• fMRI studies tell us what’s true of brain activation on the average, but we’re nowhere near the point where fMRI scans have diagnostic value at the level of individual subjects. Put another way, you may be able to tell that people with ADHD have somewhat different neural responses than people without ADHD on average, but you can’t tell whether someone has ADHD or not by looking at their individual brain activation.
• The functional implications of specific differences in brain activation are not always clear. If schizophrenics show more activation in frontal brain regions than healthy controls, is that a good or bad thing? Are the increases reflective of the underlying disorder, or do they represent the brain’s attempt to compensate for the underlying deficit? We just don’t know at this point.
• Scientists and journalists alike are too quick to draw what Poldrack has called the “reverse inference“, arguing that a specific cognitive function must be involved in a certain task on the basis of the spatial location of activation. For example, many researchers who observe increased amygdala activation in response to a particular stimulus are quick to suggest that people are engaging in emotional processing, when in fact the amygdala may be activated by many other types of processes. There just isn’t enough evidence to support most reverse inferences.
• For all of the above reasons (and others), the people selling various fMRI-related services–e.g., “neuromarketing” firms that purport to tell major companies how people “really” feel about their brands–are basically selling snake oil.

Anyway, it’s a good piece, so give it a read. Poldrack is widely respected in the field of cognitive neuroscience for his thoughtfulness and methodological rigor, so it’s always worth paying attention to what he has to say on such matters.

[hat-tip: MindHacks]

While I’m sure the engine isn’t quite as flexible or powerful as the demo makes it seem (presumably Wolfram only asks questions he knows Wolfram Alpha has a good answer to), there’s clearly a lot of functionality already built in. What really blows me away in this demo is the ability to instantaneously plot the relation between arbitrary variables–in Wolfram’s example, the correlation between national GDP and railway length for European countries. Wolfram Alpha is built on Mathematica, so assuming that some of Mathematica’s statistical functions make it in (e.g., linear regression), it’ll make for a pretty awesome toy.

Of course, all this looks like it’ll require a good deal more computing power to serve up than your average Google query, so we’ll see how well Wolfram Alpha’s servers survive the onslaught that’s sure to accompany its arrival next week.

The neuroimaging in python (NIPY) project is an environment for the analysis of structural and functional neuroimaging data. It currently has a full system for general linear modeling of functional magnetic resonance imaging (fMRI).

This strikes me as a great project for a number of reasons (see this page for more):

• The existing free software packages for fMRI analysis (or at least the two I’m moderately familiar with) have limitations that are pretty hard to live with. SPM is about as close to an industry standard as there is, but has a hideously clunky GUI, depends on expensive proprietary software (MATLAB), and lacks integration with other environments/languages. FSL is very powerful, but also lacks interoperability, and in practice, I’ve found it hard to build complex models with FSL.
• Speed. NIPY is built on SciPy/NumPy, an increasingly popular set of Python libraries for scientific computing. Much of the SciPy/NumPy code is just a wrapper for C++/Fortran libraries that do the heavy lifting. So in theory, NIPY could be very fast (though Matlab is comparable for many operations. For a nice comparison of different numerical analysis packages, see this page).
• Open source / total interoperability. In theory, SPM and FSL are both “open” to varying degrees. But as the NIPY developers note, in practice, relatively few people actually make substantial contributions to the SPM or FSL codebase. Moving to a high-level language that’s easier to learn and develop in could do a lot to increase the level of community support for any package.
• The language. I can’t see myself ever contributing much to the SPM codebase precisely because I find programming in Matlab to be about as pleasant as pulling teeth. That’s not because I’m a terrible programmer; I have a fair amount of experience with a number of other languages. It’s because Matlab isn’t really a programming language. There’s limited or non-existent support for any number of operations that are a single call away in Python or R. And if the functionality you want doesn’t exist, you’ll probably have to write it yourself. Whereas Python has freely available packages for just about everything. And the language just makes sense. If you’re going to build a new package for fMRI analysis, it’s not a bad idea to build it in a language that’s actually fun to program in.
• Great support. NIPy has great developers and institutional support (the project is maintained by the Brain Imaging Center at Berkeley), and seems likely to stay funded for the foreseeable future.

