Small Gray Matters

If you read only one neuroimaging paper this week, make it this paper in PLoS Biology by Hagmann and colleagues. It’s a really remarkable combination of technical wizardry, creativity, and pretty, pretty pictures of the brain. What Hagmann et al have done is assemble rock-solid evidence that a network of brain regions located primarily in posterior midline cortex serves as the structural ‘core’ of the broader cortical connectivity map. Whereas most brain regions show sparse connectivity, typically talking to only a handful of other nearby regions , regions in the structural core are much more densely connected with one another and with other regions throughout the cortex. Hagmann et al. support this basic conclusion with five or six different analyses, each using a different network topology metric (herein lies the technical wizardry), but the bottom line is that they obtain much the same result no matter how they looked at the data.

What’s really striking about this study is that it’s arguably the best example to date (or at least, the best example that I know of–I don’t follow this literature closely) of the power that new structural MRI techniques provide to assess in vivo brain connectivity in humans. In this case, the authors used diffusion spectrum imaging, a technique that lets the researcher construct whole-brain images of white matter fiber density and then (using some sophisticated post-processing) plot the trajectories of those tracts. The authors defined a connection between regions as the presence of at least one fiber with end-points in both regions (the more terminating fibers, the stronger the connection). Given an N x N matrix (where N = 998 different brain regions in this case!) of connectivity strengths between regions, they could then apply the suite of network topology metrics to produce those pretty, pretty figures.

Lest you think this all sounds like black magic (as I suspect a reviewer or two did), Hagmann et al. provide evidence that these structure-based connectivity maps (a) are reliable across hemispheres and scanning sessions; (b) degrade gracefully in the presence of noise; (c) conform nicely to connectivity data obtained from more conventional anatomical tract tracing techniques in monkeys; and (d) are quantitatively very similar to maps obtained using functional resting-state data in the same participants.  The sheer breadth of analysis in this paper is really quite striking, and you’d have to nit-pick to find faults with the methodology.

That said, there’s one critical question that these results don’t really address, and that’s what the findings mean from a functional standpoint. it’s easy to make the general argument that a small-world network structure is A Good Thing ™ for the brain to have; but the (arguably) more interesting question is why the hubs are located in these particular brain regions. The fact that a majority of the hubs (including posterior cingulate, precuneus, lateral parietal cortex, and superior temporal sulcus) are components of the brain’s “default” or task-negative network is clearly no coincidence. So what functional purpose does this pattern of connectivity serve? Why do those regions that are maximally activated at rest have the broadest pattern of connectivity with the rest of the cortex? Or is it perhaps the other way around, so that these regions develop their default status precisely because they receive inputs from multiple sources, and are ideally situated to mediate transitions between different task sets? Clearly, many questions remain to be addressed (warning: a horribly cliched ending to this post is imminent), but the Hagmann et al. paper will probably turn out to be a pretty important piece of the puzzle (see, I warned you).

Hat-tip: Neurophilosophy.

There’s an interesting discussion (at least, it looks interesting; so far I’ve only read two of the posts, and have skimmed the rest) going on over at The Immanent Frame about the so-called “cognitive revolution” predicted by David Brooks in a recent New York Times Op-Ed piece. Brooks’ argument, in a nutshell, is that emerging neuroscience findings are going to reverse the recent trend towards what he terms ‘hard-core materialism’, and will eventually combine with mystical views to “lead to new movements that emphasize self-transcendence but put little stock in divine law or revelation”. That’s a pretty bold claim, and one that, as far as I can tell, Brooks provides no good support for. Both the basic thrust of the argument and its central flaw are nicely summarized in the following quote:

Over the past several years, the momentum has shifted away from hard-core materialism. The brain seems less like a cold machine. It does not operate like a computer. Instead, meaning, belief and consciousness seem to emerge mysteriously from idiosyncratic networks of neural firings. Those squishy things called emotions play a gigantic role in all forms of thinking. Love is vital to brain development.

