MAOis For Dummies (And British Pundits)

Allegedly, British Prime Minister Gordon Brown takes a monoamine oxidase inhibitor (MAOi) antidepressant.

That's the rumor, based on the rumored fact that he is unable to eat certain things, notably cheese and Chianti wine. These are foods rich in tyramine, a chemical that's normally harmless, but can be toxic in people taking MAOis. So, if Brown is indeed on a Chianti-and-cheeseless regime, he almost certainly is taking one of the several MAOis on the market today.

The original source for this idea is this blogger, who claims to have heard it from an unnamed Brown aide. Is he to be believed? A glance over his website shows he is hardly an impartial commentator, and he goes on to demonstrate his psychological insight with statements like

"Obsessive Compulsive Disorder (OCD) is relatively common. Most of us display some obsessive features in everyday life, but under stress a minority of people become borderline or actual OCD in their behaviour, and need medication to control both this and the depression which almost always presents soon afterwards. ... Gordon Brown's symptoms are obvious when viewed in this light: the constant repetition of phrases, and an almost embarrassing (for his Party) need to spray every Parliamentary answer with statistics... they - and the constant speech repetition - represent Brown's unconscious means of controlling the severe anxiety that accompanies depression with OCD."

So one might think that his credibility is somewhat questionable. This hasn't stopped certain corners of the British blogosphere from getting very excited, however, and even respected political journalist Andrew Marr yesterday quizzed Brown about the issue.

Unfortunately, while many are eager to write about Brown and his possible pills, few of them seem to know anything about psychiatry or antidepressants, which has led to some embarrassing errors. So, for the benefit of British pundits, here are some helpful facts.

MAOis -

• are not "powerful", "heavy duty" antidepressants. In terms of effectiveness, they are no better, on average, than Prozac. In fact, no antidepressant is much better than any other one. They differ in terms of side effects, but not "strength". For what it's worth, current opinion is that if there is a best antidepressant, it is escitalopram, a modern Prozac-like SSRI with very mild side effects, which is just about as unlike a MAOi as you can imagine.
  
• do not "impair" or "affect judgment". Antidepressants don't. Except that they treat depression, and someone who's happy might make different judgments to someone who's depressed. But these drugs do not affect judgment in the way that intoxicants like alcohol or cocaine do. You don't get high on them. This is why they have no street value. Most drugs which impair judgment get used recreationally, because having your judgment impaired can be fun. Antidepressants aren't.
  
• are not exclusively used in "severe depression". They are usually reserved for when a patient has not responded to other drugs. This is because of their troublesome side effects, including high blood pressure, and the fact that you can't eat cheese. But "treatment-resistant" depression is not the same as "severe" depression. In fact, the more severe the depression, the more likely it is to respond to treatment with conventional drugs. If Brown is on MAOis, he has probably tried at least two or three other drugs, but this is by no means uncommon because antidepressants just don't work especially well. According to the largest trial in a real-world setting, the STAR*D project, only 30% of people fully recover on their first antidepressant and only 30% of the rest respond to the second one.
  
• are not especially effective in OCD, as the source of the rumor claimed - "this older class of drugs has one huge advantage: for severe depression and obsessive compulsive disorder it remains very effective", emphasis in the original. This is just flat-out wrong. Other antidepressants are more useful in OCD. Here's a recent review of drug therapy for OCD. MAOis get a mention... right at the end, after (deep breath) SSRIs, clomipramine, atypical antipsychotics, SNRIs, pregabalin, tricyclic antidepressants, and benzodiazepines. Here's the only published trial comparing a monoamine oxidase inhibitor to another drug, Prozac, for OCD. The MAOi didn't work, Prozac did.
• were the first class of antidepressants to be discovered; the very first, iproniazid, was discovered in 1952. Others followed, such as tranylcypromine, phenelzine, and selegiline. Today, there are a handful of MAOis on the market. These include some newer drugs such as moclobemide (which has milder side effects) and the selegiline transdermal patch (which carries fewer dietary restrictions). MAOis are primarily used to treat depression, but are also used in Parkinson's disease.

So, even if Brown is taking MAOis, this has no implications regarding his mental state or competence to govern. What about the possibility that he is depressed? This could be relevant, but considering that the most popular British leader of all time famously suffered from severe depressive episodes throughout his life, including his time in office, the historical precedents are not unfavourable.

Realistically, none of this is going to change people's minds. No-one is really concerned about the possibility that Gordon Brown is using MAOis, or even the possibility that he's depressed. Rather, a lot of people just really don't like him, and this rumor is the latest stick with which to beat him. Blogger Guido Fawkes has been asking "Is Brown Bonkers?" for months. As one journalist put it, "Whether literally the case or not, however, this rumor carries the kind of psychological truth that tends to be more damaging than fact." Which didn't stop him from repeating the rumor uncritically.

[BPSDB]

Encephalon #76

Welcome to #76 in the fortnightly Encephalon blog carnival series.

• Sandra Kiume's Channel N points us to a fascinating and inspiring talk on blindness, vision science and the brain, from MIT Prof. Pawan Sinha. It's an hour long, but well worth your attention.
• The tale of a Polish violin prodigy whose career was tragically cut short is recounted over at Providentia. Josef Hassid was originally thought to have been suffering from schizophrenia, but was eventually diagnosed with a brain tumour.
• The Neurocritic hits us with a pair of posts about some rather drastic neurological treatments for addiction (one, two), and also reviews a study arguing that neuroscience teaches us that torture doesn't work.
  
