Help! There's an Epidemic of Anxiety! (Part II)

In my last-post-but-one I slammed the claim that the British are suffering from an epidemic of anxiety disorders. I declared it a myth pushed by the Mental Health Foundation and echoed uncritically by British newspapers (although The Economist has since run a kind-of skeptical piece on it.) But I also promised that there are important lessons to be learned here. So, here we go:

The Mental Health Foundation produced a report, In The Face of Fear, which contains various interesting thoughts about the role of fear in public debates. Here's just one:

Individually we experience both rational and irrational fears that drive our behaviour and fear also drives communities and social policies... Excessive fear poses an enormous burden on our society directly through anxiety related illness, which can be physical as well as mental, and indirectly through inappropriate behaviours such as excessive supervision of children or failure to invest. It also paralyses long term rational planning to deal with key future threats such as global warming by diverting attention to more immediate but less important fears.

This is true. Everyone should be scared of global warming. Most people aren't. They're scared of... well, it varies. Cervical cancer was scary a few weeks ago, before that it was the crisis in child protection services, right now it's the Mexican swine flu crisis - not to mention the economic crisis, the knife crime "crisis" - and that's just England.

I'm not saying that we shouldn't care about these things. I'm worried about Mexican swine flu, and so should you be. Especially you, Simon "The Armchair Virologist" Jenkins. But in the face of crisis after crisis after crisis, it becomes hard to take the really crucial crises, such as global warming, seriously. There's a temptation to see every apparant crisis as just another piece of overblown nonsense in need of "debunking" as Ben Goldacre has just discovered. One could call this "crisis fatigue", but that's not exactly right. We're too fond of crises. There are just too many of them.

This is why the MHF felt the need to be so "creative" with the data. As I explained in Part I of this post, the best available figures show that the prevalence of anxiety disorders in Britain has remained boringly level since at least 2000. The MHF simply ignored those numbers in order to make it look as though we're currently facing an epidemic of anxiety. A crisis.

I wish they hadn't. But I don't really blame them for what they did. They did it because they knew that if they didn't, no-one would care about anything they had to say. In an ideal world they would have said: Although British anxiety and depression levels are probably not rising, and although they're not as high as in some countries, they're still higher than in other countries, so we can and should try harder to reduce them. That's the truth. But the truth doesn't involve a crisis, so it wouldn't have made the headlines, or if it did, no-one would have cared. Thus it is that a report warning (inter alia) about the dangers of scaremongering ended up becoming a prime example of scaremongering.

This is the point where, conventionally, one blames "the media" for only publishing "sensationalist" stories in order to "sell papers". Well, that's all true. But the media don't behave that way just for fun. A sensational story is a good story. People want sensationalist stories. Nothing wrong with that, as such. And there's nothing wrong with caring more about a crisis than about a mere problem. A crisis, by definition, is something that deserves urgent attention.

But the result of this is that today, in order to get attention, a problem has to be a crisis - something which is bad and getting worse, fast. Just being a problem in need of a solution isn't enough. There are too many problems - no-one can possibly care about them all. Whereas if something is a crisis, it might just get a little attention. Hence why the MHF had to do what they did. They needed a crisis, so they created one.

If I were a humanities graduate, I would now start explaining how it's all the fault of our postmodern, "post-historical" condition in which there are no grand narratives or central moral authorities to tell us what to care about, leaving every political or moral cause (and organization) to fend for itself in a Darwinian (or market) struggle for attention (and money) in which the only way to survive is to adopt the language of panic, crisis, and emergency thereby devauling that very discourse in a cultural tragedy-of-the-commons. But I'm a science graduate, so I wouldn't dream of doing that.

[BPSDB]

Help! There's an Epidemic of Anxiety! (Part II)

In my last-post-but-one I slammed the claim that the British are suffering from an epidemic of anxiety disorders. I declared it a myth pushed by the Mental Health Foundation and echoed uncritically by British newspapers (although The Economist has since run a kind-of skeptical piece on it.) But I also promised that there are important lessons to be learned here. So, here we go:

The Mental Health Foundation produced a report, In The Face of Fear, which contains various interesting thoughts about the role of fear in public debates. Here's just one:

Individually we experience both rational and irrational fears that drive our behaviour and fear also drives communities and social policies... Excessive fear poses an enormous burden on our society directly through anxiety related illness, which can be physical as well as mental, and indirectly through inappropriate behaviours such as excessive supervision of children or failure to invest. It also paralyses long term rational planning to deal with key future threats such as global warming by diverting attention to more immediate but less important fears.