This paragraph is interesting, because it provides a nice summary of recent trends in neuroscience (everything but the first sentence is true) while simultaneously betraying a deep misunderstanding of the materialist worldview. Brooks holds up constructs like meaning, belief, and consciousness as if they were antithetical to the “hard-core” materialist worldview; but should it surprise anyone that meaning and belief emerge from “idiosyncratic networks of neural firings”? Do materialists quake in their boots at the thought that love plays a role in brain development? It shouldn’t, and they don’t. A good materialist (not just a ‘hard-core’ materialist, whatever that means, but any good one) takes these observations as self-evident. If you believe, as materialist neuroscientists do, that the brain is the proximal source all thought, feeling, and action, then you must believe that meaning and belief arise through the actions of neurons chattering with one another; you must believe that the nurturing effects on love on human development are mediated by changes in the brain. For Brooks, the notion that love might influence brain development appears to come as an epiphany; but really, what alternative is there? Does he suppose that the real materialists are the ones who would deny the existence of meanings, beliefs, consciousness, and love? If so, there aren’t any. Maybe there used to be, briefly, in the 1980s heyday of eliminative materialism; but those materialists were philosophers (e.g., the Churchlands), not neuroscientists, and it appears they’ve long seen the light and backed away from their stronger claims (e.g., that terms like “belief” are just conveniences of folk psychology, and don’t map onto anything real).

This fundamental misunderstanding of the central tenet of materialism gets played out repeatedly in Brooks’ op-ed (despite the fact that it’s only one page long). Consider the following assertion, which Brooks seems to take as evidence against ‘militant’ materialism:

First, the self is not a fixed entity but a dynamic process of relationships. Second, underneath the patina of different religions, people around the world have common moral intuitions.

These points are hard to dispute, but they certainly don’t constitute an argument against “militant atheism” or “hard-core materialism”, unless one takes these militant atheist materialists to be people who not only don’t believe in meaning, belief, consciousness, and love, but also think the self is a fixed entity and that there’s no such thing as a moral intuition. Now, I haven’t met any of these people, but they sound like fascinating individuals, if a bit odd.

Or take the following statement, which accurately describes ongoing research in certain areas of cognitive science, neuroscience, and genetics:

Researchers now spend a lot of time trying to understand universal moral intuitions. Genes are not merely selfish, it appears. Instead, people seem to have deep instincts for fairness, empathy and attachment.

Or this one:

Scientists have more respect for elevated spiritual states. Andrew Newberg of the University of Pennsylvania has shown that transcendent experiences can actually be identified and measured in the brain (people experience a decrease in activity in the parietal lobe, which orients us in space). The mind seems to have the ability to transcend itself and merge with a larger presence that feels more real.

From a descriptive standpoint, “Brooks gets the research essentially right,” as Kelly Bulkeley notes in a commentary over on the SSRC blogs. But why Brooks thinks such findings will soon lead to militant materialism falling by the wayside, I don’t know. I would have thought precisely the opposite, and so it seems, does Bulkeley:

To begin with, neuroscientist Andrew Newberg’s brain-imaging studies of meditation, highlighted by Brooks, can easily be used to confirm rather than disprove a materialist worldview. Newberg’s finding that people who are meditating have measurable decreases in parietal lobe activity fits perfectly with the idea advanced by Richard Dawkins and others that religious experience is a product of altered or abnormal brain functioning. Contrary to the popular view that Newberg’s research supports religion, it can readily be taken as supporting the “militant atheism” Brooks wants to reject. The mind may, as Brooks says, have “the ability to transcend itself,” but we didn’t need Newberg’s SPECT scanners to tell us that.

This conclusion seems exactly right to me. After all, it would surely be better for non-materialists if it turned out that religious experiences didn’t have some identifiable neural correlates. “Look,” one could imagine them saying then, “visual perception, motor control, and speech production… all of these things depend on the brain. But transcendental experiences don’t!” Unfortunately, it doesn’t work out that way. Religious experiences turn out to have underlying neural representations, just like every other psychological state or process that’s been investigated. That includes meaning, belief, consciousness, and yes, love. Such findings aren’t inconsistent with materialism; they’re necessary for materialism to hold. Why this simple observation baffles Brooks so, I don’t know.