So what’s the downside? Well, the software clearly isn’t ready for prime-time yet. The developers themselves counsel you not to use it for any serious data analysis. But there’s already a reasonable amount of functionality, and it’s generally well-documented. Give it another year or two and NIPy should start to siphon users away from SPM and FSL. I’ll certainly be happy to make the switch.

Merck paid an undisclosed sum to Elsevier to produce several volumes of a publication that had the look of a peer-reviewed medical journal, but contained only reprinted or summarized articles–most of which presented data favorable to Merck products–that appeared to act solely as marketing tools with no disclosure of company sponsorship.

The journals in question–at least 14 of which go by the “Australasian journal of…” moniker–look and read like peer-reviewed journals, but aren’t. They’re apparently just bound collections of ads for drugs like Merck’s Fosamax.

The Scientist article is really worth a read. It’s like something out of The Onion, except the funny drains out of it when you realize that literally thousands of physicians have received copies of “The Australasian Journal of Bone and Joint Medicine” or its other Australasian cousins over the past few years.

Elsevier, of course, has responsible and contrite things to say about the episode:

A spokesperson for Elsevier, however, told The Scientist, “I wish there was greater disclosure that it was a sponsored journal.” Disclosure of Merck’s funding of the journal was not mentioned anywhere in the copies of issues obtained by The Scientist.

The Elsevier spokesperson said the company wasn’t aware of how many copies of the Australasian Journal of Bone and Joint Medicine were produced or how the publication was distributed in Australia, but noted that “the common practice for sponsored journals is that doctors receive them complimentary.” The spokesperson added that Elsevier had no plans to look further into the matter.

The bitter irony is that Elsevier, along with the other major academic publishers, have spent the last few years ceaselessly lobbying against the open access movement, on the grounds that open access journals can’t be trusted to maintain the high quality of peer review that the  commercial publishers provide. Any guesses as to whether Elsevier will rethink that stance following this fiasco?

Much more on this story over at Peter Suber’s open access blog…

In a nutshell, the authors scanned a group of dieting participants as they viewed and rated a series of foods that varied in their taste and health value. The dieters were classified into “self-control” (SC) and “no self-control” (NSC) groups based on their behavior during the task. The SC participants rejected foods that were unhealthy even if they liked those foods, whereas the NSC participants based their decisions to accept or reject foods based almost entirely on their taste value.

The imaging results tell a very similar story to the one Rangel’s group at Caltech has been promoting for a while now. To summarize:

• Ventromedial PFC (VMPFC) activation shows stronger responses to foods participants accept than foods they reject. In Hare et al’s terminology, it represents the “goal value” of the food.
• VMPFC likes tasty foods in all participants, but only likes healthy foods in SC participants.
• When trials that required self-control (i.e., those that offered tasty but unhealthy foods) were binned based on whether participants successfully exercised self-control (rejecting the item) or failed to exercise self-control (accepting the item), both groups of dieters showed activation in dorsolateral prefrontal cortex (DLPFC). But the SC dieters showed more activation.

So far so good. These are nice results, and while I don’t know that they’re Science-worthy, they’re at the very least consistent with the idea that (to put it simplistically) VMPFC tells us what we like, and DLPFC tells us whether or not we’re going to choose what we like. But of course, that interpretation (which shows up in the title of the paper) implies a stronger claim, namely, that DLPFC actually modulates the VMPFC representation. And here’s where things get a bit wobbly.

The first analysis Hare et al present to try and make the case that DLPFC and VMPFC are actually talking to each other is a simple correlational analysis demonstrating that DLPFC and VMPFC are inversely related across SC participants. Meaning, self-controllers who show relatively more DLPFC activation also show relatively less VMPFC activation.