• Sharpbrains discusses a pioneering initiative to encourage awareness of dementia in San Francisco.
• Neurophilosophy features a pair of typically lucid posts about associative learning in coma patients and an fMRI study showing that hippocampal activity predicts unconscious memory.
• Zoe Wool over at Neuroanthropology writes about the life of a solider injured in Iraq and the difficulty in separating the "physical" from the "psychological" in such cases.
• Crime and Consequences blogger Steve Erikson alerts us to a provocative new paper of his discussing and criticizing the "neurolaw" movement. Sure to be food for thought.
  
• Brain-inspired "neuromorphic" software may soon be able to recognise text better than current methods, writes Brain Stimulant.
• Neurones may be more energy-efficient than previously believed, according to a paper featured at AK's Rambling Thoughts. He also points out the dangers of taking scientific terminology too seriously.
• Finally, The Mouse Trap discusses the moodiness of entrepreneurs and the near-chaotic nature of the brain.
  

That's it for this time. We're still looking for a host for the next edition, so if you're a neuro/psychology blogger and you'd like to be the next Encephalon editor, please email encephalon dot host at gmail dot com.

Panic! In the fMRI Scanner

Continuing the theme of interesting single case reports, I was pleased to see a paper about brain activity in someone who suffered a panic attack in the middle of an fMRI brain scan experiment.

The unfortunate volunteer, a 46 year old woman, was taking part in an experiment looking at restless-leg syndrome. The scan lasted 40 minutes, and everything was going smoothly until quite near the end, when out of the blue, she had a panic attack.

Obviously, the scan had to be abandoned - as soon as the volunteer pressed the emergency "panic button", they stopped the scan and got her out of the MRI. (This kind of thing is why we have such buttons!) However, they decided to see what happened in the woman's brain as the panic started using the data they acquired up to that point.

Here's what they found: the top graph here shows her heart rate. It starts increasing a bit and then spikes, which shows exactly when the attack occurred. What about the brain? Well, amygdala and left insula activity sort of increase around this time. A bit. If you stare at the lines hard enough.

If you believe they did, it makes sense because the amygdala is known to be involved in anxiety (amongst other things) while the insula is responsible for the perception of the body's internal state, which is rather out of whack during a panic attack.

What doesn't make sense is the middle temporal gyrus bit, which was statistically the only part of the brain where activity was significantly correlated with heart rate (in whole-brain analysis). That region is not believed to have anything to do with panic, and to be honest, it's probably just a fluke.

This is only the second published report about panic during fMRI. There was one previous paper from 2006 about an attack in someone with a history of panic, which also found amygdala activation. But there are sure to be others out there which haven't made it into print - anxiety and panic during scans is not unheard of (the scanner is rather claustrophobic). It would be interesting to get more data on this, because it's obviously rather hard to research real-life panic attacks, on account of them being unpredictable.

Spiegelhalder, K., Hornyak, M., Kyle, S., Paul, D., Blechert, J., Seifritz, E., Hennig, J., Tebartz van Elst, L., Riemann, D., & Feige, B. (2009). Cerebral correlates of heart rate variations during a spontaneous panic attack in the fMRI scanner Neurocase, 1-8 DOI: 10.1080/13554790903066909

Spot The Difference

As part of my extensive research into the famous dead fish brain scanning study, I decided to read a little bit about the Atlantic salmon (Salmo salar), the fish which started it all.

It turns out, at least according to Wikipedia, that there are various interesting things about this species, for example, it's "much more aggressive than other salmon". Who knew?

However, by far the most interesting thing is that developing salmon embryos are about the cutest things in the world, and look exactly like smiley faces, or maybe Pacman. Those dark spots really are the eyes.

Endless forms most beautiful, indeed.

The Man With Half A Brain

A lovely new paper reports in fascinating detail on a man who lost a uniquely large portion of his brain: Bilateral limbic system destruction in man.

The authors, Feinstein et al from Iowa City, have studied the patient, "Roger", for 14 years. Roger was born in 1952, and lived a fairly uneventful life until he contracted herpes simplex encephalitis (HSE) at the age of 28.

HSE is an extremely rare condition in which the herpes virus infects the central nervous system. Untreated, it is fatal in 70% of people. Survivors suffer varying degrees of neurological damage. Roger suffered more than most - his is the worst case of herpes encephalitis damage among patients currently alive, and there are only three recorded cases of similarly extensive lesions. Roger lost almost his entire "limbic system":

The amount of destroyed neural tissue is extensive and includes bilateral damage to core limbic and paralimbic regions, including the hippocampus, amygdala, parahippocampal gyrus, temporal poles, orbitofrontal cortex, basal forebrain, anterior cingulate cortex, and insular cortex. The right hemisphere is more extensively affected than the left, although the lesions are largely bilateral.

"Limbic system" is an old, vague, but still popular term for a collection of brain structures located deep in the centre of the brain (but not to be confused with the basal ganglia). It's often thought of as the "primitive", "emotional" part of the brain, and there is some truth to this. Roger's limbic system was profoundly damaged on both sides; on the right side, the lesion included the whole temporal lobe and most of the ventral prefrontal cortex as well.

What happened to Roger's mind when his brain suffered such injury? In many ways, remarkably little. His only major impairment is profound anterograde amnesia: he is unable to remember anything that has happened since the infection, which was 28 years ago.

For Roger, not much has changed over the past 28 years. He has virtually no episodic memories for any events that have transpired over the past three decades. For example, he has no recollection of 9/11, and when shown pictures of the planes crashing into the World Trade Center he often responds with bewilderment, speculating that Russia must be attacking America.

