New, Voodoo-Free fMRI Technique

MIT brain scanners Fedorenko et al present A new method for fMRI investigations of language: Defining ROIs functionally in individual subjects. Also on the list of authors is Nancy Kanwisher, one of the feared fMRI voodoo correlations posse.

The paper describes a technique for mapping out the "language areas" of the brain in individual people, not for their own sake, but as a way of improving other fMRI studies of language. That's important because while everyone's brain is organized roughly the same way, there are always individual differences in the shape, size and location of the different regions.

This is a problem for fMRI researchers. Suppose you scan 10 people and show them pictures of apples and pictures of pears. And suppose that apples activate the brain's Fruit Cortex much more strongly than pears. But unfortunately, the Fruit Cortex is a small area, and its location varies between people. In fact, in your 10 subjects, no-one's Fruit Cortex overlaps with anyone else's, even though everyone has one and they all work exactly the same way.

If you did this experiment you'd fail to find the effect of apples vs. pears, even though it's a strong effect, because there will be no one place in the brain where apples reliably cause more activation. What you need is a way of finding the Fruit Cortex in each person beforehand. What you'd need to do is a functional localization scan - say, showing people a big bowl of fruit - as a preliminary step.

Fedorenko et al scanned a bunch of people while doing a simple reading task, and compared that to a control condition, reading a random list of nonsense which makes no linguistic sense. As you can see, there's a lot of variation between people, but there's also clearly a basic pattern of activation: it looks a bit like a tilted "V" on the left side of the brain:

These are the language areas of each person. (Incidentally, this is why fMRI, despite its limitations, is an amazing technology. There is no better way of measuring this activation. EEG is cheaper but nowhere near as good at localizing activity; PET is close, but it's slow, expensive and involves injecting people with radioactivity.)

Fedorenko et al then overlapped all the individual images to produce of map of the brain showing how many people got activation in each part:

The most robust activations were on the left side of the brain, and they formed a nice "V" shape again. These are the areas which have long been known to be involved in language, so this is not surprising in itself.

Here's the clever bit: they then took the areas activated in a large % of people, and automatically divided them up into sub-regions; each of the "peaks" where an especially large proportion of subjects showed activation became a separate region.

This is on the assumption that these peaks represent parts of the brain with distinct functions - separate "language modules" as it were. But each module will be in a slightly different place in each person (see the first picture). So they overlapped the subdivisions with the individual activation blobs to get a set of individual functional zones they call Group-constrained Subject-Specific functional Regions of Interest, or GcSSfROIs to their friends.

Fedorenko et al claim various advantages to this technique, and present data showing that it produces nice results in independent subjects (i.e. not the ones they used to make the group map in the first place.)

In particular, they argue that it should allow future fMRI studies to have a better chance of finding the specific functions of each region. So far, experiments using fMRI to investigate language have largely failed to find activations specific to particular aspects of language like grammar, word meaning, etc. which is unexpected because patients suffering lesions to specific areas often do show very selective language problems.

Does this relate to the voodoo correlations issue? Indirectly, yes. The voodoo (non-independence error) problem arises when you do a large number of comparisons, and then focus on the "best" results, because these are likely to be wholly, or partially, only that good by chance.

Fedorenko et al's method allows you to avoid doing lots of comparisons in the first place. Instead of looking all over the whole brain for something interesting, you can first do a preliminary scan to map out where in each person's brain interesting stuff is likely to happen, and then focus on those bits in the real experiment.

There's still a multiple-comparisons problem: Fedorenko et al identified 16 candidate language areas per brain, and future studies could well provide more. But that's nothing compared to the 40,000 voxels in a typical whole-brain analysis. We'll have to wait and see if this technique proves useful in the real world, but it's an interesting idea...

ResearchBlogging.orgFedorenko, E., Hsieh, P., Nieto Castanon, A., Whitfield-Gabrieli, S., & Kanwisher, N. (2010). A new method for fMRI investigations of language: Defining ROIs functionally in individual subjects Journal of Neurophysiology DOI: 10.1152/jn.00032.2010

I'm Bipolar, You're a Schizophrenic

Over at Comment is Free, Beatrice Bray takes issue with this cartoon (for those who don't follow British politics, the guy on the right is trying to win an election at the moment.)

The use of the word "psychotic" was offensive. You may think this political correctness gone mad, but if you are ill, or have been, you need words to describe your experience to yourself and to others. If for you these words are negative, you will hate yourself. Language can make or break your happiness. That is why mental health activists do not like psychiatric terms being used as abuse...
Hmm. Fair enough... but why would a sick person care if people insulted their illness? Cancer patients don't seem to be offended when things are called "a cancer on our society" or whatever, because not many cancer patients like cancer.

