'yes', the patient was to think about swinging a tennis racket; if 'no', moving around one's home town. One patient was able to do this successfully.

Note that the brain scans couldn't see the patient deciding 'yes' or 'no' -- actually, they couldn't see the patient deciding at all. This seems to be why Saletan thinks this is evidence of an invisible will controlling the physical brain: "On the tablet of your brain, you can write whatever answer you want."

The Mistake

The biggest problem with this reasoning is a misunderstanding of the method the scientists used. FMRI detects very, very small signals in the brain. The technology tracks changes in blood oxygenation levels, which correlates with local brain activity (though not perfectly). A very large change is on the order of 1%. For more complicated thoughts, effect sizes of 0.5% or even 0.1% are typical. Meanwhile, blood oxygen levels fluctuate a good deal for reasons of their own. This low signal-to-noise ratio means that you usually need dozens of trials: have the person think the same thoughts over and over again and average across all the trials. In the fMRI lab I worked in previously, the typical experiment took 2 hours. Some labs take even longer.

To use fMRI for meaningful communication between a paralyzed person and their doctors, you need to  be able to detect the response to an individual question. Even if we knew were to look in the brain for 'yes' or 'no' answers -- and last I heard we didn't, but things change quickly -- its unlikely we could hear this whispering over the general tumult in the brain. The patients needed to shout at the top of their lungs. It happens that physical imagery produces very nice signals (I know less about navigation, but presumably it does, too, or the researchers wouldn't have used it).

Thus, the focus on visual imagery rather than more direct "mind-reading" was simply an issue of technology.

Dualism

The more subtle issue is that Saletan takes dualism as a starting point: the mind and brain are separate entities. Thus, it makes sense to ask which controls the other. He seems to understand modern science as saying the brain controls the mind.

This is not the way scientists currently approach the problem -- or, at least, not any I know. The starting assumption is that the mind and brain are two ways of describing the same thing. Asking whether the mind can control the brain makes as much sense as asking whether the Senate controls the senators or senators control the Senate. Talking about the Senate doing something is just another way of talking about some set of senators doing something.

Of course, modern science could be wrong about the mind. Maybe there is a non-material mind separate from the brain. However, the theory that the mind is the brain has been enormously productive. Without it, it is extremely difficult to explain just about anything in neuroscience. Why does brain trauma lead to amnesia, if memories aren't part of the brain? Why can strokes leave people able to see but unaware that they can see?

Descartes' Error

A major problem with talking about the mind and brain is that we clearly conceptualize of them differently. One of the most exciting areas of cognitive science in the last couple decades has looked at mind perception. It appears humans are so constructed that we are good at detecting minds. We actually over-detect minds, otherwise puppet shows wouldn't work (we at least half believe the puppets are actually thinking and acting). Part of our concept of mind is that it is non-physical but controls physical bodies. While our concept of mind appears to develop during early childhood, the fact that almost all humans end up with a similar concept suggests that either the concept or the propensity to develop it is innate.

Descartes,  who produced probably the most famous defense of dualism, thought the fact that he had the concept of God proved that God exists (his reasoning: how can an imperfect being have the thought of a perfect being, unless the perfect being put that thought there?). Most people would agree, however, that just because you have a concept doesn't mean the thing the concept refers to exists. I, for instance, have the concept of cylons, but I don't expect to run into any.

Thus, even as science becomes better and better at explaining how a physical entity like the brain gives rise to our perceptions, our experience of existing and thinking, the unity of mind and brain won't necessarily make any more intuitive sense. This is similar to the problem with quantum physics: we have plenty of scientific evidence that something can be both a wave and a particle simultaneously, and many scientists work these theories with great dexterity. But I doubt anyone really has a clear conception of a wave/particle. I certainly don't, despite a semester of quantum mechanics in college. We just weren't set up to think that way.

For this reason, I expect we'll continue to read articles like Saletan's long in the future. This is unfortunate, as neuroscience is becoming an increasingly important part of our lives and society, in a way quantum physics has yet to do. Consider, for instance, insanity pleas in the criminal justice system, lie detectors, and so on.

Keeping your brain in a computer

A researcher at UC-San Diego is methodically slicing and preparing one of the world's most famous brains (where "world" is narrowly defined as the world of cognitive science -- I suspect HM isn't a household name, though he was a huge anonymous celebrity among psychologists and neuroscientists for the last half-century). The hope is to make the data electronically available.