Having said all that, I do think there’s one redeeming point to Brooks’ Op-Ed. I think he has it basically right when he suggests that “we’re in the middle of a scientific revolution” that’s going to have “big cultural effects”. But I suspect that he’s banking on the wrong revolution. Instead of modern neuroscience giving rise to “neural Buddhism”, what’s much more likely to happen is that, as our understanding of the brain increases and we learn more and more about precisely those aspects of human behavior and cognition that were once thought to be resistant to material explanation, it’ll become increasingly difficult for non-materialists to adhere to their dogmas in the face of reductive explanations. In a world where religious experiences are scientifically mysterious, a dualist worldview is defensible, because there’s no better explanation than “God did it”. In a world where such experiences unfold as, say, a sequence of attractor states in a temporoparietal network that mediates the experience of agency, one has a choice between “God did it” and “the brain did it”. My bet is that, for many (though certainly not all) people, the brain will beat God.

This week’s issues of Science and Nature each have very nice commentaries on the limitations of fMRI, a topic I’ve written about a few times before. The Nature piece is a review by Nikos Logothetis entitled “What we can do and what we cannot do with fMRI“. Logothetis is uniquely placed to comment on these matters; a very large chunk of what we know about the BOLD signal (the primary vehicle of fMRI studies) is due to his seminal work. While the review is pretty expansive (particularly for Nature, at 10 pages!) and somewhat technical, the take-home message is that the most serious limitations of fMRI are due to massive aggregation over distinct populations of neurons rather than to any technical limitations per se. Or, as he puts it much more eloquently:

The limitations of fMRI are not related to physics or poor engineering, and are unlikely to be resolved by increasing the sophistication and power of the scanners; they are instead due to the circuitry and functional organization of the brain, as well as to inappropriate experimental protocols that ignore this organization.

That’s not to say that all is lost, of course. On the whole, Logothetis is pretty optimistic about the value of fMRI, even going so far as to suggest that “MRI is currently the best tool we have for gaining insights into brain function and formulating interesting and eventually testable hypotheses”; it’s just that it’s not perfect by a long shot.  But anyway, there’s much more to the review than I can convey coherently in my current sleepy state, so if you have access to Nature, it’s definitely worth reading.

The Science piece (“Growing Pains for fMRI”) is a much lighter news article by Greg Miller, and it focuses mostly on a controversy that played out in the pages of the New York Times last year. The thumbnail sketch is  that one group of fMRI researchers did some very shoddy “research” on the way people view the different election candidates, and another (larger) group of researchers called them on it.  The exchange then led to a period of widespread soul-searching amongst cognitive neuroscientists, until ultimately, in March 2008, the Cognitive Neuroscience Society imposed a moratorium on publication of all fMRI data until a common set of guidelines for rigorous and ethical research conduct was agreed upon.  Ok, that last part is completely made up. But the point is that the article is a good read, and you should check it out if you can.  It’s not often you hear one scientist say that another scientist’s study was “really closer to astrology than it was to real science” (for the record, I agree with that assessment in this case).

In many areas of the social sciences and humanities, authored books are the pinnacle of scholarly achievement. That’s not to say that peer-reviewed journals don’t exist in fields like History and English Literature; they just don’t carry as much weight as books do (bad pun intended). If you want to receive tenure as a professor of History or English lit, you need to write at least one book. (At least, that’s what the few historians and literary folks I know tell me; it’s possible they’re stringing me along.)

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).