This is, obviously, a disabling deficit: Roger cannot lead a normal life. But in other areas of mental functioning, he is quite normal. His IQ is above average; his speech and language abilities are excellent; his vision and hearing are normal, although he has no sense of taste or smell. His short term (working) memory, attention, and reasoning abilities are unimpaired. His motor abilities are fine - he is reportedly an excellent bowler - and he is able to improve motor skills through practice. And his recall of things which happened before the infection is largely preserved, although the few years just before the infection are partially lost.

Fascinatingly, Roger's personality and emotional life seems to have been changed by the infection as well, but in a rather fortunate way -

Roger appears remarkably unconcerned by his condition. He hardly ever complains and, in general, shows little worry for anything in life. Both of his parents and his sister fervently claim that “Roger is always happy,” an observation that is consistent with our own impression. Moreover, based on his family’s report, Roger is paradoxically happier now than he was before his brain damage. ... His premorbid disposition of being somewhat reserved and introverted has shifted to being outgoing and extroverted...

Most conversations with Roger involve animated speech that is replete with prosody, gesture, and, often times, laughing. He readily displays signs of positive emotion including happiness, amusement, interest, and excitement. As previously noted, Roger’s positive mood has remained essentially unchanged over nearly three decades.

His only other reported quirks are an insatiable appetite, and a habit of collecting and holding onto everyday items.

What does all this mean? Neuroscientists will find little about the case surprising. No textbooks are going to have to be rewritten. Roger's inability to form new memories, combined with preserved memory of events up to the few years before the damage, is similar to that seen in other cases of bilateral hippocampus damage. The most famous being the sadly recently deceased patient "H. M.", but there have been plenty of others. The hippocampus seems to be necessarily for forming new long term memories, but the memories themselves are stored elsewhere.

Roger's happy-go-lucky disposition is also not too unexpected, given that he suffered bilateral damage to the ventromedial prefrontal cortex (vmPFC). Last year I wrote about a study from the same Iowa team finding that damage to this area seems to protect against depression. And this is the same region which was targeted by the infamous prefrontal lobotomies of the 40s and 50s - which, for all their ethical shortcomings, sometimes did seem to relieve people of mental anguish.

For me, Roger provides two main lessons, both rather satisfying ones. Firstly, even after losing large parts of the brain, life goes on. The brain is modular, and we can live without many of the modules. And secondly, if our emotional circuitry is damaged, we generally feel better, rather than worse. To put it another way, perhaps, happiness is our default state, and emotions just have a habit of getting in the way.

Feinstein, J., Rudrauf, D., Khalsa, S., Cassell, M., Bruss, J., Grabowski, T., & Tranel, D. (2009). Bilateral limbic system destruction in man Journal of Clinical and Experimental Neuropsychology, 1-19 DOI: 10.1080/13803390903066873

Encephalon #76 - Call for Submissions

Neuroskeptic will be hosting the 76th instalment of ENCEPHALON, the regular neuroscience and psychology carnival. So get writing, or get submitting things you've already written, about the brain, the mind, and all that kind of thing.

As ever, please e-mail submissions (up to 3 posts) to encephalon dot host at gmail dot com, by the end of this Sunday 27th September!

Why Do We Sleep?

Why do we sleep? Because otherwise, we'd always be doing stuff.

This is the theory advanced by UCLA sleep researcher Jerome Siegel (website) in a new paper, Sleep viewed as a state of adaptive inactivity (free pdf). It's part of a Nature Reviews Neuroscience special issue on the evolution of the nervous system. Siegel proposes that the evolutionary function of sleep is simply to ensure that animals are only active when the benefits of movement (mostly access to food, and mates) outweigh the costs (activity burns calories, and puts you at risk of predation or accidents).

Sleep, in other words, is our equivalent of the inactive states into which most living things, even plants, periodically enter when it suits them. Even (deciduous) trees spend the cold, dark half of the year doing not very much. In Siegel's view, this is their equivalent of sleep.

This theory stands in contrast to the idea that sleep has a restorative function - that animals need to sleep, because some kind of important biological process can only occur while we're sleeping. This idea is intuitively appealing - it feels like we benefit from sleep, and at least in humans sleep deprivation has many well-documented negative effects.

But, as Siegel points out, we're far from any kind of a consensus on what the biological function of sleep is. It's generally assumed that there is one, and a great many have been proposed - he lists some, ranging from that sleep is important for the formation of new neural connections, to the idea that sleep is needed to reverse cellular damage caused by oxidative stress (interestingly, Siegel himself contributed to one of the papers he gives as a reference for that idea).

If a vital restorative function of sleep were to be conclusively identified, Siegel's theory would obviously be disproven. On the other hand, if Siegel is right, several things should be true. Firstly, the proportion of time that an animal spends asleep should be directly proportional to the amount of time that it is useful for it to be active.

Siegel argues that this is what we find. The big brown bat for example is the doziest of all mammals, sleeping for 20 hours per day. But it wouldn't benefit from being awake any more, because the insects it feeds on are only active for a few hours at dusk. If it were flying around during the day, it would just be wasting energy (and risking becoming lunch for a bird.)

By contrast, he says, some marine mammals (cetaceans, dolphins and whales) never sleep at all. In land mammals, sleep consists of distinct periods of neural activity such as REM and slow wave sleep. Neither, however, occurs in cetaceans. They do show a kind of neural activity called Unihemispheric Slow Waves (USWs). But these are confined to one half of the brain at a time. It's often said that this is "half the brain going to sleep". However, the animals remain moving normally, and are able to avoid obstacles, during USWs. It's not as if only half their body remains awake. As such, Siegel says, the USW state is not sleep.