While this first result is interesting, it’s not very convincing, for a couple of reasons. One is that there often are very large individual differences in global activation in fMRI studies, meaning that some people just systematically show more activation than others in regions that are task-positive, and more deactivation in regions that are task-negative. VMPFC and DLPFC fit the bill here, in that the former was strongly deactivated and the latter was strongly activated. So one would like to see some evidence of specificity here. Is this association selective to the DLPFC-VMPFC circuit, or are similar inverse correlations found between very diffuse brain networks? And similarly, is the correlation the authors report specific to self-control trials, or does it also show up for non self-control trials? The authors only report the former, and one would like to know that the latter didn’t hold (i.e., you shouldn’t see a correlation that’s supposedly related to self-control in a condition where there’s no need for self-control!).

A second and more serious concern is that the presence of a between-subject correlation between two regions really says almost nothing about whether those two regions are talking to one another in a meaningful way. What Hare et al want to argue is that, on a trial-by-trial basis, when DLPFC kicks in, VMPFC is downregulated, resulting in a behavioral change. In other words, changes in DLPFC activation cause changes in VMPFC activation. But demonstrating that people who show more activation in DLPFC on average also show less activation in VMPFC on average isn’t the same thing. There are any number of ways you could get a negative between-subject correlation between two regions without any within-subject correlation whatsoever. One trivial example I alluded to above is that some people might just be more engaged in the task than others. DLPFC and VMPFC tend to show a negative correlation in all kinds of tasks; one plausible interpretation for this is that people who pay more attention to the task will show more activation in “task-positive” regions and more deactivation in “task-negative” regions. So you could very well get this effect for free, no self-regulation required.

In any case, Hare et al go on to report a second “functional connectivity” analysis. Unlike the above correlational analysis (which, unfortunately, some people also refer to as a functional connectivity analysis), the functional connectivity analysis was conducted over time rather than over participants. In other words, Hare et al were looking for regions in which activation tended to covary with a “seed” region of interest (in this case, DLPFC). The rationale for this type of analysis is that if two regions tend to coactivate, it’s reasonable to suppose that there might be a causal relationship between them (though articulating that relationship is not so easy).

The big problem with functional connectivity analysis is that it’s very difficult to test whether the correlation between two regions differs reliably across conditions. Unfortunately, that’s often exactly what we want to know. In this case, what Hare et al want to show is that the correlation between DLPFC and VMPFC exists specifically during trials that require self-control (i.e., unhealthy foods), and isn’t always there (which would argue against a self-control-specific explanation). So they perform what’s called a psychophysiological interaction (PPI) analysis. The basic idea here is that you add a term into your model that codes for the interaction between the experimental variables you care about (e.g., healthy vs. unhealthy trials) and the activation in the seed region. (Statistically, this is just the product of the two variables, after controlling for their main effects.) You can then interpret any regions you identify through this analysis roughly as “regions that show a stronger correlation with the seed region in one condition than another”. In this case, Hare et al identify a number of regions that show functional connectivity with DLPFC.

Sounds good, right? If it’s this easy, why doesn’t everyone use PPI analysis? Unfortunately, there’s a big technical problem, which is that the BOLD response (the signal that fMRI detects) is kind of slow, and lags behind neuronal activation for several seconds. Without getting too deep into the details, what this basically means is that if you run a standard PPI analysis, as implemented in some fMRI packages, you actually aren’t identifying regions that covary with neural activation in your seed region. Instead, you’re identifying regions in which activation correlates with the delayed hemodynamic response in your seed region. Which, to put it bluntly, makes it very difficult to have any idea what you’re really looking at.

The solution some people have adopted to this problem is to use a very complicated deconvolution approach to essentially try and figure out what neural activity must have been like several seconds before the response you observed. Once you’ve done that, you then use that estimate of neural activity in your PPI analysis rather than the observed signal itself. After that, you can interpret the results in the relatively straightforwad way I suggest above, i.e., you can identify regions that show changes in functional connectivity with your seed region as a function of condition.