Seems like it’s been a while (over a year!) since I wrote anything in this space. I was originally going to use CNS ‘08 as an excuse to post something short and uninformative (again) about people wandering around poster halls looking lost, or seagulls eating pieces of fish tacos on the pier. But then I forgot. So instead I’ll babble a bit about what I’ve been doing over the past year:

• I got married.
• I published a few first author papers in reasonably good journals, and have a dozen or so other projects in various stages of rejection / submission / preparation / imagination. (It’s interesting how the number of projects you’re involved with magically balloons when you let yourself include manuscripts “in preparation” in the count.)
• I lined up a post-doc for next year (pending funding!) that I’m really excited about.
• I made a little bit of headway on my dissertation. Which is a nice way of saying I now know what the topic will be.
• I learned a lot of interesting things–some useful, mostly not.
• I picked up another musical instrument.
• I met twelve new people. I know, because I counted! No, just kidding. It’s more like fifteen.
• I visited some interesting places. Well, a handful, really. Where ‘handful’ means ‘two’.

This is a pretty standard list of things that could happen to a person over the course of a year, and you may be thinking to yourself that I lead a pretty uneventful academic life. Well, you’d be mistaken. Rest assured I’ve deliberately left out a good half dozen bullet points detailing my intricate dealings with petty dictators and rogue government agencies. One day soon I will tell you daredevil stories about high-altitude computation of paired t-tests that will fill your belly up with suspense and wonder. But that day is probably not today.

I’m in New York for the 2007 annual meeting of the Cognitive Neuroscience Society. CNS alternates between San Francisco and New York; this year it’s in the latter city. I suppose if you have to pick two cities to have a conference in, those are pretty good ones. Still, one of the things I like best about going to conferences is getting to explore cities I haven’t spent time in. Not so much of that this year. On the other hand, having less inclination to sightsee leaves more time for posters, talks, and socializing, and that’s not a bad thing either.

* * *

As always, there are too many posters to see. The CNS schedule of events doesn’t begin to approach SFN standards–the latter consisting of a CD’s worth of fully indexed and searchable abstracts, and five different books (one per day)–but if you do any sort of neuroimaging work, a much higher proportion of the abstracts are likely to interest you. I start every conference I go to by spending half an hour meticulously checking off all the posters I want to see at the next session. Then when that session rolls around I promptly discard my notes and drift aimlessly from aisle to aisle.

* * *

There are a lot of complaints this year about the quality of the poster halls here at the Sheraton New York. The halls are (a) maze-like; (b) dark; and (c) warm. It’s a safe bet that some small proportion of attendees enjoys this environment, but for those of us who (a) don’t have an exquisitely-tuned spatial navigation system, (b) aren’t vampires, or (c) don’t suffer from hyperthyroidism, it’s a little bit uncomfortable.

* * *

The drinks last night at the welcome reception started at $6.50 for a soft drink. $11.50 for a beer. When I asked the bartender why I couldn’t just have a cup of tap water for free, he shrugged in antipathy. I suppose it was more polite than saying “because it would undercut our bottom line, schmuck.” So I went down the street, bought a bucket, filled it with ice and water, and gave away free refreshments to all the thirsty neuroscientists. No, just kidding. I bent over and took it just like everyone else.

* * *

Memo to presenters: that signup sheet next to your poster isn’t real. Etiquette requires that after someone’s finished being bored by the intimate details of your presentation for fifteen minutes, they be provided with some way of expressing their joy and gratitude to you for furnishing them with a life-changing experience. They do this by signing up to receive a second iteration of your treatment in written form. Putting their name on your form completes all contractual obligations. There’s no requirement that you actually follow up and email them your poster. In fact, doing so only inconveniences your audience. Last time I came back from CNS I spent an entire morning hitting the ‘delete’ button. I could have been doing much more productive things, like brushing my teeth.

* * *

I’m slowly realizing that New York is an expensive place with terrible service. Take for instance this morning. I was standing on the corner outside the hotel when a nice man approached me and said he was an artist and that he could put a beautiful glossy sheen on my poster for just $80. So I gave him my poster and $80, and he said he’d be back in twenty minutes. Well it’s been 3 hours and I haven’t heard anything. When he comes back, I’m going to be very angry with him. Just wait till he sees what kind of customer evaluation I give him at the information desk.