If it's true that there are animals which never sleep, this is strong evidence for Siegel's theory, and against the idea that sleep plays a vital role. But not everyone agrees with his claim that dolphins and whales don't sleep. See, for example, this 2008 open-access paper, Is Sleep Essential?, which calls Siegel's theory of sleep the "null hypothesis" and then proceeds to criticize it.

In particular, the authors claim that dolphins do sleep, albeit with only one half of their brain at a time, and they make the interesting point that "the very fact that dolphins have developed the remarkable specialization that is unihemispheric sleep, rather than merely getting rid of sleep altogether, should count as evidence that sleep must serve some essential function and cannot be eliminated."

At this point the debate becomes highly technical. The sleep behaviour and neural activity of marine mammals is hardly easy to research, and it looks as though more evidence is needed before we can know for sure whether they sleep or not. This is one of those seemingly trivial questions which could end up deciding between two theories with enormous implications. There are quite a lot of them in science. We don't yet know why we sleep. But the answer may lie with the dolphins.

Link: More recently, I asked Why do we dream?

Siegel, J. (2009). Sleep viewed as a state of adaptive inactivity Nature Reviews Neuroscience, 10 (10), 747-753 DOI: 10.1038/nrn2697

Puff the Illusionary Dragon

There's a lot of interest in visual illusions at the moment thanks to an excellent article over at Seed, This Picture Is Not Moving.

A while back I wrote about the Hollow Face Illusion in which a hollow (concave) mask of a face appears to be a solid (convex) face and I posted a seriously freaky video featuring Charlie Chaplin. But reader "Jake" just pointed out an even better example of the same illusion, the Paper Dragon.

See the video above. If you like what you see, you can make your own paper dragon by printing out this .pdf here. It only takes 10 minutes, scissors and a bit of sticky tape. I highly recommend it, the effect is astonishing - it really looks as though the dragon's head is moving. You may need to close one eye to get the full experience. (The dragon was designed by ThinkFun).

The dragon, like the Charlie Chaplin mask, is an example of the "depth inversion" effect. Our visual system assumes that objects are convex, rather than concave, especially when those objects are familiar things like faces.

In my opinion the most interesting thing about the phenomena, and indeed with all illusions, is that concious belief cannot override the effect. I know that the dragon's head is concave, I folded it up and stuck it together myself. Yet I still see it as convex. This is strong evidence for the modularity of mind. But that's another story.

fMRI Gets Slap in the Face with a Dead Fish

A reader drew my attention to this gem from Craig Bennett, who blogs at prefrontal.org:

Neural correlates of interspecies perspective taking in the post-mortem Atlantic Salmon: An argument for multiple comparisons correction

This is a poster presented by Bennett and colleagues at this year's Human Brain Mapping conference. It's about fMRI scanning on a dead fish, specifically a salmon. They put the salmon in an MRI scanner and "the salmon was shown a series of photographs depicting human individuals in social situations. The salmon was asked to determine what emotion the individual in the photo must have been experiencing."

I'd say that this research was justified on comedic grounds alone, but they were also making an important scientific point. The (fish-)bone of contention here is multiple comparisons correction. The "multiple comparisons problem" is simply the fact that if you do a lot of different statistical tests, some of them will, just by chance, give interesting results.

In fMRI, the problem is particularly severe. An MRI scan divides the brain up into cubic units called voxels. There are over 40,000 in a typical scan. Most fMRI analysis treats every voxel independently, and tests to see if each voxel is "activated" by a certain stimulus or task. So that's at least 40,000 separate comparisons going on - potentially many more, depending upon the details of the experiment.

Luckily, during the 1990s, fMRI pioneers developed techniques for dealing with the problem: multiple comparisons correction. The most popular method uses Gaussian Random Field Theory to calculate the probability of falsely "finding" activated areas just by chance, and to keep this acceptably low (details), although there are other alternatives.

But not everyone uses multiple comparisons correction. This is where the fish comes in - Bennett et al show that if you don't use it, you can find "neural activation" even in the tiny brain of dead fish. Of course, with the appropriate correction, you don't. There's nothing original about this, except the colourful nature of the example - but many fMRI publications still report "uncorrected" results (here's just the last one I read).

Bennett concludes that "the vast majority of fMRI studies should be utilizing multiple comparisons correction as standard practice". But he says on his blog that he's encountered some difficulty getting the results published as a paper, because not everyone agrees. Some say that multiple comparisons correction is too conservative, and could lead to genuine activations being overlooked - throwing the baby salmon out with the bathwater, as it were. This is a legitimate point, but as Bennett says, in this case we should report both corrected and uncorrected results, to make it clear to the readers what is going on.

YouGov Reply

On Thursday, I wrote about British polling company YouGov, in a follow-up to an earlier post about modern Britain's fondness for opinion polls. YouGov's Co-Founder, Stephan Shakespear, has written a response, which I've posted below.

Stephan makes a strong case that YouGov's polling methods are at least as good, or better, than those of other polling companies. I don't disagree, and I don't have any suggestions as to how they could be improved. In the political sphere, YouGov are widely regarded as the most credible British pollsters, and as Stephan says, they have an excellent record of accuracy in that area. Their popularity is why I chose them as the focus of my piece.

In my post, I did rashly suggest that YouGov's internet-based panel approach might be less representative than a random phone sampling method. But as Stephan says, such a system has plenty of serious problems of its own: "There’s no such thing as a random sample for any kind of market research or polling. There is only random invitation, but since the overwhelming majority of people decline the invitation (or don’t even receive it because they are out when the phone rings...) the resulting sample cannot be random. And it is clearly skewed against certain types of people ... as well as different temperaments..."