Maybe the clue is later on:
And please allow individuals an identity apart from their illness, so always say "a person with schizophrenia" rather than "a schizophrenic".
So the problem is that unlike cancer patients, the mentally ill aren't seen as people separate from their illness. That is a serious issue - but getting offended by someone using "psychotic" as a term of abuse surely only reinforces the idea that sufferers identify with it?

In fact, a lot of people with psychiatric illnesses don't follow Bray's advice when talking about themselves. "Bipolar", for example, is commonly used to describe people, rather than their illness - and many bipolars do this... bipolar people... people with bipolar disorder. Whatever.

On Google, "I'm bipolar" gets 247,000 hits and "I am bipolar" gets 235k, so that's about 500k in total. "I have bipolar" gets 576k - so "having" and "being" are about equally popular.

Likewise for schizophrenia, "I have schizophrenia" gets 174k, but "I'm schizophrenic" gets 136k, and "I am schizophrenic" 31k - almost equal again. "I'm a schizophrenic" gets 465k, mainly because of a movie, however if you exclude those you still get over 100k.

So if mental health activists want to reform the way we talk about mental illness, it's not just the "them" of the general public who need bringing into line. But I've never been convinced that changing what words people use about things like this is a good way of changing minds: it's an easy way to create the appearance of doing so, but actually changing minds is hard, and I don't think language reform is even a good first step.

You don't change minds by telling people to please change, you make them change by showing them examples of why they're wrong. If your aim is to convince that schizophrenia happens to people and doesn't define them, a movie like A Beautiful Mind (or more recently perhaps Shutter Island, although it takes a lot of artistic license with the symptoms of psychosis) is worth a thousand word-changes.

Neural Correlates of Being a Total Bad-Ass

A new fMRI study in PLoS reports Differential Brain Activation to Angry Faces by Elite Warfighters, the elite warfighters being US Navy SEALs.

SEALs are indeed pretty elite. This being a British blog, I wouldn't want to say that they're the world's elitest naval special forces unit. That's the British Special Boat Service. But they could still kill you ten times before you knew they were there (unless you're in the Special Boat Service.)

Anyway, San Diego researchers Paulus et al scanned 11 SEALs and 23 healthy civilian men during an emotional face matching (originally developed by Hariri et al) that involved seeing happy, angry, and fearful faces.

Such tasks are very popular in neuroimaging at the moment because looking at faces of people expressing strong emotions reliably activates emotion-related brain areas, without needing to actually induce emotions in your volunteers which can cause practical problems, i.e. people getting scared and maybe panicking in the MRI scanner. Whether studying emotional-face-induced activation is a valid substitute for studying emotion-induced activation is an open question.

What happened? fMRI being a sensitive way of measuring human brain activation, they found some differences between the two groups in neural responses to seeing the faces:
elite warfighters relative to comparison subjects showed relatively greater right-sided insula, but attenuated left-sided insula, activation. Second, these individuals showed selectively greater activation to angry target faces relative to fearful or happy target faces bilaterally in the insula.
OK. So what does that mean?
These findings support the notion that elite warfighters... deploy greater neural processing resources toward potential threat-related facial expressions and reduced processing resources to non-threat-related facial expressions. This finding suggests that rather than expending more effort in general, elite warfighters show more focused neural and performance tuning, such that greater neural processing resources are directed toward threat stimuli and processing resources are conserved when facing a nonthreat stimulus situation.
So the message is that SEALs are better at focusing on threats and don't get distracted by benign background stuff. Although apparently this is only true of their insula, not an area known for its role in attention, and the threat was an angry face on a screen. But that aside, this is not very surprising given that they're highly-trained soldiers.

But the unsurprisingness of this result is a problem. We don't need neuroscience to tell us that elite soldiers are good at detecting and responding to threats. That's rather obvious. I'd guess that most of them were pretty good at it before they got selected, and then they got even better with training. This must have something to do with the brain, because your brain is what allows you to learn stuff.

What we don't understand very well yet is how training (or other forms of learning) works, on a neural level, i.e. what the molecular and cellular mechanisms are. It would be really nice to find out. Unfortunately, fMRI studies like this are unable to tell us that, because they only study the very last stage in the process, the final product.

This is in no way a problem with this paper alone, and it's no worse than many other articles. The same issue applies to many neuroimaging studies of abnormal states like depression or, as I've posted about previously, psychological trauma. Such results can form the basis for investigations into mechanisms, and as ways of testing theories, but on their own, finding that abnormal brains react in abnormal ways is not, in itself, very useful.