* * *

Auditory perception, memory systems, emotion, and numerical processing. These are all important areas of research, and certainly worthy of inclusion in the poster sessions. But there’s no reason to be elitist. Cognitive neuroscience is a diverse field. I’ve been emailing the poster committee my suggestions for topics for several years, and I’ve yet to see any follow-through or receive a reply. What’s wrong, people? Too creative? Too novel? Don’t envy me just because I thought of having a symposium on brick-selective cortex and you didn’t. It’s not my fault you lack vision.

* * *

There’s a lot of talk at this conference about how the brain is this wonderfully clever device that lets us project ourselves effortlessly into the past and future, move forwards and backwards in time, etc. etc. It’s not entirely unlike that other device that smoothly whisks you from the seventeenth floor down to the atrium while you’re busy placing mental bets on the length of the coffee line. Between your brain and the elevator, there’s no dimension you can’t conquer! You’re a master of time and space! Then the doors open up and someone jams your shoulder into the wall as they rush by you. Looks like you’re a lowly grad student again, grasshopper.

* * *

After a long day spent milling around hundreds of posters made by hundreds of scientists, all as smart and creative as you, all working on equally interesting problems, it’s easy to get a little down on yourself. What’s the point, you might ask yourself. Why bother participating in science if the best any of us can ever hope for is to make a tiny, insignificant contribution to that great puzzle that is the human mind. And what’s so great about the human mind anyway, if it’s just the temporal analog of an elevator. You might as well be studying dirt. Dirt is less dynamic than the mind, but more tractorable.

* * *

If a neuroscientist gives a great keynote address at a conference and no one hears it because they’ve all skipped the morning session to go roam around lower manhattan, does she still get to put it on her vita?

The New York Times has an interesting article in today’s paper by Mary Jenkins covering a new federal program set to provide substantial raises in funding for a minority of graduate students in the sciences. The Pell-Mell Grants, a joint venture of the Federal Government, Pell Grant program, and Andrew W. Mellon Foundation, is projected to cost 8 billion dollars over the next twenty years. Needless to say, with that amount of money on the table, you’re going to see some strong opinions put forward about the program’s merit. The basic gist of the NYT’s article is that (not surprisingly) graduate students love it; established faculty members, not so much.

The really striking thing about the program is the sheer amount of money it throws at a select number of students—a projected 8,000 in 2014, with the number of awards gradually increasing over the next six years. It funds graduate students in natural science and engineering disciplines at a level up to $60,000 annually for three years, with applications renewable up to four times. Why the dramatic increase in funding over such a protracted period? From the article:

Critics complain that allowing graduate students to secure major funding for up to 12 years of predoctoral work will encourage complacency and clog up universities with ‘lifers’. Others see it is a necessary step if the US wishes to remain competitive with emerging Asian countries. Dr. Ron Sekubus, chair of the department of public policy at George Washington University, notes that without the funding, American universities would be forced to admit an ever-increasing number of international students in order to buffer against the loss of American students to more lucrative fields such as medicine and law. When international students complete their degrees, they are almost invariably unable to find legal work in the US, leading them to return to their home countries. The long-run outcome of this perpetual ‘brain drain’, Sekubus suggests, is that the US will fall in scientific productivity relative to rapidly-developing countries such as India and China.

When I ask him whether the government couldn’t just solve this problem overnight by allowing more trained foreign scientists to stay in the US once they’ve completed their doctorate, Sekubus’ responds aggressively. “Immigration is not the solution,” he says. “Increasing funding for American citizens via merit-based and non merit-based programs is the solution.”

The reasoning seems pretty straightforward. But as always, the story isn’t as clear cut as the above quote suggests. Here’s another relevant bit from the article:

Tovaz Shikarti, a program officer at the NIH, points out that high levels of predoctoral funding in the sciences make sense within the current cultural context:

“When we sat down to look at it, we couldn’t really understand why the top 5% American graduate students are getting paid less than the bottom 1% of American faculty. American culture is built on the promise of potential; it’s a foregone conclusion that this generation of top students is going to do some pretty remarkable things in a few years. The Pell-Mell grant program is our way of equalizing the situation by honoring the American tradition. You could think of this as an NBA draft for scientists.”