This is true. Everyone should be scared of global warming. Most people aren't. They're scared of... well, it varies. Cervical cancer was scary a few weeks ago, before that it was the crisis in child protection services, right now it's the Mexican swine flu crisis - not to mention the economic crisis, the knife crime "crisis" - and that's just England.

I'm not saying that we shouldn't care about these things. I'm worried about Mexican swine flu, and so should you be. Especially you, Simon "The Armchair Virologist" Jenkins. But in the face of crisis after crisis after crisis, it becomes hard to take the really crucial crises, such as global warming, seriously. There's a temptation to see every apparant crisis as just another piece of overblown nonsense in need of "debunking" as Ben Goldacre has just discovered. One could call this "crisis fatigue", but that's not exactly right. We're too fond of crises. There are just too many of them.

This is why the MHF felt the need to be so "creative" with the data. As I explained in Part I of this post, the best available figures show that the prevalence of anxiety disorders in Britain has remained boringly level since at least 2000. The MHF simply ignored those numbers in order to make it look as though we're currently facing an epidemic of anxiety. A crisis.

I wish they hadn't. But I don't really blame them for what they did. They did it because they knew that if they didn't, no-one would care about anything they had to say. In an ideal world they would have said: Although British anxiety and depression levels are probably not rising, and although they're not as high as in some countries, they're still higher than in other countries, so we can and should try harder to reduce them. That's the truth. But the truth doesn't involve a crisis, so it wouldn't have made the headlines, or if it did, no-one would have cared. Thus it is that a report warning (inter alia) about the dangers of scaremongering ended up becoming a prime example of scaremongering.

This is the point where, conventionally, one blames "the media" for only publishing "sensationalist" stories in order to "sell papers". Well, that's all true. But the media don't behave that way just for fun. A sensational story is a good story. People want sensationalist stories. Nothing wrong with that, as such. And there's nothing wrong with caring more about a crisis than about a mere problem. A crisis, by definition, is something that deserves urgent attention.

But the result of this is that today, in order to get attention, a problem has to be a crisis - something which is bad and getting worse, fast. Just being a problem in need of a solution isn't enough. There are too many problems - no-one can possibly care about them all. Whereas if something is a crisis, it might just get a little attention. Hence why the MHF had to do what they did. They needed a crisis, so they created one.

If I were a humanities graduate, I would now start explaining how it's all the fault of our postmodern, "post-historical" condition in which there are no grand narratives or central moral authorities to tell us what to care about, leaving every political or moral cause (and organization) to fend for itself in a Darwinian (or market) struggle for attention (and money) in which the only way to survive is to adopt the language of panic, crisis, and emergency thereby devauling that very discourse in a cultural tragedy-of-the-commons. But I'm a science graduate, so I wouldn't dream of doing that.

[BPSDB]

More Brain Voodoo, and This Time, It's Not Just fMRI

Ed Vul et al recently created a splash with their paper, Puzzlingly high correlations in fMRI studies of emotion, personality and social cognition (better known by its previous title, Voodoo Correlations in Social Neuroscience.) Vul et al accused a large proportion of the published studies in a certain field of neuroimaging of committing a statistical mistake. The problem, which they call the "non-independence error", may well have made the results of these experiments seem much more impressive than they should have been. Although there was no suggestion that the error was anything other than an honest mistake, the accusations still sparked a heated and ongoing debate. I did my best to explain the issue in layman's terms in a previous post.

Now, like the aftershock following an earthquake, a second paper has appeared, from a different set of authors, making essentially the same accusations. But this time, they've cast their net even more widely. Vul et al focused on only a small sub-set of experiments using fMRI to examine correlations between brain activity and personality traits. But they implied that the problem went far beyond this niche field. The new paper extends the argument to encompass papers from across much of modern neuroscience.

The article, Circular analysis in systems neuroscience: the dangers of double dipping, appears in the extremely prestigious Nature Neuroscience journal. The lead author, Dr. Nikolaus Kriegeskorte, is a postdoc in the Section on Functional Imaging Methods at the National Institutes of Health (NIH).

Kriegeskorte et al's essential point is the same as Vul et al's. They call the error in question "circular analysis" or "double-dipping", but it is the same thing as Vul et al's "non-independent analysis". As they put it, the error could occur whenever

data are first analyzed to select a subset and then the subset is reanalyzed to obtain the results.

and it will be a problem whenever the selection criteria in the first step are not independent of the reanalysis criteria in the second step. If the two sets of criteria are independent, there is no problem.


