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...

Fedorenko, 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

Head Trip

A quick post to recommend the 2007 book Head Trip, by Jeff Warren.

Head Trip is about "24 hours in the life of your brain": sleeping, waking, and everything in-between, from lucid dreaming to daydreams and hypnosis.

Warren gives a nice overview of current research and theory along with the story of his personal quest to experience the full spectrum of conciousness.

The book's most interesting chapter is called "The Watch". It's about that hour or two of wakefulness which occurs in the middle of the night, between the first sleep and the second sleep. You know the one...right? Neither did I, but apparently, this makes us a bit weird, historically speaking.

Warren says that until the era of artificial lighting and alarm clocks, sleep was segmented. It was common for people to sleep twice each night, with a bout of awakeness in the middle. This nocturnal alertness wasn't quite like daytime waking, though: it was more relaxed, less focussed, carefree. Our modern sleep pattern, then, is kind of compressed, with the two sleeps pushed together until they merge into one.

There are two lines of evidence for this. Writings from the pre-modern era routinely make reference to "first sleep" and "second sleep", and in many languages, although not modern English, there were special words for these periods and the wakefulness between. This is according to historian A. Roger Ekirch in his history of night-time, At Day's Close (review, Wiki), a book I really want to read now.

On the other hand, there's the findings of sleep psychiatrist Thomas Wehr, in particular his classic 1992 study called In short photoperiods, human sleep is biphasic. Wehr took healthy American volunteers and put them in an artificial environment with a controlled light cycle, such that there were only 10 hours of brightness per day. (That's 6 hours less than we get on average, even in winter, due to artificial light.) Within a few weeks "their sleep episodes expanded and usually divided into two symmetrical bouts, several hours in duration, with a 1-3 h waking interval between them."

This is pretty freaky. Sleeping all night seems natural, normal and healthy: if we wake up before we need to get up, we're dismayed and we call it insomnia. Maybe this is a modern invention like electric lighting. There's something amazing and also a bit disturbing about this idea. As Warren says, it's like finding out that your house "is really the exposed bell-tower of a vast underground cathedral".

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.

Of Yeast and Men

Nature reports on the Dissection of genetically complex traits with extremely large pools of yeast segregants.


Ehrenreich et al have a new way of mapping the genetic basis of complex traits in yeast, "complex" being what geneticists call anything which isn't controlled by one single gene. They dub their approach "Extreme QTL mapping". This suggests images of geneticists running experiments atop Everest, or perhaps collecting blood samples from lions with their bare hands, but actually

Extreme QTL mapping (X-QTL) has three key steps. The first is the generation of segregating populations of very large size. The second is selection-based phenotyping of these populations to recover large numbers of progeny with extreme trait values. This can be accomplished, for example, by selection for drug resistance or by cell sorting. The final step is quantitative measurement of pooled allele frequencies across the genome.

The basic idea is to cross breed two strains of yeast to generate lots of different hybrid strains each with a random selection of DNA from each "parent". Then, you put all the hybrids under some kind of selective pressure - for example, by adding the toxin 4-NQO to their dish.

Some yeast are more or less resistant to 4-NQO, and this trait is largely determined by genetics. So after a while, the vulnerable hybrids will die out and only the most highly resistant strains will be left in the 4-NQO dish to reproduce. It's a quick and dirty form of selective breeding. Finally, you can compare the genetics of the 4-NQO resistant hybrids to a control group of hybrids who didn't get any toxins, using a GWAS. Any genetic differences are likely to represent 4-NQO resistance genes.

Using this method, Ehrenreich et al found no less than 14 4-NQO resistance variants. That includes two replications of previous findings, and 12 new ones. Collectively, the genes explained

59% of the phenotypic variance in 4-NQO sensitivity in an additive model. Because we measured the heritability of this trait to be 0.84, the loci explained 70% of the genetic variance, indicating that we have explained most of the genetic basis of this trait with the loci detected by X-QTL.

In other words, they've found most of the genes with a substantial effect on 4-NOR resistance, but not all of them. (They then did the same thing for several other toxins). About 30% of the heritability is "missing". Compare that to most human complex traits, where the missing heritability is more like 95%-99% at the moment. For example, twin studies and similar find human height to have a heritability of about 0.8, and more than 40 genetic variants have been associated with height, but together they only explain 5% of the heritability.

Why is Neuroskeptic posting about yeast? Well, partly because we live in a yeast-based society. Without yeast, we would have no alcoholic drinks. I think it's important to acknowledge their contribution to our lives. But mainly because there's a lesson here for people interested in the genetics of complex traits in humans, like, say, personality, IQ, and mental illness.