An interesting fact tucked in at the end of the article is that in order to make it possible to zoom down to the cellular level on each electronic copy of each slide will require 1 - 10 terabytes per slide. That's terabytes with a t. There are 2,400 slices of the brain (I'm not clear as to whether all will become slides, but presumably a good fraction will be). And the researcher wants to eventually expand the project to 500 brains.

This creates a serious storage issue.

It also brings up the question of building synthetic brains. If we need something on the order of 5,000 terabytes just to render a digital image of a brain, how many do we need to perfectly model a brain?

Granted, there aren't 5,000 trillion neurons in a brain (there are about 100 billion). But one neuron doesn't equal one bit -- a neuron's behavior is complex, and it's pieces do things. As we don't fully understand what neurons do, I take it as uncontroversial we don't know how many 'bits' make up a neuron.

This is one of the complications with predicting the future of neuroscience. Our knowledge and technology are growing exponentially, but we don't know how far there is to go.

Emotions Caused by Your Brain

Yesterday, the New York Times ran a science article under the following heading: In Pain and Joy of Envy, the Brain May Play a Role. It is a very well-written and engaging article of the subject of envy, which is a fascinating emotion.

The title, however, leaves something to be desired. It seems to imply that there was some doubt over whether the brain plays a role in envy. The modern scientific consensus is that the brain plays a role in all emotions.

So why write this article? To tell the truth, the article doesn't fit the title very well: the article isn't really about proving a role for the brain in envy. A better title might have been "The Science of Envy." I suspect the editors chose the title because it is well-known that people believe cognitive research more if you stick the word "brain" in a few places. In journalistic parlance, neuroscience is a good hook.

However, as a public service, and in probably a vain attempt to forestall future articles with titles such as "In Pain and Joy of love/hate/surprise/etc., the Brain May Play a Role," here are a list of emotions and psychological states (courtesy of WordNet) in which the brain certainly plays a role, to the extent we can be certain about anything:

abashment
abhorrence
absolutethreshold
acidity
acridity
activity
addiction
affection
agape
aggravation
aggression
aim
alarm
anaphrodisia
angst
animus
antagonism
anxiety
anxiousness
aphrodisia
appetite
ardor
aroma
arousal
assumption
astringence
attention
attitude
attributing
auditoryperception
awareness
awe
badtemper
beholding
belief
belligerence
beneficence
benevolence
bitter
blessedness
bloodlust
boding
bold
boredom
brave
breakdown
brightnessconstancy
caprice
caring
cautious
chafe
chagrin
chill
chromesthesia
class feeling
cogitation
cold
cold feet
colorconstancy
coloredhearing
comfortzone
competence
concentration
concept
conditioned response
confidence
conscience
consideration
constancy
constriction
construction
construing
contemplation
contrast
copulation
cowardly
craving
creeps
curiosity
curious
cutaneoussensation
deficit
deliberation
desire
despisal
detection
devotion
differencethreshold
diffidence
discombobulation
discomfiture
discontentment
disgruntlement
displeasure
dissatisfaction
dread
dream
driven
dudgeon
dysphoria
ecstasy
edginess
education
elation
embarras
embarrassmentsment
embitterment
emotionalstate
empathy
emulation
enamoredness
engrossment
enmity
estimate
euphoria
exhilaration
expectation
exuberance
facerecognition
faculty
faintness
fear
fed
feeling
finish[winetasting]
fit
fondness
fondregard
fragility
frisson
frustration
fundamental
fury
gaiety
generosity
gloom
gloomy
gratefulness
gratification
gratitude
hackles
hankering
happiness
harassment
harmonic
hatred
health
heart
heartstrings
homesickness
horror
huffiness
humility
hunch
hysteria
idea
image
immersion
impatient
impression
incautious
incense
incentive
indignation
infirmity
infuriation
insecurity
intention
interest
interpretation
interpreting
intimidation
intoxication
introspection
intuitions
irascibility
ire
itching
jealousy
jitteriness
jnd
joy
jubilance
judgement
judgment
lazy
lecherousness
lemon
letdown
levity
libido
limen
lividity
longing
love
lovesickness
loyalty
maleficence
malevolence
malice
malodor
masking
meekness
melody
misanthropy
misocainea
misogamy
misogyny
misology
misoneism
misopedia
mittelschmerz
motivation
motive
murderousness
music
music[music]
musicalperception
musicofthespheres
musings
musk
nationalism
naughty
need
nervous
niff
nostalgia
nymphomania
objective
objectiveorgoal
objectrecognition
open
opinion
opticalfusion
outlook
overtone
pain>twinge
painthreshold
panic
passion
patient
perspective
pessimism
phantom limb pain
piece
pining
pins and needles
pique
plan
pointofview
pondering
position
pressure
projection
protectiveness
proud
prurience
pruritus
pruritusani
pruritusvulvae
puppylove
purpose
qualityoflife
racket
radiance
rationalized
reaction
reasoning
reflection
regard
relish
representation
resentment
reserve
responsible
sadness
salt
satyriasis
scare
scent
scruple
security
seethe
self-depreciation
self-disgust
selfish
sensation>odor
sense
sensuality
serenity
serious
sexiness
sexualdesire
shame
shamefacedness
shapeconstancy
shyness
side
sinking
sizeconstancy
smell
softspot
somesthesia
sound>tone
sour
speculation
speechperception
stage fright
stance
state
stomach
supposing
surmising
suspense
suspicious
sweet
sweettooth
sympathy
synesthesia
taste>tang
temperature>warmth
temptation
tenderness
terror
thinking
thought
tickle
timid
timidness
tingle
titillation
to stop loving
tolerant
tone
topognosia
touch
trepidation
triumph
trust
twinge
umbrage
uneasiness
unhappiness
up
urge
urtication
vanilla
velleity
view
viewpoint
vigil
vindictiveness
vision
visualspace
wakefulness
warmth
weakness
whistful
whitenoise
willies
wishfulness
wishing
wistfulness
withdrawn
wor
worship
wrath