If this all sounds like black magic to you, you’re not alone. While opinions certainly vary, mine, for what it’s worth, is that PPI analyses are close to worthless. You have to make so many convoluted (no pun intended) assumptions about what activation must have been like to produce the observed signal, and what activation will probably be like if we just multiply this indicator variable by this time-series and pretend that everything remains perfectly stationary when we reconvolve it, and what the shape of the hemodynamic response is in all the other regions we’re correlating with the seed ROI, that it’s virtually impossible to come away feeling confident that you know what your results reflect. So, on purely methodological grounds, I think it’s reasonable to express a good deal of skepticism about any paper that bases its strongest claim on a very convoluted technique that really hasn’t been adequately validated.

Having said that, opinions do vary, and some people might feel perfectly comfortable with Hare et al’s analysis, had it produced the expected result–namely, that DLPFC activation correlations with VMPFC activation during evaluation of unhealthy foods, but not otherwise. But Hare et al don’t actually show that. What they find, instead, is that DLPFC is functionally connected to a number of other frontoparietal regions. You might think this to be a deal-break for the hypothesis; but the authors are persistent, and instead suggest that “DLPFC might modulate the vmPFC through its effect in a third region, such as IFG/BA46.”

It’s not immediately clear why this second hypothesis should be necessary; after all, the PPI analysis is acausal. It doesn’t tell you that DLPFC caused activation in VMPFC, it just tells you that the two are correlated. If there really was any sort of relation between DLFPC and VMPFC, however many nodes it was mediated by, you would still expect it to show up in the first analysis. If it doesn’t, you might want to conclude that any effect, however indirect, is relatively weak, and probably can’t account for the large differences in mean levels of activation in these regions.

In any case, to test their prediction, Hare et al then conduct a second PPI analysis, using the IFG region that was functionally connected with the original DLPFC seed as the new seed (minimal rationale for this choice is provided, and there were other available candidates, so it’s pretty clear this was a fishing expedition). This time they get lucky: the third region (IFG) was in fact functionally connected to the VMPFC. So Hare et al conclude that, indeed, “vmPFC was functionally connected to the left DLPFC through a two-node network”. Hypothesis confirmed!

In sum, the best evidence the authors have for their claim that “Self-Control in Decision-Making Involves Modulation of the vmPFC Valuation System” (the paper’s title) is that they were able to find a third region that appeared to be functionally connected to both DLPFC and VMPFC using some very methodologically convoluted analyses and a rather unprincipled approach to region selection. That’s my take on it, at least; I leave it to you to decide whether or not to believe the result.

Having said all that, I hasten to point out that I don’t think this is a bad study overall. Other than the connectivity analyses, the results are pretty compelling, and represent a nice addition to the growing literature (much of it from Rangel’s lab) highlighting the VMPFC as a central component of the brain’s valuation system. It’s just that Hare et al never really provide any convincing evidence for their central claim–a claim that, one suspects, is what got the paper accepted in Science (along with a credulous reviewer or two, perhaps).

• Act like a cowboy
• Play chess in the dark
• Scrub its own back in the shower
• Talk on a tin can telephone
• Stuff a turkey
• Break a pinata
• Declare war on the neighborhood
• Master R
• Build a Ferrari out of jelly beans

On its face, writing a book doesn’t seem to be a high priority in psychology. Very few psychologists can claim to have an authored book on their vita, and these select few individuals still typically list books under a separate heading well below the almighty “Peer-Reviewed Journal Articles” section. I can count on one hand (well, maybe two) the number of times another psychologist has said something to me along the lines of “you should really read so-and-so’s book”. Books don’t play much of a role in day-to-day psychological research, and if anything, many researchers seem to harbor a slight contempt for them. Psychologists typically write books for laypersons, so that research-wise, the level of detail often leaves much to be desired. When psychologists want to know about fancy new experiments, they read fancy new research articles in journals like JEP and Psych Science; when they want to get a bird’s-eye view of a field, they read review articles in journals like Psych Review and Psych Bulletin. Books like Stumbling on Happiness or The Blank Slate may make for great reading before bed, but they’re rarely cited as a primary source in research articles (with a few notable exceptions, e.g., Antonio Damasio’s “Descartes’ Error”, which everyone and their grandmother cites).