Yeast resistance to toxins is about the most straightforwardly "biological" trait you could imagine. Finding its genetic basis ought to be easy. But it wasn't. It was...extreme. Ehrenreich et al had to breed and select yeast with extreme traits (e.g. extremely high resistance to toxins), and compare them to control yeast of the same ancestry, to find the genes, and they still had a good deal of missing variance.

If they'd had to work on a random bunch of yeast from the wild, they'd have had a lot more trouble. That's why previous yeast GWAS studies didn't get results as good as these. Yet when it comes to humans, we're indeed forced to use a random bunch of people from the wild. You can't selectively breed people.

You can breed, say, mice, but it takes a lot longer than with yeast. I think there have been a few studies breeding mice for a certain trait and then looking at their genetics but not with a great degree of success, even though the first thing every mouse researcher learns is that different strains of mice are very different (C57BL/6 mice, for example, are notoriously hard to handle and love biting people.)

This is bad news for human genetics, where the interesting traits are clearly a lot more complex, ill-defined, and hard to measure than in yeast. On the other hand, though, it's perhaps also rather reassuring, as it suggests that our failure to explain more than a few % of the heritability so far reflects technical limitations rather than because these traits just aren't as genetic as we think after all...

Ehrenreich IM, Torabi N, Jia Y, Kent J, Martis S, Shapiro JA, Gresham D, Caudy AA, & Kruglyak L (2010). Dissection of genetically complex traits with extremely large pools of yeast segregants. Nature, 464 (7291), 1039-42 PMID: 20393561

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.

Paulus, 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

How I Write

I thought I'd share some of the things I keep in mind when writing my posts. These are lessons I've learned through trial and error in the 18 months I've been blogging, and that I wish I'd been told when I started out.

In no particular order:

• Write little and often. I find that I'm most productive at the beginning and the end of a session of writing: in the middle, it's easy to lose steam and spend a long time doing very little. So I now generally write in regular short bursts (20 minutes or so). Each post will take as many bursts as it needs to be finished, which is usually 2 or 3, but sometimes more.
• Keep it brief. Two short posts are better than one long one, because a lot of people (e.g. me) just don't read long posts. At the moment, I aim for about 500 words per post with a maximum limit of 1,000 words. If that's not enough space, I'll split the ideas over multiple posts. This is easier to read, and I find it makes it easier to write too, once you get into the swing of it. Some might worry that this makes it impossible to express complex ideas, but I really don't think it does. You just need to express them clearly.
  
• Think, then write. You should know what you're going to write about before you start typing: it's hard to write and think at the same time. This is easier said than done, and often you'll think of new ideas while writing, so it's not an absolute rule. But you should know the major points you'll be making before writing.
• Don't start at the beginning. Don't write the first sentence first, spending ages reworking it until it's perfect, and only then move on to the second sentence. Write the basic skeleton first, no matter how badly it reads, and then tidy it up afterwards. It's a lot easier to do the tidying up once you know how it all fits together.
  
• If in doubt, leave it out. Some people would disagree with this, and it's ultimately a matter of personal style, but this is my rule: if I'm not sure how confident I am in something, or if I'm not sure it's interesting enough to bother with, I won't post it. If I'm not sure a paragraph is a good addition to a post, I'll cut it.

417 words... I'm done.

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.

Binder 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.

Social Learning in Antisocial Animals

In an unusual study with potentially revolutionary implications, Austrian biologists Wilkinson et al show evidence of Social learning in a non-social reptile.

Social learning means learning to do something by observing others doing it, rather than by doing it yourself. Many sociable animal species, including mammals, birds and even insects, have shown the ability to learn by observing others doing things. It's often seen as a distinct form of cognition, separate to "normal" learning, which evolved to facilitate group living. It's one of the things that everyone's favorite brain cells, mirror neurons, have been invoked to explain.

But if observational learning is a specifically social adaptation, then non-social animals would be predicted to lack this ability. One distinctly unfriendly species is the South American red-footed tortoise (Geochelone carbonaria). In the wild, they hatch from their eggs alone, and get no parental care; they live most of their lives without interacting with others.

Wilkinson et al found that red-footed tortoises can, nevertheless, learn by observation. They took four tortoises and got them to watch another "demonstrator" tortoise completing a difficult task: walking around an obstacle to get to some food (it's hard if you're a tortoise).

The observing animals all learned to do the task. In most cases, they walked around the obstacle to the right, which is what the demonstrators did, but sometimes they went left, showing that they were not simply copying the movements of the demonstrators. The wood chips on the floor of the floor of the cage were mixed up after each trial, to rule out the possibility that the tortoises were just following the smell of the demonstrator. None of four control tortoises, who got no demonstrations, managed to figure it out on their own.