Suppose that I have some eggs. I want to know whether any of the eggs are rotten. So I put all the eggs in some water, because I know that rotten eggs float. Some of the eggs do float, so I suspect that they're rotten. But then I decide that I also want to know the average weight of my eggs . So I take a handful of eggs within easy reach - the ones that happen to be floating - and weigh them.

Obviously, I've made a mistake. I've selected the eggs that weigh the least (the rotten ones) and then weighed them. They're not representative of all my eggs. Obviously, they will be lighter than the average. Obviously. But in the case of neuroscience data analysis, the same mistake may be much less obvious. And the worst thing about the error is that it makes data look better, i.e. more worth publishing:

Distortions arising from selection tend to make results look more consistent with the selection criteria, which often reflect the hypothesis being tested. Circularity is therefore the error that beautifies results, rendering them more attractive to authors, reviewers and editors, and thus more competitive for publication. These implicit incentives may create a preference for circular practices so long as the community condones them.

To try to establish how prevalent the error is, Kriegeskorte et al reviewed all of the 134 fMRI papers published in the highly regarded journals Science, Nature, Nature Neuroscience, Neuron and the Journal of Neuroscience during 2008. Of these, they say, 42% contained at least one non-independent analysis, and another 14% may have done. That leaves 44% which were definitely "clean". Unfortunately, unlike Vul et al who did a similar review, they don't list the "good" and the "bad" papers.

They then go on to present the results of two simulated fMRI experiments in which seemingly exciting results emerge out of pure random noise, all because of the non-independence error. (One of these simulations concerns the use of pattern-classification algorithms to "read minds" from neural activity, a technique which I previously discussed). As they go on to point out, these are extreme cases - in real life situations, the error might only have a small impact. But the point, and it's an extremely important one, is that the error can creep in without being detected if you're not very careful. In both of their examples, the non-independence error is quite subtle and at first glance the methodology is fine. It's only on closer examination that the problem becomes apparent. The price of freedom from the error is eternal vigilance.

But it would be wrong to think that this is a problem with fMRI alone, or even neuroimaging alone. Any neuroscience experiment in which a large amount of data is collected and only some of it makes it into the final analysis is equally at risk. For example, many neuroscientists use electrodes to record the electrical activity in the brain. It's increasingly common to use not just one electrode but a whole array of them to record activity from more than brain one cell at once. This is a very powerful technique, but it raises the risk the non-independence error, because there is a temptation to only analyze the data from those electrodes where there is the "right signal", as the author's point out:

In single-cell recording, for example, it is common to select neurons according to some criterion (for example, visual responsiveness or selectivity) before applying
further analyses to the selected subset. If the selection is based on the same dataset as is used for selective analysis, biases will arise for any statistic not inherently independent of the selection criterion.

In fact, Kriegeskorte et al praise fMRI for being, in some ways, rather good at avoiding the problem:

To its great credit, neuroimaging has developed rigorous methods for statistical mapping from its beginning. Note that mapping the whole measurement volume avoids selection altogether; we can analyze and report results for all locations equally, while accounting for the multiple tests performed across locations..

With any luck, the publication of this paper and Vul's so close together will force the neuroscience community to seriously confront this error and related statistical weaknesses in modern neuroscience data analysis. Neuroscience can only emerge stronger from the debate.

Kriegeskorte, N., Simmons, W., Bellgowan, P., & Baker, C. (2009). Circular analysis in systems neuroscience: the dangers of double dipping Nature Neuroscience DOI: 10.1038/nn.2303

More Brain Voodoo, and This Time, It's Not Just fMRI

Ed Vul et al recently created a splash with their paper, Puzzlingly high correlations in fMRI studies of emotion, personality and social cognition (better known by its previous title, Voodoo Correlations in Social Neuroscience.) Vul et al accused a large proportion of the published studies in a certain field of neuroimaging of committing a statistical mistake. The problem, which they call the "non-independence error", may well have made the results of these experiments seem much more impressive than they should have been. Although there was no suggestion that the error was anything other than an honest mistake, the accusations still sparked a heated and ongoing debate. I did my best to explain the issue in layman's terms in a previous post.

Now, like the aftershock following an earthquake, a second paper has appeared, from a different set of authors, making essentially the same accusations. But this time, they've cast their net even more widely. Vul et al focused on only a small sub-set of experiments using fMRI to examine correlations between brain activity and personality traits. But they implied that the problem went far beyond this niche field. The new paper extends the argument to encompass papers from across much of modern neuroscience.

The article, Circular analysis in systems neuroscience: the dangers of double dipping, appears in the extremely prestigious Nature Neuroscience journal. The lead author, Dr. Nikolaus Kriegeskorte, is a postdoc in the Section on Functional Imaging Methods at the National Institutes of Health (NIH).