Even Experts Don't Know what Brain Scans Mean

For some reason, many people find neuroscience more compelling than psychology. That is, if you tell them that men seem to like video games more than women, they are unconvinced, but if you say that brain scans of men and women playing video games showing that the pleasure centers of their brains respond to video games, suddenly it all seems more compelling.

More flavors is more fun, and the world can accept variation in what types of evidence people find compelling -- and we're probably the better for it. In this case, though, there is a problem in that neuroscientific data is very hard to interpret. Jerome Kagan said it perfectly in his latest book, so I'll leave it to him:

A more persuasive example is seen in the reactions to pictures that are symbolic of unpleasant (snakes, bloodied bodies), pleasant (children playing, couples kissing), or neutral (tables, chairs) emotional situations.The unpleasant scenes typically induce the largest eyeblink startle response to a loud sound due to recruitment of the amygdala. However, there is greater blood flow to temporal and parietal areas to the pleasant than to the unpleasant pictures, and, making matters more ambiguous, the amplitudes of the event-related waveform eight-tenths of a second after the appearance of the photographs are equivalent to the pleasant and unpleasant scenes. A scientist who wanted to know whether unpleasant or pleasant scenes were more arousing could arrive at three different conclusions depending on the evidence selected.

Daniel Engber in Slate has more excellent discussion of this problem.

Similarly, many posts ago, I noted that another Harvard psychologist, Dan Gilbert, prefers to simply ask people if they are happy rather than use a physiological measure because the only reason we think a particular physiological measure indicates happiness is because it correlates with people's self-reports of being happy. In other words, using any physiological measure (including brain scans) as indication of a mental state is circular.


----
Kagan (2007) What Is Emotion, pp. 81-82.

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PS Since I've been writing about Russian lately, I wanted to mention an English-language Russian news aggregator that I came across. This site is from the writer behind the well-known Siberian Light Russia blog.

Skeptical of the Skeptics

I have complained -- more than once -- that the media and the public believe a psychological fact (some people are addicted to computer games) if a neuroimaging study is somehow involved, even if the study itself is irrelevant (after all, the definition of addiction does not require a certain pattern of brain activity -- it requires a certain pattern of physical activity).

Not surprisingly, I and like-minded researchers were pleased when a study came out last year quantifying this apparent fact. That is, the researchers actually found that people rated an explanation of a psychological phenomenon as better if it contained an irrelevant neuroscience fact.