As he goes on to say, what YouGov do is inherently difficult - "It’s very hard to know with certainty what the population as a whole thinks about a particular topic, by any method." And this was my essential point: YouGov polls, like all polls, are not an infallible window into public opinion. They could be perfectly accurate - but we don't have any way of knowing how accurate they are, except when it comes to elections, which is a special case.

My issue was, and is, with those who commission opinion polls as a form of advertising, and those who try to use them to demonstrate things which they simply cannot do. Very often, these are the same people. The example I used in my original post was of a poll conducted by a company who run private health and fitness clubs. The message was that British people are incredibly unfit and lazy. Amongst other things it reported that 64% of parents are "always" too tired to play with their children. I don't believe that. I don't think an opinion poll is a good way of measuring laziness. Physical fitness is a vital public health issue, but this is just silly.

It's not clear if that was a YouGov poll, but this one was: 75% of Britons text or blog while on the toilet, which puts us at risk of haemorrhoids, according to a poll commissioned by the makers of trendy, expensive 'probiotic' yoghurt, Yakult. That got Yakult mentions in The Telegraph, The Scotsman, The Metro and The London Paper. I could go on.

Of course we can't blame polling companies for what their clients do with their data. But a healthy scepticism of this data is part of the reason why I'm so disappointed at the number of newspaper articles, usually based very closely on press releases (like Yakult's), based on such polls. It's not YouGov's fault, and I'm sure most of the research YouGov do is not like this. But it's a problem. It's lazy journalism, and it's a poor substitute for serious, informed debate about health and social issues.

Anyway, here's Stephan Shakespear's reply:

"As you must realise, there’s no such thing as a random sample for any kind of market research or polling. There is only random invitation, but since the overwhelming majority of people decline the invitation (or don’t even receive it because they are out when the phone rings, or they don’t pick up their phone because they screen calls, etc) the resulting sample cannot be random. And it is clearly skewed against certain types of people (younger people, busier people, etc), as well as different temperaments (most people won’t willingly give up their time to answer surveys: remember that they tend to be quite long, and not usually on very interesting subjects. Would you stop in the street on your way to work for someone with a clipboard? Would you say ‘yes’ when you are called in the middle of making supper for your kids?)

When researchers do manage to talk to someone, there is no way of knowing whether the answers respondents give to the questions reflect their true thinking. Indeed, as a neuroscientist will be quick to point out, it may not be easy to define what their “true thinking” is, because they may never before have thought about the topic they are being asked about. It may well be that ten minutes after the interview, they think differently about it. Or maybe they were lying, either to the interviewer or to themselves. Maybe they were trying to please the interviewer with the answer they thought was wanted. Maybe they want to appear more reasonable than they really are.

So it’s very hard to know with certainty what the population as a whole thinks about a particular topic, by any method. In fact it’s impossible even if one has the latest neuropsychology techniques at one’s disposal. Nowhere in your piece do you discuss any of these issues which apply to all forms of opinion research, under any conditions. Comparison with other methodologies is important, because we must do the best we can when conditions dictate imperfection.

To repeat: all methodologies include selection bias (self-selection to participate in a panel is not essentially different from the overwhelming self-de-selection that applies to random-interruption methods), and all have motivational biases (anyone who wants to spend their time giving opinions is different in some way to people who don’t; why should payment mean a ‘financial interest’ that skews opinions? Are the volunteers used for neuroscience not usually rewarded, often financially? Surely non-payment skews the motivation too?)

For the record, at YouGov, we take a lot of care to recruit people to our panel by a variety of methods. The great majority are proactively recruited, they do not find their own way to the panel. They are recruited from a variety of ‘innocent’ sources to maintain as good a demographic balance as we can. But we do not claim random selection - as stated above, no research agency can possibly enforce participation from a random selection, it’s impossible. It was precisely because of our acknowledgement that true random samples are impossible that we say we ‘model’, we do not merely ‘measure’ – something which most of the industry now agrees with. Because we are explicit about this, and because we have historical data on our respondents, we can model by more variables. In other words, we are more scientific, not less scientific, than the methods which, by implication of your omissions, you prefer. We know more about our sample, so we can compare them with the general population in a more sophisticated way; and we have no interviewer effect; and respondents can think a little longer about their answer. So we think that makes for better data. In fact, wherever our data can be compared to real outcomes, we have a fantastic record.

You say that our record of accuracy in predicting elections does not mean we are accurate in other things. It is true that most areas of public opinion cannot be proved, by any method, and therefore we cannot prove it either. But it’s surely better to use a methodology that has proven its accuracy in areas that can be proven, rather than one that was found to be wrong, no? YouGov has the best record of accuracy in predicting real outcomes; most recently the Euro elections and the London Mayoral election. You may remember other pollsters had Ken Livingstone beating or neck-and-neck with Boris Johnson. We said Johnson would win by 6%. He won by 6%. Would you rather trust a company that gets the provable things right, or a company that gets them wrong? Does your ‘science’ tell you that methodologies which get the wrong political prediction are more likely to be right in other areas? If so, please explain further.

As it happens, the vast majority of the revenue for YouGov comes from market research for companies who do not publish the results in the media, companies which rely on the accuracy of our descriptions and predictions of consumer behaviour for their future planning. You might want to credit them with some kind of quality-control, if only in their self-interest.

Given that we all acknowledge the difficulty of knowing precisely the percentage that think this or that about some topic they may rarely have thought about, what is your suggested better course? As it is ultimately impossible to know what a single person “thinks”, let alone an entire population, maybe we should attempt nothing, report nothing? Would it be better if there were no data available, only the anecdotal publications of bloggers?