Now, given academic psychologists’ general apathy toward authored books, you might expect that the authors of popular books on psychology would tend to be writers first and foremost, and that well-known researchers would rarely if ever take time out of their schedule to write a 400-page volume. That would be my intuition, at least; but it turns out to be the wrong one. In fact, a disproportionate number of popsci psychology books are written by very eminent researchers. People like Dan Wegner (The Illusion of Conscious Will), Dan Gilbert (Stumbling on Happiness), Dan Schacter (Searching for Memory), Paul Bloom (Descartes’ Baby), Steven Pinker (a zillion bestselling books on language and/or evolution), Antonio Damasio (several books nominally about old dead white guys but really about emotion), Michael Gazzaniga (The Mind’s Past), and Joseph LeDoux (The Emotional Brain) have all had extremely productive, well-respected research careers independently of their popular output.

The interesting question, of course, is why. Why are popular psychology books more likely to be written by eminent researchers?  Broadly speaking, I think there are three classes of explanations (I’m sure I’m leaving many out, though). One possibility is that popular books aren’t actually more likely to be written by famous psychologists; rather, psychologists are more likely to become famous if they’re written popular books. This would be interesting if true inasmuch as it would suggest that the conventional wisdom is wrong: rather than focusing single-mindedly on publishing peer-reviewed journal articles, young academics might do better to divert at least some of their time to popularizing psychology by writing full-length books (then again, most of the aforementioned authors wrote their first book after receiving tenure). Of course, this still wouldn’t explain why psychologists become famous after writing popular books. Perhaps there’s a familiarity effect: psychologists who publish popular books are likely to have their names repeated widely and often, which might subsequently bias researchers to assign more weight to those authors’ empirical research, regardless of its actual merit. Or perhaps hiring committees at schmancy universities use popular fame as an explicit criterion when evaluating candidates (though that seems unlikely, because many of the people listed above–e.g., Wegner, Gilbert, and Schacter, all currently at Harvard–published their major popular works after moving to elite universities).

Another possibility is that there’s a kind of selection effect: lots of psychologists publish (or try to publish) popular books, but only books by famous psychologists are widely read. Other things being equal, one would expect that books by Harvard professors sell more copies than books by professors at third-tier schools, so a bias may emerge at either the publishing stage (famous psychologists are more likely to get book deals) or the consumer stage (people are more likely to buy books that say Harvard or Yale on the cover).

The final possibility, which I personally find most interesting, is that there’s something characterological about good researchers–or at least, a subset of good researchers–that makes them more likely to publish popular works. There are a number of traits that come to mind here. One is simply intelligence: while popular science books are often maligned for their lack of depth, synthesizing a broad research literature into a clear, readable package can be a considerable feat of intellect. Another relevant dimension is creativity and/or the ability to see the big picture. Researchers who are good at integrating diverse ideas maybe both more likely to produce good research and more motivated to paint a discipline with broad strokes in a popular book. Or, it could be a matter of drive: writing a book takes persistence and hard work, and persistent, hard-working people are likely to be more productive in general. Of course, one could also cast this all in a more negative light, as simply a result of egomania: if you’re highly driven to be respected and admired by your academic peers, you might also be driven to show the public at large how cleverly you can write a book.