The authors conclude that

The dominant hypothesis in this field claims that social learning evolved as a result of social living and therefore predicts that the tortoises would have difficulty with this task. They did not. The findings suggest that, in this case, social learning may be the result of a general ability to learn. Although the brain mechanisms that underlie the tortoises’ ability to learn socially remain unclear, it seems most likely that it is the product of a general learning mechanism that allows the tortoises to learn, through associative processes, to use the behaviour of another animal just as they would learn to use any cue in the environment.

This is a nice experiment, and the result is important: the idea that social learning is somehow evolutionarily and neurally "special" underlies a lot of modern social neuroscience. However, I'm not convinced that these tortoises can be accurately described as "non-social". Even the most anti-social species have to socialize in order to mate: no animal is an island. According to Wikipedia the red-footed tortoise has some quite elaborate (and hilarious) mating behaviours...

male to male combat is important in inducing breeding in redfoots. Male to male combat begins with a round of head bobbing from each male involved, and then proceeds to a wresting match where the males attempt to turn one another over. The succeeding male (usually the largest male) then attempts to mate with the females. The ritualistic head movements displayed by male red-foots are thought to be a method of species recognition. Other tortoise species have different challenging head movements....The unique body shape of the male redfooted tortoise facilitates the mating process by allowing him to maintain his balance during copulation while the female walks around, seemingly attempting to dislodge the male by walking under low-hanging vegetation.

Wilkinson, A., Kuenstner, K., Mueller, J., & Huber, L. (2010). Social learning in a non-social reptile (Geochelone carbonaria) Biology Letters DOI: 10.1098/rsbl.2010.0092

Why Do We Dream?

A few months ago, I asked Why Do We Sleep?

That post was about sleep researcher Jerry Siegel, who argues that sleep evolved as a state of "adaptive inactivity". According to this idea, animals sleep because otherwise we'd always be active, and constant activity is a waste of energy. Sleeping for a proportion of the time conserves calories, and also keeps us safe from nocturnal predators etc.

Siegel's theory in what we might call minimalist. That's in contrast to other hypotheses which claim that sleep serves some kind of vital restorative biological function, or that it's important for memory formation, or whatever. It's a hotly debated topic.

But Siegel wasn't the first sleep minimalist. J. Allan Hobson and Robert McCarley created a storm in 1977 with The Brain As A Dream State Generator; I read somewhere that it provoked more letters to the Editor in the American Journal of Psychiatry than any other paper in that journal.

Hobson and McCarley's article was so controversial because they argued that dreams are essentially side-effects of brain activation. This was a direct attack on the Freudian view that we dream as a result of our subconscious desires, and that dreams have hidden meanings. Freudian psychoanalysis was incredibly influential in American psychiatry in the 1970s.

Freud believed that dreams exist to fulfil our fantasies, often though not always sexual ones. We dream about what we'd like to do - except we don't dream about it directly, because we find much of our desires shameful, so our minds disguise the wishes behind layers of metaphor etc. "Steep inclines, ladders and stairs, and going up or down them, are symbolic representations of the sexual act..." Interpreting the symbolism of dreams can therefore shed light on the depths of the mind.

Hobson and McCarley argued that during REM sleep, our brains are active in a similar way to when we are awake; many of the systems responsible for alertness are switched on, unlike during deep, dreamless, non-REM sleep. But of course during REM there is no sensory input (our eyes are closed), and also, we are paralysed: an inhibitory pathway blocks the spinal cord, preventing us from moving, except for our eyes - hence why it's Rapid Eye Movement sleep.

Dreams are simply a result of the "awake-like" forebrain - the "higher" perceptual, cognitive and emotional areas - trying to make sense of the input that it's receiving as a result of waves of activation arising from the brainstem. A dream is the forebrain's "best guess" at making a meaningful story out of the assortment of sensations (mostly visual) and concepts activated by these periodic waves. There's no attempt to disguise the shameful parts; the bizarreness of dreams simply reflects the fact that the input is pretty much random.

Hobson and McCarley proposed a complex physiological model in which the activation is driven by the giant cells of the pontine tegmentum. These cells fire in bursts according to a genetically hard-wired rhythm of excitation and inhibition.

The details of this model are rather less important than the fact that it reduces dreaming to a neurological side effect. This doesn't mean that the REM state has no function; maybe it does, but whatever it is, the subjective experience of dreams serves no purpose.

A lot has changed since 1977, but Hobson seems to have stuck by the basic tenets of this theory. A good recent review came out in Nature Neuroscience last year, REM sleep and dreaming. In this paper Hobson proposes that the function of REM sleep is to act as a kind of training system for the developing brain.

The internally-generated signals that arise from the brainstem (now called PGO waves) during REM help the forebrain to learn how to process information. This explains why we spend more time in REM early in life; newborns have much more REM than adults; in the womb, we are in REM almost all the time. However, these are not dreams per se because children don't start reporting experiencing dreams until about the age of 5.