We don’t let it rest. We constantly experiment - with, for example, deliberative methodologies to try to measure how people change their thinking when they consider a matter more, when they are given access to more information, etc. Our panel methodology allows us to use very large (20,000+) randomly-split samples where we seek responses from each split to very slightly altered inputs, controlling for all but a single variable. Even you might agree that our methodology here is of a piece with that of your fellow scientists, some of whom we’ve consulted. We are able to do scientific things with our methodology that other, random-digit-dialing methods can’t, or at least can’t do in an affordable way. You might want to credit us with our serious approach to methodology, rather than slag us off in your most unscientific manner.

Stephan Shakespeare, Co-Founder and Chief Innovation Officer, YouGov"

Most People Experience "Mental Illness" By Age 32

Mental illness: how common is it? A popular answer is one in four - 25% of people will experience it at least once in their lives. In fact, most published research suggests that the lifetime rate is higher, around 30-50%, in Western nations.

That's a lot. But even this may be a serious underestimate, according to a new paper, How common are common mental disorders? The study compared the proportion of people reporting mental illness under two different research methods: retrospective and prospective.

Retrospective means asking people to think back and remember whether they ever have felt a certain way. A prospective study, however, recruits people and then follows them up for a certain length of time, asking them how they feel at regular intervals.

The obvious advantage of prospective studies is that there is less chance of forgetting. In a retrospective study, people are required to remember how they were feeling years, or even decades, ago. Human memory just isn't that good. A prospective study requires some remembering, as people are generally asked to report how they've felt over the last year, but this is clearly less problematic.

The prospective study in question here included 1,000 people from Dunedin, New Zealand. The volunteers were followed from birth to age 32, and were interviewed at ages 18, 21, 26 and 32. The results were compared to three large retrospective lifetime studies, two American and one from NZ. (1,2,3).

50% of the Dunedin prospective cohort reported at least one "anxiety disorder", 41% reported "depression", 32% confessed to "alcohol dependence" and 18% to "cannabis dependence". (Those were the only conditions studied.) For some reason, we're not told how much overlap there was, but even assuming there was a lot, well over half of all the cohort will have experienced at least one disorder. If the overlap was low, it could be almost all of them. And remember, this is just up to age 32. And there still may have been some forgetting...

Compared to the retrospective studies, these rates are all about twice as high. What does this mean for psychiatry?

First, it suggests that retrospective studies, which are by far the most common, are flawed. People just tend to forget a lot of "mental illness" when asked to remember across the lifetime. More evidence for this comes from the fact that the ratio of past-year to lifetime reported disorders was 38% in the prospective study compared to about 60% in the retrospective ones.

But there's a more profound implication. A growing number of critics have argued that the very high reported lifetime rates of mental disorders mean that the way most psychiatrists diagnose mental illness is flawed. The "Bible" of modern psychiatric diagnosis is the Diagnostic and Statistical Manual (DSM) of Mental Disorders of the American Psychiatric Association. DSM diagnostic criteria were used in the studies in question here.

These results suggest that DSM diagnoses are even more common than previously believed, which only strengthens the critics' case. According to DSM criteria, at least 40% of people experience "Major Depressive Disorder" by age 32.

In which case, what is it? A fairly usual part of human life. So, calling it a disease and treating it with drugs or therapy seems rather presumptuous. Especially since so many people who "suffer" from it manage to not only get over it, but actually forget it ever happened. (Of course, this shouldn't be taken to mean that real, serious clinical depression doesn't exist.)

The authors conclude - listen carefully -

This article is uninformative (and agnostic) about the validity of diagnoses as defined by DSM-IV ... [rather], objections voiced to surveys’ higher than expected lifetime prevalence of disorder are objections to prevalence that is only half what it could be in reality...

Researchers might begin to ask why so many people experience a DSM-defined disorder at least once during their lifetimes, and what this prevalence means for etiological theory, the construct validity of the DSM approach to defining disorder, service-delivery policy, the economic burden of disease, and public perceptions of the stigma of mental disorder.

That hammering sound you hear is another nail sealing the coffin of DSM's credibility. If many* DSM "disorders" are simply descriptions of normal parts of human life, we need to take a long, hard look at those "disorders", and rethink whether they need to labelled and treated as medical problems.

The newest edition of DSM, DSM-5, is currently in development. This would seem like a great opportunity to do just that. Unfortunately, the development process is rapidly degenerating into farce. If DSM-5 does not address the issues raised here, many people will be tempted to give up on DSM entirely.

* Not all: the great majority of people will never meet criteria for schizophrenia or bipolar disorder, for example.

Moffitt, T., Caspi, A., Taylor, A., Kokaua, J., Milne, B., Polanczyk, G., & Poulton, R. (2009). How common are common mental disorders? Evidence that lifetime prevalence rates are doubled by prospective versus retrospective ascertainment Psychological Medicine DOI: 10.1017/S0033291709991036

YouGov're Having A Laugh

A few weeks back I wrote about the surveys-of-2,000-people which form a growing proportion of British news stories. Suppose you're a company or activist group. You commission a survey of 2,000 people, and ask them some questions vaguely relating to your product or cause. You pick the most interesting results, write them up into a publication-ready press release, and send it to journalists. There's a good chance that your press release will appear, with minor alterations, as a news story in the British media. Like these articles (BBC, Daily Telegraph), which bear a striking similarity to this press release.

Which is good news for you. You get your name in the papers, and it doesn't even look like advertising. Journalists get column inches for very little work, and the pollsters who conducted the survey get publicity too (and your money). Everyone wins, except the public, who end up bombarded with usually meaningless statistics in the guise of "research".