Kriegeskorte et al's essential point is the same as Vul et al's. They call the error in question "circular analysis" or "double-dipping", but it is the same thing as Vul et al's "non-independent analysis". As they put it, the error could occur whenever

data are first analyzed to select a subset and then the subset is reanalyzed to obtain the results.

and it will be a problem whenever the selection criteria in the first step are not independent of the reanalysis criteria in the second step. If the two sets of criteria are independent, there is no problem.


Suppose that I have some eggs. I want to know whether any of the eggs are rotten. So I put all the eggs in some water, because I know that rotten eggs float. Some of the eggs do float, so I suspect that they're rotten. But then I decide that I also want to know the average weight of my eggs . So I take a handful of eggs within easy reach - the ones that happen to be floating - and weigh them.

Obviously, I've made a mistake. I've selected the eggs that weigh the least (the rotten ones) and then weighed them. They're not representative of all my eggs. Obviously, they will be lighter than the average. Obviously. But in the case of neuroscience data analysis, the same mistake may be much less obvious. And the worst thing about the error is that it makes data look better, i.e. more worth publishing:

Distortions arising from selection tend to make results look more consistent with the selection criteria, which often reflect the hypothesis being tested. Circularity is therefore the error that beautifies results, rendering them more attractive to authors, reviewers and editors, and thus more competitive for publication. These implicit incentives may create a preference for circular practices so long as the community condones them.

To try to establish how prevalent the error is, Kriegeskorte et al reviewed all of the 134 fMRI papers published in the highly regarded journals Science, Nature, Nature Neuroscience, Neuron and the Journal of Neuroscience during 2008. Of these, they say, 42% contained at least one non-independent analysis, and another 14% may have done. That leaves 44% which were definitely "clean". Unfortunately, unlike Vul et al who did a similar review, they don't list the "good" and the "bad" papers.

They then go on to present the results of two simulated fMRI experiments in which seemingly exciting results emerge out of pure random noise, all because of the non-independence error. (One of these simulations concerns the use of pattern-classification algorithms to "read minds" from neural activity, a technique which I previously discussed). As they go on to point out, these are extreme cases - in real life situations, the error might only have a small impact. But the point, and it's an extremely important one, is that the error can creep in without being detected if you're not very careful. In both of their examples, the non-independence error is quite subtle and at first glance the methodology is fine. It's only on closer examination that the problem becomes apparent. The price of freedom from the error is eternal vigilance.

But it would be wrong to think that this is a problem with fMRI alone, or even neuroimaging alone. Any neuroscience experiment in which a large amount of data is collected and only some of it makes it into the final analysis is equally at risk. For example, many neuroscientists use electrodes to record the electrical activity in the brain. It's increasingly common to use not just one electrode but a whole array of them to record activity from more than brain one cell at once. This is a very powerful technique, but it raises the risk the non-independence error, because there is a temptation to only analyze the data from those electrodes where there is the "right signal", as the author's point out:

In single-cell recording, for example, it is common to select neurons according to some criterion (for example, visual responsiveness or selectivity) before applying
further analyses to the selected subset. If the selection is based on the same dataset as is used for selective analysis, biases will arise for any statistic not inherently independent of the selection criterion.

In fact, Kriegeskorte et al praise fMRI for being, in some ways, rather good at avoiding the problem:

To its great credit, neuroimaging has developed rigorous methods for statistical mapping from its beginning. Note that mapping the whole measurement volume avoids selection altogether; we can analyze and report results for all locations equally, while accounting for the multiple tests performed across locations..

With any luck, the publication of this paper and Vul's so close together will force the neuroscience community to seriously confront this error and related statistical weaknesses in modern neuroscience data analysis. Neuroscience can only emerge stronger from the debate.

Kriegeskorte, N., Simmons, W., Bellgowan, P., & Baker, C. (2009). Circular analysis in systems neuroscience: the dangers of double dipping Nature Neuroscience DOI: 10.1038/nn.2303

Help! There's an Epidemic of Anxiety! (Part I)

All British journalists are psychotic. Pathologically obsessed with "mental health issues", and suffering from grandiose delusions of their competence to discuss them, these demented maniacs...

Sorry. I got a bit carried away there. But you'll forgive me, because I was just following the example of seemingly everyone in the British media these past couple of weeks. If you believe the headlines, we're in the grip of an epidemic of anxiety:

BBC: UK society 'increasingly fearful'

The Telegraph: Britons 'living in fear' as record numbers suffer from anxiety

The Independent: Britain is becoming a more fearful place – and the economy is paying the price. The Indie also ran a comment by Janet Street-Porter - "The main reason people feel anxious is loneliness.", thanks Janet, qualifications: none, career path: fashion journalist - and a piece by a clinically anxious person - "I reckon a root cause of my anxiety is the modern notion that we can do away with risk by anticipating every imaginable danger."