If I had to put money on it, I’d guess the reason book authors tend to be respected researchers is a little of column B (selection) and a little of column C (character). In theory this is a pretty easily testable hypothesis (the question being, essentially, what factor(s) mediate the relationship between (a) book authorship and (b) research eminence)–in fact, there’s a sizeable literature on the personality of highly successful scientists (e.g., Dean Simonton’s work). In practice, you’d probably be hard-pressed to get Steven Pinker to sit down with you for two hours of psychological testing. Which is fine, because it’s really not that informative a question anyway. The bottom line is just that there’s a interesting discrepancy between what many academic psychologists think about popular psychology books (negatively, or not at all) and what they think about the people who tend to write those books (positively).

The “cognitive neuroscience of religion” phrase is used early on in the piece:

“This is a new science that’s emerging,” says Patrick McNamara, an assistant professor of neurology at Boston University School of Medicine. “You might call it the cognitive neuroscience of religion. This is definitely a new discipline, and it’s poised to make some major new discoveries.”

The article itself alternates haphazardly between covering genuinely interesting developments in the neuroscience of belief and spirituality (e.g., the recent focus on Buddhist meditation) and focusing on the beliefs of neuroscientists who happen to harbor religious or mystic worldviews themselves. The author, Richard Monastersky, doesn’t acknowledge anywhere in the piece that there’s a big difference between trying to understand the neural bases of religious belief and trying to justify one’s beliefs via neuroscience. Plenty of people are interested in the former; relatively few are interested in the latter. Yet Monastersky allocates the majority of time to the latter group. Some choice quotes:

Mr. Price also questions the reigning materialist concept of the mind, asking, “Why say that consciousness exists only inside a body?” Regarding subjective experience, he wonders, “Are we talking about some organ inside our skull, or are we talking about our connection with something outside ourselves? That connection outside ourselves can include a spiritual connection.”

…

Other scientists are asking similarly heretical questions. Jeffrey M. Schwartz, a research professor of psychiatry at the University of California at Los Angeles, has been treating people with obsessive-compulsive disorders to counter their urges through focused attention of the mind. Scans of his patients’ brains reveal that such mental therapy can alter the behavior of their brains, something that could not happen if the mind emerged entirely from the brain, he says.

“It is a tragedy of history that materialism became the regnant paradigm,” says Dr. Schwartz, who rails against the contemporary norms that divide science and religion (see related story, Page A18). There are a growing number of scientists, he says, who “believe that this separation of science from religion is a cultural artifice.”

In Monastersky’s defense, he does give some airtime to opposing (and sensible) views from some of the field’s luminaries:

Stephen F. Heinemann, president of the Society for Neuroscience and a professor in the molecular-neurobiology lab at the Salk Institute for Biological Studies, in La Jolla, Calif., echoed many scientists’ reactions when he said in an e-mail message, “I think the concept of the mind outside the brain is absurd.”

…

Michael S. Gazzaniga, a professor of psychology at the University of California at Santa Barbara and a leading neuroscientist who serves on President Bush’s Council on Bioethics, says that essentially all brain biologists accept the materialist view of the mind. “I would say that 98 or 99 percent of people in the business think that,” he says.

You’d think 98 or 99 percent would come across as a pretty big number, yet somehow the article still left me with the same uncomfortable sense of ambiguity found in much of the pro-ID literature (though I’m certainly not suggesting Monastersky, a widely-acclaimed science writer, is pro-ID): the sense that somehow, somewhere, there’s a genuine controversy, and researchers need to give equal time to both sides. Which of course they don’t, as the Gazzaniga quote makes abundantly clear.

One would expect that the brain sciences would be among the last places deeply religious people would venture. To my mind it seems it would be very difficult for most people to continue to hold non-materialist views of the mind after a year or two of staring at images of localized activation increases or dealing with patients with focal lesions and equally selective behavioral deficits. When I look around at my colleagues, I don’t see the “growing numbers of religious and nonreligious researchers who support” the view of a non-material mind. What I do see is a growing number of researchers who want to understand why it is that so many people around them maintain religious beliefs, and for the first time feel they have the tools to do it at the level of the brain.