Neuroskeptic has written a very provocative piece urging us to be skeptical of this paper:

This kind of research - which claims to provide hard, scientific evidence for the existence of a commonly believed in psychological phenomenon, usually some annoyingly irrational human quirk - is dangerous; it should always be read with extra care. The danger is that the results can seem so obviously true ("Well of course!") and so important ("How many times have I complained about this?") that the methodological strengths and weaknesses of the study go unnoticed.

Read the rest of the post here.

Who are you calling a neuroscientist: Has neuroscience killed psychology?

The Chronicle of Higher Education just produced a list of the five young scholars to watch who combine neuroscience and psychology. The first one listed is George Alvarez, who was just hired by Harvard.

Alvarez should be on anybody's top five list. The department buzzed for a week after his job talk, despite the fact that many of us already knew his work. What is impressive is not only the quantity of his research output -- 19 papers at last count, with 6 under review or revision -- but the number of truly ground-breaking pieces of work. Several of his papers have been very influential in my own work on visual working memory.

He is also one of the best exemplars of classical cognitive psychology I know. His use of neuroscience techniques is minimal, and currently appears to be limited to a single paper (Batelli, Alvarez, Carlson & Pascual-Leone, in press). Again, this is not a criticism.

Neurons vs. Behavior

This is particularly odd in the context of the attached article, which tries to explore the relationship between neuroscience techniques and psychology. Although there is some balance, with a look at the effect of neuroscience in draining money away from traditional cognitive science, I read the article as promoting the notion that the intersection of neuroscience and psychology is not just the place to be at, it's the only place to be at.

Alvarez is one of the best examples of the opposite claim: that there is still a lot of interesting cognitive science to be done that doesn't require neuroimaging. I should point out that I say this all as a fan of neuroscience, and as somebody currently designing both ERP and fMRI experiments.

EEG vs. fMRI

One more thing before I stop beating up on the Chronicle (which is actually one of my favorite publications). The article claims that EEG (the backbone of ERP) offers less detailed information about the brain in comparison with fMRI. The truth is that EEG offers less detailed information about spatial location, but its temporal resolution is far greater. If the processes you are studying are lightning-fast and the theories you are testing make strong claims about the timing of specific computations, fMRI is not ideal. I think this is why fMRI has had less impact on the study of language than it has in some other areas.

For instance, the ERP study I am working on looks at complex interactions between semantic and pragmatic processes that occur over a few hundred milliseconds. I have seen some very inventive fMRI work on the primary visual cortex that managed that kind of precision, but it is rare (and probably only succeeded because the layout of the visual areas of the brain, in contrast with the linguistic areas, is fairly well-established).

Do Bullies like Bullying?

Although Slate is my favorite magazine, and usually the first website I check each day, I've been known to complain about its science coverage, which typically lacks the insight of its other features. A much-too-rare exception to this are the occasional articles by Daniel Engber (full disclosure: I have attempted to convince Engber, a Slate editor, to run articles by me in the past, unsuccessfully).

Yesterday, he wrote an excellent piece about a recent bit of cognitive neuroscience looking at bullies and how they relate to bullying. Researchers scanned the brains of "bullies" while they viewed videos of bullying and reported that pleasure centers in the brain activated.

In a cheeky fashion typical of Slate, Engber questions the novelty of these findings:

Bullies like bullying? I just felt a shiver run up my spine. Next we'll find out that alcoholics like alcohol. Or that overeaters like to overeat. Hey, I've got an idea for a brain-imaging study of child-molesters that'll just make your skin crawl!

Obviously, I was a sympathetic reader. But Engber does not stop there:

OK, OK: Why am I wasting time on a study so lame that it got a write-up in the Onion? Hasn't this whole fMRI backlash routine gotten a bit passé?

Engber goes on to detail a number of limitations to the study, including how the kids were defined as "bullies" (some appear to be rapists, for instance) and also how "pleasure center" was defined (the area in question is also related to anxiety, so one could reasonably argue bullies find bullying worrisome, not pleasurable).

The second half of the article is a plea for better science reporting, one that I hope is widely-read. Read it yourself here.