The survey doesn't have to be of 2,000 people, but that's the norm. This is because this is the size of the samples used by YouGov PLC, who are responsible for (at least it seems to me) the majority of these things.

YouGov polls are everywhere. I'd always assumed that they were telephone surveys of a random sample of the British population. I assumed that because I thought that they were meant to be representative. How naïve.

In fact YouGov polls work like this: you sign up as a panelist, online, which takes two minutes. You then occasionally get e-mails inviting you to do surveys. If you do one, you get 50p credit. When you've got £50 they send you a cheque. It's a great way of making cash online, according to websites about making cash online. Sign up here to get in on the action.

So, the participants in all YouGov polls are not random people but are both self-selected and financially motivated. Many of them will be just doing it for the cash, in which case they will be trying to answer the survey as quickly as possible.

Worst, the panelists are not representative of the British population - they consist of people who use the internet, have heard about YouGov, and chose to participate. YouGov say they have 200,000 users, out of 60 million British people.

Every day, YouGov sends a survey to a certain sample of their users which collects 2,000 responses. They call this the "Omnibus" poll. It costs £500 to commission one, according to the leaflet. That's chump change in advertising terms; I don't know how much it would cost to run an ad in one or more newspapers, but it would be much more. With a YouGov poll you might even get onto bbc.co.uk, which doesn't do paid advertising at all. You can see why it's so popular.

YouGov defend their methodology against criticisms. Their main argument is that their approach has a track record of being accurate in predicting the outcome of British elections. But political polling is unique. Politics is one of the few things that most people have strong opinions about. And elections are just big polls, after all. Pollsters can learn through trial-and-error the best ways of weighting their results to achieve accurate predictions.

So the fact that YouGov are good at predicting elections doesn't mean that their polls are any good at probing the nation's drinking habits, attitudes to the mentally ill, favorite vegetables, or whatever else. They could be totally wrong. Or they could be perfect. We don't know. It doesn't matter to the people who commission these surveys, of course, because it's publicity either way. It should matter to journalists, but it doesn't seem to.

Bottom line: if you want cheap media exposure, call YouGov. If you want serious news, don't. And if you want to know how journalism got into this sorry state, read Bad Science and Flat Earth News. Really. Bloggers like me are not going to shut about those books until everyone's read them at least five times.

[BPSDB]

Trauma Alters Brain Function... So What?

According to a new paper in the prestigous journal PNAS, High-field MRI reveals an acute impact on brain function in survivors of the magnitude 8.0 earthquake in China.

The earthquake, you'll remember, happened on 12th May last year in central China. Over 60,000 people died. The authors of this paper took 44 earthquake survivors, and 32 control volunteers who had not experienced the disaster.

The volunteers underwent a "resting state" fMRI scan; survivors were scanned between 13 and 25 days after the earthquake. Resting state fMRI is simply a scan conducted while lying in the scanner, not doing anything in particular. Previous work has shown that fMRI can be used to measure resting state neural activity in the form of low-frequency oscillations.

The authors found differences in the resting state low-frequency activity (ALFF) between the trauma survivors and the controls. In survivors, resting state activity was increased in several areas:

"The whole-brain analysis indicated that, vs. controls, survivors showed significantly increased ALFF in the left prefrontal cortex and the left precentral gyrus, extending medially to the left presupplementary motor area... [and] region of interest (ROI) analyses revealed significantly increased ALFF in bilateral insula and caudate and the left putamen in the survivor group..."

They also reported correlations between resting activity in some of these areas and self-reported anxiety and depression symptoms in the survivors.

Finally, survivors showed reduced functional connectivity between a wide range of areas ("a distributed network that included the bilateral amygdala, hippocampus, caudate, putamen, insula, anterior cingulate cortex, and cerebellum.") Functional connectivity analysis measures the correlation in activity across different areas of the brain - whether the areas tend to activate at the same time or not.

Now - what does all this mean? And does it help us understand the brain?

The fact that there are differences between the two groups is neither informative nor surprising. "Resting state" neural activity presumably reflects whatever is going through a person's mind. Recent earthquake survivors are going to be thinking about rather different things compared to luckier people who didn't experience such trauma. It doesn't take a brain scan to tell you that, but that's all these scans really tell us.

But these weren't just any differences - they were particular differences in particular brain regions. Does that make knowing about them more interesting and useful?

Not as such, because we don't know what they represent, or what causes them. So living through an earthquake gives you "Increased ALFF in the left prefrontal cortex" - but what does that mean? It could mean almost anything. The left prefrontal cortex is a big chunk of the brain, and its functions probably include most complex cognitive processes. Ditto for the other areas mentioned.

The authors link their findings to previous work with frankly vague statements such as "The increased regional activity and reduced functional connectivity in frontolimbic and striatal regions occurred in areas known to be important for emotion processing". But anatomically speaking, most of the brain is either "fronto-limbic" or "striatal", and almost everywhere is involved in "emotion processing" in one way or another.

So I don't think we understand the brain much better for reading this paper. Further work, building on these results, might give insights. We might, say, learn that decreased connectivity between Regions X and Y is because trauma decreases serotonin levels, which prevents signals being communicated between these areas, which is why trauma victims can't use X to deliberately stop recalling traumatic memories, which is what Y does.

I just made that up. But that's a theory which could be tested. Much of today's neuroimaging research doesn't involve testable theories - it is merely the exploratory search for neural differences between two groups. Neuroimaging technology is powerful, and more advanced techniques are always being developed. What with resting state, functional connectivity, pattern-classification analysis, and other fancy methods, the scope for finding differences between groups is enormous and growing. I'm being rather unfair in criticizing this paper; there are hundreds like it. I picked this one because it was published last week in a good journal.