Others don’t see it that way. John Jacobson, a professor of history at The College of Wooster, complains. “I certainly don’t object to students making a livable wage. I was a graduate student once too. But when a first year physics graduate student at Wisconsin makes more than I do as an Associate Professor of Historical Arts at Wooster, I don’t think that’s right. My wife and I are giving serious thought to respecializing in materials science just so we can get a piece of the pie. It’s almost like the government’s goal is to get rid of the humanities and social sciences altogether.”

One of the caveats to the program is that the awards are highly selective–more so than existing NSF and NIH fellowships. There’s a three-stage selection process. The first two are fairly standard: First, would-be Pell-Mell grantees send in an application similar to the one required for the current NSF predoctoral fellowships. In fact, applicants to the NSF program are automatically entered into the Pell-Mell competition if they fill in several new fields on the NSF forms. Second, successful first-stage applicants are subjected to a still more rigorous screening, including close scrutiny of applicants’ transcripts, letters of recommendation, and current institution.

But it’s the final stage that sets the Pell-Mell grants apart from other programs. Successful applicants must not only demonstrate their academic prowess, but must also pass muster in the eyes of a newly-created Human Excellence Review Board (HERB). One of the novel requirements implemented by HERB is that applicants must designate a non-academic hobby as their “special skill”. The goal of this requirement is to encourage applications from well-rounded students with broad interests, instead of automatons who spend all day in the lab living and breathing one narrow discipline.

“What you list as your special skill is flexible,” says Tovaz Shikarti. “There’s no strict criterion our applicants have to live up to.” He notes that when the NIH conducted a limited test run with graduate students at Darthmouth College and the University of Pennsylvania, it received applications from people with skills like lizard hunting, karaoke, and cheese making. “There was even one trapeze swinger,” he says.

If this all sounds a little bit cock-eyed, don’t worry, the government is on top of that too.

When prompted as to whether the Pell-Mell program might not produce bad press for the NIH and NSF at a time when American scientists are complaining about flatlining funding, administrators demur. “We had a serious discussion about that at HERB,” says Aashish Patel, a board member. “Some people wanted to kill the program, to stub it out. But it’s not like we’re sitting around smoking up when we come up with these ideas. They’re serious policy proposals.”

Following in the footsteps several other science blogs, here’s a library card for smallgraymatters.com:

Select a few neuroimaging papers at random and you’re likely to come across a handful of statements in the introduction to the effect that the topic under study is of “increasing interest”. At conferences and research talks, you’ll sometimes see speakers invoke a familiar kind of figure that looks something like this:

That’s the number of citations in PubMed containing the terms ‘fMRI’ and ‘language’ in the abstract or title, plotted by year of publication. Figures like this purport to show that interest in a topic is increasing dramatically. Just look at that increase! In 1996, there were only 13 hits; by 2005, there were 99! It’s as clear as daylight that interest in the neural bases of language is increasing!

Of course, the poorly-kept secret is that fMRI didn’t exist twenty years ago, and wasn’t really widely adopted until the last few years. So it’s natural to see an increase in publications that study language using neuroimaging methods. You’d expect a similar increase for almost every other area of research. The more pertinent question is whether interest in a particular topic has increased disproportionately relative to the general increase in the use of fMRI over the last few years. Instead of plotting absolute numbers, what we want is something like this:

In the above figure, the pink line represents the number of papers with the terms ‘fMRI’ and ‘language’ in the title (the blue line in the first figure has now turned pink–sorry about the color confusion!). But now the additional (blue) line shows the number of papers that have just the term ‘fMRI’ in the abstract. The increase in language papers starts to look suspect, since it’s clear the increase in fMRI papers on language is essentially paralleled by the increase in fMRI papers in general. Here’s an even better representation:

That’s the proportion of PubMed studies with the terms ‘fMRI’ and ‘language’ in the title or abstract over the last few years relative to the total number of studies with just the term “fMRI”. As you can see, it’s a very different picture. It’s a small sample size, but there’s not much reason to think people are any more interested in studying language in 2006 than in 1998—at least, relative to interest in other topics that can be studied with fMRI.