Why the Insanity Defense is Un-scientific

In his class book Emotional Intelligence, Daniel Goleman presents a very compelling case for studying individual differences in social and emotional skills. Since people who are less empathic -- less aware of others' thoughts and feelings -- are apparently more likely to commit crime, Goleman argues that this raises the issue of what to do about criminals who are biologically limited in their empathic abilities:

If there are biological patterns at play in some kinds of criminality -- such as a neural defect in empathy -- that does not argue that all criminals are biologically flawed, or that there is some biological marker for crime ... Even if there is a biological basis for a lack of empathy in some cases, that does not mean all who have it will drift to crime; most will not. A lack of empathy should be factored in with all other psychological, economic, and social forces that contribute to a vector toward criminality.

This may seem like a reasonable, middle-of-the road take on the issue, but I would argue that it is actually an extremely radical, non-scientific statement. (Since it is such a common sentiment, I realize this means I may be calling most of the public crazy radicals. So be it. Sometimes, that's the case.)

The Fundamental Axiom of Cognitive Science

It is the scientific consensus that all human behavior is the result activity in the brain. Like gravity and the laws of thermodynamics, this cannot be proven beyond a doubt (in fact, there's a good argument that nothing can be proven beyond a doubt). However, it is the foundation upon which modern psychology and neuroscience is built, and there is no good reason to doubt it.

In fact, many of the world's events cannot be understood otherwise. Classic examples are people who, as a result of brain injury, are unaware of the fact that they can see or that the left half of the world exists or think their leg is a foreign entity not part of their own body. The oddest fact about such syndromes is that such patients sometimes are completely unaware of their problem and cannot understand it when it is explained to them (Oliver Sacks is a great source of such case histories).

The Problem for the Insanity Defense

Back to Goleman. He writes "Even if there is a biological basis for a lack of empathy in some cases..."

I hope that the fundamental problem with the quote is now clear. The consensus of the scientific community is that for any behavior, personality trait or disposition, there is always a biological basis. There are fundamental brain differences between Red Sox fans and Yankees fans, or between those attracted to Tom Cruise or Nicole Kidman. There is some brain state such that it is being a Red Sox fan.

So whenever somebody says, "My brain made me do it," they are telling the truth.

The Soft Bigotry of Medical Evidence

As matters currently stand, however, certain brain differences are privileged over others. Say Jane and Sally are both accused of a similar crime, but Jane has a known brain "abnormality" that correlates with criminal behavior, but Sally has no such brain data to point to. They may likely face different sentences.

However, the difference between Jane and Sally may have more to do with the state of our scientific understanding than anything else. If Sally is predisposed to crime in some way, then it must be because of some difference in her brain. At the very least, if you were able to take a snapshot of her brain during the moments leading up the crime, there would be some difference between her brain and the brain of Rebecca, who had the opportunity to commit the crime but chose not to, because the act of choosing is itself a brain state.

The effect is to discriminate between people based, not on their actions or on their persons, but based on current medical knowledge.

A problem without an easy solution

I think that most people prefer that the legal system only punish those who are responsible for wrongdoing. If we exclude from responsibility everybody whose actions are caused by their brains, we must exclude everybody. If we include even those who clearly have little understanding or control of their own actions, that seems grossly unfair.

I don't have any insight into how to solve the problem, but I don't think the current standard is workable. It is an exceptionally complex problem, and many very smart people have thought about it very hard. I hope they come up with something good.

New research on understanding metaphors

Metaphors present a problem for anybody trying to explain language, or anybody trying to teach a computer to understand language. It is clear that nobody is supposed to take the statement, "Sarah Palin is a barracuda" literally.


However, we can imagine that such phrases are memorized like any other idiom or, for that matter, any word. Granted, we aren't sure how word-learning works, but at least metaphor doesn't present any new problems.

Clever Speech

At least, not as long as it's a well-known metaphor. The problem is that the most entertaining and inventive language often involves novel metaphors.

So suppose someone says "Sarah Palin is the new Harriet Miers." It's pretty clear what this means, but it seems to require some very complicated processing. Sarah Palin and Harriet Miers have many things in common. They are white. They are female. They are Republican. They are American. They were born in the 20th Century. What are the common characteristics that matter?

This is especially difficult, since in a typical metaphor, the common characteristics are often abstract and only metaphorically common.