ResearchBlogging.orgPaulus, M., Simmons, A., Fitzpatrick, S., Potterat, E., Van Orden, K., Bauman, J., & Swain, J. (2010). Differential Brain Activation to Angry Faces by Elite Warfighters: Neural Processing Evidence for Enhanced Threat Detection PLoS ONE, 5 (4) DOI: 10.1371/journal.pone.0010096

The Hunt for the Prozac Gene

One of the difficulties doctors face when prescribing antidepressants is that they're unpredictable.

One person might do well on a certain drug, but the next person might get no benefit from the exact same pills. Finding the right drug for each patient is often a matter of trying different ones until one works.

So a genetic test to work out whether a certain drug will help a particular person would be really useful. Not to mention really profitable for whoever patented it. Three recent papers, published in three major journals, all claim to have found genes that predict antidepressant response. Great! The problem is, they were different genes.

First up, American team Binder et al looked at about 200 variants in 10 genes involved in the corticosteroid stress response pathway. They found one, in a gene called CRHBP, that was significantly associated with poor response to the popular SSRI antidepressant citalopram (Celexa), using the large STAR*D project data set. But this was only true of African-Americans and Latinos, not whites.

Garriock et al used the exact same dataset, but they did a genome-wide association study (GWAS), which looks at variants across the whole genome, unlike Binder et al who focussed on a small number of specific candidate genes. Sadly no variants were statistically significantly correlated with response to citalopram, although in a GWAS, the threshold for genome-wide significance is very high due to multiple comparisons correction. Some were close to being significant, but they weren't obviously related to CRHBP, and most weren't anything to do with the brain.

Uher et al did another GWAS of response to escitalopram and nortriptyline in a different sample, the European GENDEP study. Escitalopram is extremely similar to citalopram, the drug in the STAR*D studies; nortriptyline however is very different. They found one genome-wide significant hit. A variant in a gene called UST was associated with response to nortriptyline, but not escitalopram. No variants were associated with response to escitalopram, although one in the gene IL11 was close. There were some other nearly-significant results, but they didn't overlap with either of the STAR*D studies.

Finally, one of the STAR*D studies found a variant significantly linked to tolerability (side effects) of citalopram. GENDEP didn't look at this.


The UST link to nortriptyline finding is the strongest thing here, but for citalopram / escitalopram, no consistent pharmacogenetic results emerged at all. What does this mean? Well, it's possible that there just aren't any genes for citalopram response, but that seems unlikely. Even if you believe that antidepressants only work as placebos, you'd expect there would be genes that alter placebo responses, or at the very least, that affect side-effects and hence the active placebo improvement.

The thing is that the "antidepressant response" in these studies isn't really that: it's a mix of many factors. We know that a lot of the improvement would have happened even with placebo pills, so much of it isn't a pharmacological effect. There are probably genes associated with placebo improvement, but they might not be the same ones that are associated with drug improvement and a gene might even have opposite effects that cancel out (better drug effect, worse placebo effect). Some of the recorded improvement won't even be real improvement at all, just people saying they feel better because they know they're expected to.

If I were looking for the genes for SSRI response, not that I plan to, here's what I'd do. To stack the odds in my favour, I'd forget people with an moderate or partial response, and focus on those who either do really well, or those who get no benefit at all, with a certain drug. I'd also want to exclude people who respond really well, but not due to the specific effects of the drug.

That would be hard but one angle would be to only include people whose improvement is specifically reversed by acute tryptophan depletion, which reduces serotonin levels thus counteracting SSRIs. This would be a hard study to do, though not impossible. (In fact there are dozens of patients on record who meet my criteria, and their blood samples are probably still sitting in freezers in labs around the world... maybe someone should dig them out).

Still, even if you did find some genes that way, would they be useful? We'd have had to go to such lengths to find them, that they're not going to help doctors decide what to do with the average patient who comes through the door with depression. That's true, but they might just help us to work out who will respond to SSRIs, as opposed to other drugs.

ResearchBlogging.orgBinder EB, Owens MJ, Liu W, Deveau TC, Rush AJ, Trivedi MH, Fava M, Bradley B, Ressler KJ, & Nemeroff CB (2010). Association of polymorphisms in genes regulating the corticotropin-releasing factor system with antidepressant treatment response. Archives of general psychiatry, 67 (4), 369-79 PMID: 20368512