So what to make of claims that research interest is increasing in topics X, Y, and Z? Well, in a sense those claims are true, since the total number of neuroimaging publications continues to rise fairly dramatically. But in the sense that researchers probably care about more—namely, the “if I have a magnet and I want to do a study, what’s a hot topic right now?” sense—most research topics can’t be on the rise, by definition (just like most people can’t be of above average intelligence). Moreover, the number of academic publications in general has increased pretty dramatically over the last few years, so it’s not even clear from the above just how much of the increase in the number of fMRI papers on language is due to greater adoption of fMRI as opposed to a more global increase in scientific research output.

Now, the point of this post isn’t just to malign a ubiquitous research tactic. One can’t really fault people for wanting to think their own research is more interesting than other people’s. I’ll be the first to confess I’ve inserted some rather disingenuous comments about how oh-so-fascinating my results are and how much they (should) mean to other researchers in my papers. It’s hard to motivate a paper without doing that to some degree, or even to get motivated to do the research in the first place. What the second graph above does point up though, is that the question as to what topics are ‘hot’ is an empirical one—and fortunately, one that can be relatively easily (though imprecisely) tested.

To generate the above graphs, I used data from PubMed. One of the many nice things about PubMed is that it has an API that allows you to access the database programmatically (in contrast to Google Scholar, which is inaccessible via API due to agreements between Google and the major publishers to keep it that way). So, in the interest of doing some trendspotting, I wrote a small Visual Basic program to quantify the emergence (or lack thereof) of real ‘trends’ in research. I used the search string “fMRI [tiab]” as the control—i.e., all articles containing the string “fMRI” in the title or abstract. This is a conservative approach since the standard PubMed search also searches article contents, resulting in a difference of an order of magnitude in hits (7000 vs. 160000). But the more conservative approach is likely more accurate, since any study that includes the term in its title or abstract is much more likely to report original fMRI data than studies that just mention the terms in passing.

This reference number (broken down by year) was then compared with the results of a series of more specific searches. Basically, for a variety of topics, I added a single search term like “language” or “emotion” to the basic search. Again, the stipulation was that only titles and abstracts be searched. The ratio between the specific and the general term was then plotted for each year in order to highlight potential trends.

What do the results look like? Here are the ‘trends’ in neuroimaging for four major areas of research, broken down for the years 1996-2006:

What can we infer from the above figure? Well, just by eyeballing it, it looks like there’s a general trend toward relative increases in the number of papers on emotion, working memory, and attention, and no change for language. Statistical tests reveal that the three positive trends are significant (p < .05 for all three). So there’s at least some evidence that there are in fact trends in neuroimaging research (assuming there isn’t some alternative explanation, e.g., abstracts just getting longer and consequently mentioning more terms). The key point is that this kind of information can’t be gleaned just by looking at the first figure presented in this post. Absolute increases in publication count aren’t particularly informative. In contrast, when you use a control condition—though in this case, an admittedly crude one—you can feel a little more confident about the conclusions you’re able to draw. Naturally, this is a small sample size, and as I mentioned, the search is highly conservative (obviously, more than 46 fMRI articles on emotion were published in 2006!). But it’s likely that the results are a good representation of what’s out there, and that we can safely generalize to the many papers that use fMRI to study these topics but didn’t use the exact term in the abstract.

What about other ways of carving up the literature? Here’s the breakdown by sensory modality:

Doesn’t look like much is going on, and indeed none of the regression slopes are statistically significant. But at least this analysis is somewhat reassuring given the increases seen above for working memory, attention, and emotion: it’s clearly not as though all search terms are being mentioned more frequently in more recent fMRI abstracts.