Alzheimer's and Metaphor

Some clever new research just published in Brain and Language looked at comprehension of novel metaphors in Alzheimer's Disease patients.

It is already known that AD patients do reasonably well on comprehending well-known metaphors. But what about new metaphors?

Before I get to the data, a note about why anybody would bother troubling AD patients with novel metaphors: neurological patients can often help discriminate between theories that are otherwise difficult to distinguish. In this case, one theory is that something called executive function is important in interpreting new metaphors.

Executive function is hard to explain and much about it is poorly understood, but what is important here is that AD patients are impaired in terms of executive function. So they provide a natural test case for the theory that executive function is necessary to understand novel metaphors.

The results

In this study, AD patients were as good as controls at understanding popular metaphors. While control participants were also very good at novel metaphors, AD patients had a marked difficulty. This may suggest that executive function is important in understanding novel metaphors and gives some credence to theories based around that notion.

This still leaves us a long way from understanding how humans so easily draw abstract connections between largely unrelated objects to produce and understand metaphorical language. But it's another step in that direction.


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M AMANZIO, G GEMINIANI, D LEOTTA, S CAPPA (2008). Metaphor comprehension in Alzheimer’s disease: Novelty matters Brain and Language, 107 (1), 1-10 DOI: 10.1016/j.bandl.2007.08.003

Neuroscience that matters

Science, like any other human activity, is subject to trends and fashions. Some are brief fads; others are slow waves that wash through society. For the last decade or two, cognitive neuroscience has been hot -- particularly neuroimaging.

A pretty typical example of cognitive neuroscience appears in this recent piece by the New York Times about research into the brain basis of sarcasm, which I read because I've been considering starting some work on sarcasm.

I generally don't like the media coverage of cognitive neuroscience, since it often acts surprised that human behavior is the result of activity in our brain. This particular article did not have that problem, but it still suffered from failing to answer the most important question any article has to answer.

The Right Parahippocampal Gyrus detects Sarcasm. So What?

The punch line of the article was that a neuroimaging study found the right parahippocampal gyrus to be active in sarcasm detection. Why this is important is left to the reader to decide.

So why is it?

In a lecture last spring, Randy Buckner distinguished between two types of cognitive neuroscience. 

In one, neuroscience techniques (patient studies, fMRI, single-cell recording, etc.) are used as behavioral measures. The goal of that type of research is to better understand human behavior. For instance, you might use fMRI to see if different brain regions are used in interpreting sarcasm and irony, which would suggest that the two phenomena are truly distinct.

The other kind of cognitive neuroscience uses the techniques of neuroscience to better understand how the brain produces the behavior in question. For instance, what computations to the neurons perform such that a person can perceive sarcasm? 

I am sympathetic to both types of cognitive neuroscience, though I tend to feel that there are very few human behaviors we understand well enough to seriously explore their neural instantiations (the basic phenomena of sensory perception are the only clear candidates I can think of, though basic memory processes might also make that list). You can't reverse-engineer a product if you don't know what it does. 

Interpreting Cognitive Neuroscience

In terms of the sarcasm article, it wasn't clear what this study adds to our understanding of what sarcasm is.  So I don't think it counts as the first type of cognitive neuroscience. 

Is it the second type? Some part of the brain must be involved in detecting sarcasm, so discovering which part of the brain it is in and of itself doesn't tell us much about implementation. Finding out that Sprint's national HQ is in Overland Park, KS, doesn't, by itself, tell you very much about Sprint, other than that it has an HQ, which you already probably guessed.

That doesn't  mean it's without information. Based on what you know about Overland Park, KS -- its tax regulations, local worker pool, lines of transportation and communication, etc. -- you might derive a great deal of information about how Spring works. But, unfortunately, the Times article didn't tell us much useful. I certainly don't know enough about the right  parahippocampal gyrus to really tell much of a story.

This is not a criticism of the journal article, which I haven't yet read. I'm actually pretty happy somebody is working on this issue. I just wish the Times had told me something useful about their work.

You like video games, but does your brain?

According to CBC in Canada:

Men are more rewarded by video games than women on a neural level, which explains why they're more likely to become addicted to them.

In other words, men like video games more because their brains like them more. Since only one's brain can like or dislike something, this could be rewritten: Men like video games more because they like video games more.