Uher, R., Perroud, N., Ng, M., Hauser, J., Henigsberg, N., Maier, W., Mors, O., Placentino, A., Rietschel, M., Souery, D., Zagar, T., Czerski, P., Jerman, B., Larsen, E., Schulze, T., Zobel, A., Cohen-Woods, S., Pirlo, K., Butler, A., Muglia, P., Barnes, M., Lathrop, M., Farmer, A., Breen, G., Aitchison, K., Craig, I., Lewis, C., & McGuffin, P. (2010). Genome-Wide Pharmacogenetics of Antidepressant Response in the GENDEP Project American Journal of Psychiatry DOI: 10.1176/appi.ajp.2009.09070932

Garriock, H., Kraft, J., Shyn, S., Peters, E., Yokoyama, J., Jenkins, G., Reinalda, M., Slager, S., McGrath, P., & Hamilton, S. (2010). A Genomewide Association Study of Citalopram Response in Major Depressive Disorder Biological Psychiatry, 67 (2), 133-138 DOI: 10.1016/j.biopsych.2009.08.029

Terrifying Electric Shock Treatment

Frankenstein op saved me from suicide!!!

That's the front page headline on today's News of The World, a popular British Sunday tabloid which would probably be the worst newspaper in most other countries, but which by British standards is only slightly below average.

TV actress Bev Callard tells how she suffered an episode of severe clinical depression, and was given ECT or as the News put it "terrifying electric shock treatment" which "plunged her into a scene of horror beyond anything TV scriptwriters could have imagined." Although it's never made clear what the horror was: according to Callard her twelve sessions of shock therapy was the only thing which worked to help lift her out of her suicidal state and, as the headline says, it may even have saved her life.

She was worried about the possible side effects, including memory problems, and describes experiencing difficulty learning her lines initially, but she says, she always managed to do so successfully.

The print version includes some sensible comments from a doctor who points out that ECT is effective as a last resort in cases of depression that don't respond to drugs alone. He also comments that "Bev is so brave to talk about this".

She is, but she shouldn't have to be: talking about depression shouldn't be a matter of being brave, any more than talking about any other illness. The reason it takes courage is that unlike with other diseases, admitting to suffering from a mental illness is liable to land you on the front page of the papers.

Attitudes to Mental Illness

Ever wondered what the British public think about mental illness?

Well, the British government has, and the results of the 2010 Attitudes to Mental Illness Survey are out. I'm never sure how much faith to put in such data because what people are willing to say they think, and what they really feel, are not the same.

So while it's encouraging that only 20% of people say they agree with the statement that "Anyone with a history of mental illness should be excluded from taking public office", it would be naive to think that the other 80% would really be equally likely to vote for someone with a psychiatric history when push came to shove. We've moved on since McGovern, but maybe not all that much.

Worse, a lot of the questions are dubious. One asks whether you agree that "Mental hospitals are an outdated means of treating people with mental illness", the 'right' answer, that gets counted as a nice positive attitude, being to agree. I disagree, not least because inpatient treatment for depression helped my grandfather hugely when he was a young man. If that means I have a bad attitude to the mentally ill, so be it. I don't think it does.


Another item asks "What proportion of people in the UK do you think might have a mental health problem at some point in their lives?" The approved answer, as Neuroskeptic readers may have guessed, was 1 in 4. But only 16% of the British public picked that option from the multiple-choice quiz. Most thought it was much lower:

How silly of them...or maybe not. There has in fact never been a study of the lifetime prevalence of mental illness in Britain. Studies in other English-speaking countries, such as the US and New Zealand, have repeatedly shown lifetime prevalence rates of 50%, or higher, for mental illness according to DSM-IV criteria. But these figures and these criteria have been credibly accused of overstating the proportion of people with a genuine psychiatric illness, maybe greatly so. There's a lot to say on both sides of this debate, but the point is that the question is open. Expecting the public to know the answer, when the experts don't, is rather unfair.

However, interestingly enough, this very survey asked whether respondents had ever suffered mental illness themselves. How many had? There's a 4 in it, but it's not 1 in 4, it's 4%.

I strongly suspect this is an underestimate. Some people are ill and don't know it or don't admit it. People with mental illness might be less likely to participate in the study. There'll be people will get ill at some point in their lives after they fill in the survey. And the format of the question was a bit odd (see page 64 and see what you make of it). But still, this is another point of data for the great prevalence debate.

The proportion of people with mental illness ultimately depends on how you define "mental illness". I don't think anyone has an entirely satisfactory definition, so any attempt to pin down the lifetime prevalence is problematic until we sort that out, but if I had to put it a number on it, it would be about 1 in 10 in Western countries.

I'm no expert on this topic so take this with a big pinch of salt. Still, I'd find it very hard to accept a figure much lower than this, from personal experience if nothing else. I'd be open to the idea that the true figure is much higher, but this would mean that tens of millions of British people are going around getting mentally ill and never receiving treatment, and it would take some very strong evidence to convince me of that.

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