Protoconscious REM sleep could therefore provide a virtual world model, complete with an emergent imaginary agent (the protoself) that moves (via fixed action patterns) through a fictive space (the internally engendered environment) and experiences strong emotion as it does so.

This is a fascinating hypothesis, although very difficult to test, and it begs the question of how useful "training" based on random, meaningless input is.

While Hobson's theory is minimalist in that it reduces dreams, at any rate in adulthood, to the status of a by-product, it doesn't leave them uninteresting. Freudian dream re-interpretation is probably ruled out ("That train represents your penis and that cat was your mother", etc.), but if dreams are our brains processing random noise, then they still provide an insight into how our brains process information. Dreams are our brains working away on their own, with the real world temporarily removed.

Of course most dreams are not going to give up life-changing insights. A few months back I had a dream which was essentially a scene-for-scene replay of the horror movie Cloverfield. It was a good dream, scarier than the movie itself, because I didn't know it was a movie. But I think all it tells me is that I was paying attention when I watched Cloverfield.

On the other hand, I have had several dreams that have made me realize important things about myself and my situation at the time. By paying attention to your dreams, you can work out how you really think, and feel, about things, what your preconceptions and preoccupations are. Sometimes.

Hobson JA, & McCarley RW (1977). The brain as a dream state generator: an activation-synthesis hypothesis of the dream process. The American journal of psychiatry, 134 (12), 1335-48 PMID: 21570

Hobson, J. (2009). REM sleep and dreaming: towards a theory of protoconsciousness Nature Reviews Neuroscience, 10 (11), 803-813 DOI: 10.1038/nrn2716

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.

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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.

On Faithless Preachers

Everyone's favorite atheist neuro-philosopher Daniel Dennett and colleague Linda LaScola present a paper on Preachers who are not Believers - Christian clergy who stopped believing in God, in some cases many years ago, but remain in their jobs.

It's well worth a read; it's free to access, and very well written. Dennett and LaScola interviewed five (anonymous) preachers, from a variety of American Protestant denominations. All have been atheists, or something very close to it, for some time. And all are, as you'd expect, "in the closet" about their lack of belief, although some have admitted it to selected colleagues and confidants.

Two things struck me about the five men's stories. First, they're all reasonably content with their situation. Partially this must reflect the selection criteria: this was designed as a study of faithless preachers, not ex-preachers. But it's also a testament to the fact that people can accommodate themselves to fulfill even the most contradictory of roles.

Most of these men would find it very difficult to quit, because their whole career, salary, friends, and in a couple of cases marriage, are bound up in the church. But most have come see their position as morally acceptable because they see Christianity as a force for good, even if the doctrines are wrong:

My first few years of doing this were wracked with, ‘God, should I be doing this? Is this ---? Am I being ---? Am I posing? Am I being less than authentic; less than honest?’ … And, I really wrestled with it and to some degree still. But not nearly as much. I will be the first to admit that I see Christianity as a means to an end, not as an end unto itself. And the end is very basically, a kind of liberal, democratic values.

Another says

I will say one strong aspect of any religion, I’d guess, that I’ve been in is the community life. You have great friends who are close; you can depend on them. When there’s hard times, financially, emotionally, whatever, you’ve got a support group.

The second thing that interested me was the idea that the faithless priest situation is a lot less unusual than you'd think. A recurring theme in the stories of these five is that their doubts started in seminary, when they were first introduced to archaeology and Biblical criticism, the historical and linguistic study of the Bible.

Now, it's quite difficult to study these things and remain a believer in the idea that the Bible is anything like the inerrant word of God. But most American churches, and not just the very liberal ones, require their clergy to take Masters level courses in them at seminary.

Rank and file church members don't have to do this and most don't, leaving them more free to hold stronger or literalist views. So the clergy are, paradoxically, often the ones with the most liberal i.e. least traditional interpretation of the things they preach:

A gulf opened up between what one says from the pulpit and what one has been taught in seminary. This gulf is well-known in religious circles.... Every Christian minister, not just those in our little study, has to confront this awkwardness, and no doubt there are many more ways of responding to it than our small sample illustrates. How widespread is this phenomenon? When we asked one of the other pastors we talked with initially if he thought clergy with his views were rare in the church, he responded “Oh, you can’t go through seminary and come out believing in God!” Surely an overstatement, but a telling one.

As someone who hasn't sat down in a church for a decade I don't really know how true this is. Maybe Dennett, LaScola and these five men are exaggerating the size of the "gulf" - but it sounds plausible. If so it suggests that these atheists are just the extreme end of a spectrum of more or less doubtful clergy.