It's hard to blame CBC entirely for this one. I haven't tracked down the article itself, but the abstract remarks:

Males showed greater activation and functional connectivity compared to females in the mesocorticolimbic system... These gender differences may help explain why males are more attracted to, and more likely to become "hooked" on video games than females.

This is hard to parse, and given the authors work at Stanford Medical School, I'm inclined to give them the benefit of the doubt. However, the way this is phrased seems to have the natural order of investigation backwards. Men are more likely to be addicted to video games than are women. Given they show these particular brain differences during video game playing, we can make some intelligent guesses as to what those parts of the brain do.

Once we understand those parts of the brain much, much better than we do today, we may actually have a good structural model that explains this gender difference. That may be what the authors of the study meant, and they may spell this out in the full article. However, CBC's statement that men are more likely to get addicted to video games because they are "more rewarded on the neural level," is both repetitious and obvious.

See the original CBC article here.

The algebraic mind

The brain is a computational device. There may be some cognitive scientists out there who disagree with that statement, but I don't think there are many. There is much less agreement on what type of computational device it is.

One possibility is that the brain is a symbol-processing device very much like a computer. A computer can add essentially any two numbers using the same circuitry. It does not have one microchip for adding 1 + 1 and a different one for adding 2 + 2. It has a single algorithm that can be applied to any arbitrary number (assuming the computer can represent that number -- obviously there are numbers too large for any modern machine to handle).

One of the big mysteries of the brain is that it is unclear how to make a symbol-processing/algebraic device out of neurons. This has led many schools of thought, such as Connectionists, to deny that the brain can do symbol-processing or works anything like a digital computer (see Marcus's The Algebraic Mind for some blow-back). On the flip side, folks like Randy Gallistel have argued that if we don't know how to implement read/write memory into neurons (a related question), then there is a gaping hole in our knowledge about neurons.

This all comes to mind in relation to some work done in the last decade on barn owls. Barn owls locate their prey via both sight and sound, and neuroscientists have located the area of the brain where these two signals are combined. If you put prism goggles on a barn owl so that it's vision is offset (e.g., everything looks like it's 10 degrees left of where it actually is), the two signals get distorted at first, but eventually the neural map that represents location according to the ears shifts so that it's in sync with the the visual map.

As a computer programmer, the obvious thing to do would be to just add 10 degrees to the auditory signals across the map. However, that's not what the brain does. This can be shown by putting barn owls into goggles that shift only part of the field of vision. Only the auditory signals for that region of space shift. That strikes me as very non-algebraic in nature (not that a computer programmer couldn't achieve this effect, but why would she write that ability into the code. Keep in mind that barn owls didn't evolve to wear prism goggles).

That said, there's no reason that all the brain must compute things algebraically. Perceptual systems may be unusual in that respect. Still, as very little is known about how the brain computes anything, this example is very interesting.

For those interested in the barn owl details, check out:

Knudsen, E.I. (2002). Instructed learning in the auditory localization pathway of the barn owl. Nature, 417, 322-328.

What is neuroimaging good for?

On page 32 of the November/December issue, Seed Magazine reports that in July of 2007

Neuroscientists seeking to discern whether culture affects the human brain examined those of a group of Americans and Nicaraguans as they watched different hand gestures specific to their respective cultures.

Hopefully, this is not what said neuroscientists (no reference is given) were actually trying to do, because fMRI is very expensive (it typically costs hundreds of dollars an hour just to rent the machine), and you wouldn't really need to do an experiment to answer this question.

I think it's fairly obvious that people respond differently to language-specific hand gestures (for one thing, they are more likely to respond to them). If people respond differently, then their brains should also respond differently. To suggest otherwise means that you believe that the difference in behavior is due to either (1) an immaterial soul that controls that can engage in activities independently of the body, or (2) these behaviors are controlled by some organ of the body outside the brain.

These are both logically possible hypotheses, but the research over the last few centuries makes them so unlikely to be the case that unless you have a really, really good reason to suspect that the brain is not involved in interpreting hand gestures, then it's not really worth the incredible cost of fMRI to answer this particular research question.

Seed is a decent, informative magazine, so the fact that they let this slip is just more evidence of how pervasive this thinking is.