Exploratory work can be useful as a starting point, but at least in my opinion, there is too much of it. If you want to understand the brain, as opposed to simply getting published papers to your name, you need a theory sooner or later. That's what science is about.

Lui, S., Huang, X., Chen, L., Tang, H., Zhang, T., Li, X., Li, D., Kuang, W., Chan, R., Mechelli, A., Sweeney, J., & Gong, Q. (2009). High-field MRI reveals an acute impact on brain function in survivors of the magnitude 8.0 earthquake in China Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0812751106

Predicting Antidepressant Response with EEG

One of the limitations of antidepressants is that they don't always work. Worse, they don't work in an unpredictable way. Some people benefit from some drugs, and others don't, but there's no way of knowing in advance what will happen in any particular case - or of telling which pill is right for which person.

As a result, drug treatment for depression generally involves starting with a cheap medication with relatively mild side-effects, and if that fails, moving onto a series of other drugs until one helps. But since it can take several weeks for any new drug to work, this can be a frustrating process for patients and doctors alike.

Some means of predicting the antidepressant response would thus be very useful. Many have been proposed, but none have entered widespread clinical use. Now, a pair of papers(1,2) from UCLA's Andrew Leuchter et al make the case for prediction using quantitative EEG (QEEG).

EEG, electroencephalography, is a crude but effective way of recording electrical activity in the brain via electrodes attached to the head. "Quantitative" EEG just means using EEG to precisely measure the level of certain kinds of activity in the brain.

Leuchter et al's system is straightforward: it uses six electrodes on the front of the head. The patient simply relaxes with their eyes closed for a few minutes while neural activity is recorded.

This procedure is performed twice, once just before antidepressant treatment begins and then again a week later. The claim is that by examining the changes in the EEG signal after one week of drug treatment, the eventual benefit of the drug can be predicted. It's not an implausible idea, and if it did work, it would be rather helpful. But does it?

Leuchter et al say: yes! The first paper reports that in 73 depressed patients who were given the antidepressant escitalopram 10mg/day, QEEG changes after one week predicted clinical improvement six weeks later. Specifically, people who got substantially better at seven weeks had a higher "Antidepressant Treatment Response Index" (ATR) at one week than people who didn't: 59.0 ± 10.2 vs 49.8 ± 7.8, which is highly significant (p less than 0.001).

In the companion paper, the authors examined patients who started on escitalopram and then either kept taking it or switched to a different antidepressant, bupropion. They found that patients who had a high ATR after a week of escitalopram tended to do well if they stayed on it, while patients who had a low ATR to escitalopram did better when they switched to the other drug.

These are interesting results, and they follow from ten years of previous work (mostly, but not exclusively, from the same group) on the topic. Because the current study didn't include a placebo group, we can't say that the QEEG predicts antidepressant response as such, only that it predicts improvement in depression symptoms. But even this is pretty exciting, if it really works.

In order to verify that it does, other researchers need to replicate this experiment. But they may find this a little difficult. What is the Antidepressant Treatment Response Index use in this study? It's derived from an analysis of the EEG signal, and we're told that you get it from this formula:

Some of the terms here are common parameters that any EEG expert will understand. But "A", "B", and "C" are not. They're constants, which are not given in the paper. They're secret numbers. Without knowing what those numbers are, no-one can calculate the "ATR" even if they have an EEG machine.

Why keep them secret? Well...

"Financial support of this project was provided by Aspect Medical Systems. Aspect participated in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation and review of the manuscript."

Aspect is a large medical electronics company who developed the system used here. Presumably, they want to patent it (or already have). We're told that

"To facilitate independent replication of the work reported here, Aspect intends to make available a limited number of investigational systems for academic researchers. Please contact Scott Greenwald, Ph.D... for further information."

All very nice of them, but if they'd told us the three magic numbers, academics could start trying to independently replicate these results tomorrow. As it is, anyone who wants to do so will have to get Aspect's blessing, which, with the best will in the world, means they will not be entirely "independent".

[BPSDB]

Leuchter AF, Cook IA, Gilmer WS, Marangell LB, Burgoyne KS, Howland RH, Trivedi MH, Zisook S, Jain R, Fava M, Iosifescu D, & Greenwald S (2009). Effectiveness of a quantitative electroencephalographic biomarker for predicting differential response or remission with escitalopram and bupropion in major depressive disorder. Psychiatry research PMID: 19709754

Leuchter AF, Cook IA, Marangell LB, Gilmer WS, Burgoyne KS, Howland RH, Trivedi MH, Zisook S, Jain R, McCracken JT, Fava M, Iosifescu D, & Greenwald S (2009). Comparative effectiveness of biomarkers and clinical indicators for predicting outcomes of SSRI treatment in Major Depressive Disorder: Results of the BRITE-MD study. Psychiatry research PMID: 19712979

Making Music from fMRI

I've just come across the brilliant work of Dan Lloyd, a philosopher and neuroscientist who's turned fMRI data into music-like sounds:

More videos can be found here. Lloyd doesn't seem to have written or published anything about it yet, but I'm sure that's in the works.

Traditionally, fMRI data is shown as a pattern of colored patches overlayed on a picture on the brain. This emphasizes the spatial, where of the neural activity. But it glosses over the fact that there is also a temporal, when side to it.

Listening to Lloyd's soundscapes, the ever-changing nature of the neural signal is very obvious. Some of the variation over time is just random noise, of course. But some of it represents real, ongoing changes in brain activity. So while turning neuroimaging data into music is undeniably cool, it could also be a more useful way of presenting the data for some purposes.

Via New Scientist, Eavesdropping on the Music of the Brain.