Here’s one last figure (this could obviously go on for a very long time) plotting the trajectory of publication count in a few less-studied domains:

The trends for ‘social’, ‘reward’, and ‘decision making’ are significant here, but the trendline for pain isn’t. Social neuroscience research in particular appears to be emerging as a prominent domain of fMRI research, more than doubling its relative share of the literature between 2005 and 2006, though it’s still a relatively small field.

In evaluating the figures above, there are several caveats to keep in mind. One major limitation of this trendspotting approach is that it’s not well-suited to quantifying trends in more fine-grained areas of research, because there may only be a handful of studies per year, resulting in a pretty unreliable measure. Then again, claims that one small niche of research within the broader field of cognitive neuroscience is on the rise probably aren’t that interesting to begin with. If a particular topic was studied by 2 people in 2000 and 6 in 2005 (instead of a projection of, say, 4), you might want to wait a while before hopping on the bandwagon.

Another obvious limitation is that the procedure I used to generate these graphs was extremely simplistic. One can easily imagine more sophisticated approaches that control much more tightly for potential confounds (e.g., tier of journal, mean abstract length, etc.) and use better quantitative measures than the simple ratio I used above. That’s ok though; the point I want to make isn’t that this particular set of graphs provides a particularly accurate insight into the state of the field of neuromaging. Rather, the point is that scientific trends can be studied empirically just like anything else, and there’s a massive amount of data freely available for mining. Entire journals are devoted to tracking and discussing current research fads (see the ‘Trends in…’ series), but it’s unclear whether the editors at such outlets make their decisions on the basis of quantitative information. Conversely, from an author’s perspective, knowing what’s hot isn’t just a matter of curiosity—careful attention to trends could conceivably increase the rate of acceptance of one’s publications.

As a side note, if anyone wants to suggest possible searches for trends they’d like to see quantified, feel free to leave a comment below or to email me. I may release the VB program at some point, but it’s in no shape to see the light of day at the moment. Of course, you can always head over to PubMed and enter search terms manually.

Mind Hacks offers up this humorous vignette for your entertainment:

There’s a lovely typo in a 1976 paper from the Journal of Neurology, Neurosurgery, and Psychiatry that reports on a study about epilepsy after surgery. Check out the last sentence of the abstract …

I’ll spare you the suspense (but read the abstract anyway!): an undisclosed subset of patients in the sample were fortunate enough to suffer from “temporal love trauma”. You might have thought temporal love trauma to be an unusual disorder (it’s certainly much rarer than temporal lobe trauma), but that’s an empirical question, and the empirical answer is you’d be wrong. At least according to Google Scholar, which assures us quite confidently that temporal love epilepsy is a well-documented condition:

http://scholar.google.com/scholar?q=%22temporal+love%22&hl=en&lr=&btnG=Search

Marvel that it is, Google Scholar also gives us a rare glimpse into the symptoms of a related but even more mysterious disorder: frontal love epilepsy. Consider the title of the following paper, cited in the reference section of a book by one M. Cherkes Julkowski:

Burgess, PW & Shallice, T (1996). Response suppression, initiation, and strategy use following frontal love lesions. [For reasons that are presently unclear to me, I wasn't able to locate this article in the primary literature.]

Or the following helpful tip from a set of lecture notes on functional neuroanatomy, now mysteriously disappeared from their original Cambridge home (a conspiracy?):

Theories of frontal love function have superseded ARAS theory in explaining personality differences.

The lecture notes then go on to say that empirical studies have shown that the personality traits of extraversion and agreeableness depend in large part on one’s frontal love capacity. Illustrations are provided in the text. If you don’t believe me, you can go and see for yourself. Wait, I forgot: they’re no longer online. How unfortunate.

I imagine there are also cases of parietal love lesions or occipital love epilepsy (blinded by one’s feelings?) out there, waiting to be discovered. It really is a great time to be alive and doing science…