It all started with a report by the Mental Health Foundation called In The Face Of Fear. The Mental Health Foundation are a perfectly decent charity organization, although they have a prior history of endorsing slightly dodgy research. One of their previous reports, Feeding Minds: The Impact of Food on Mental Health, presented a simplistic and overblown account of the effects of nutrition upon mood and drew heavily on the "work" of Patrick Holford, vitamin pill peddler and well-documented crank. Parts of the present report are, unfortunately, dodgy as well, as you'll see below.

In The Face of Fear is actually quite thought-provoking piece of writing, but you wouldn't know that from reading the newspapers. The headlines are all about the supposed surge in anxiety amongst the British population. This, however, is the dodgiest part of the report. Firstly, the report's authors surveyed 2246 British adults in January 2009. 37% said that they get frightened or anxious more often than they used to, 28% disagreed, and 33% neither agreed nor disagreed.

That's it. That's the finding. It's really not very impressive, because quite apart from anything else, it relies upon the respondent's ability to remember how anxious they were in the past. You just can't trust people to do hard stuff like that. I know exactly what I'm worried about today - I can't remember very well what I worried about ten years ago - so I must be more worried today! Of course, this could also work in reverse, and people might forget their past lack of anxiety and wrongly say that they are less anxious today.

The survey also found that 77% of people said that "people in general" are more anxious than they used to be, while just 3% disagreed. But remember that only (at most) 37 out of those 77% said that they themselves were actually more anxious. Hmm. So the real finding here seems to be that there is a widespread perception that other people are becoming more anxious, though it's anyone's guess whether this is in fact true. The report itself does note that

more than twice as many of us agree that people in general and the world itself are becoming more frightened and frightening as agree that they themselves are more frightened and anxious

This was rather too subtle for the newspapers, though, who reported... that people are becoming more anxious.

In The Face of Fear also cites a government study on the mental health of the British population, the Adult Psychiatric Morbidity Survey. Their use of this data, however, is selective to the point of being deception. This was a household survey of a weighted sample of the British population. That section of the population who live in houses and don't mind being interviewed about their mental health, that is. Diagnoses were made on the basis of the CIS-R interview, which scores each person on a number of symptoms (including "worry", "fatigue", and "depressive ideas"). Each person is then given a total score; a total score of 12 or more is (arbitrarily) designated to indicate a "neurotic disorder".

This was done in 1993, 2000 and 2007. The 2007 report notes that overall, levels of neurotic disorders increased between 1993 and 2000, but then stayed level in 2007. In terms of anxiety disorders, there was a very small increase in "generalized anxiety disorder" (from 4.4% to 4.7%), which mostly happened between 1993 and 2000; there was an increase in phobias, from 1993 2.2% to 2007 2.6%, but rates peaked at 2.8% in 2000; and "mixed anxiety and depressive disorder" increased from 7.5% in 1993 to 9.4% in 2000 to 9.7% in 2007.

What to make of that? It's hard to know, but it's clear that any worsening in anxiety levels occured some time between 1993 and 2000. Mysteriously, while the Mental Health Foundation report cites the 1993 and the 2007 figures, and makes much of the increase, it simply ignores and does not mention the 2000 figures, which show that any increase has long since stopped. It's history, not current events. Back in 2000, you might recall, the twin towers were still standing, The Simpsons was still funny, and Who Let The Dogs Out was top of the charts.

Overall, the evidence that people in Britian are actually feeling more and more anxious is extremely thin. In fact, I would say that it's a myth. It's a very popular myth, however: 77% of the population believe it. Why? Well, the fact that the Mental Health Foundation seem determined to make the data fit that story can't be helping matters. The newspapers, not to be outdone, focussed entirely on the scariest and most pesimissitic aspects of the report.

A poor show all round, but - as always on Neuroskeptic - there are some important lessons here about how we think about threats, social change, and "crisis". Stay tuned for the good stuff next post.

[BPSDB]

Help! There's an Epidemic of Anxiety! (Part I)

All British journalists are psychotic. Pathologically obsessed with "mental health issues", and suffering from grandiose delusions of their competence to discuss them, these demented maniacs...

Sorry. I got a bit carried away there. But you'll forgive me, because I was just following the example of seemingly everyone in the British media these past couple of weeks. If you believe the headlines, we're in the grip of an epidemic of anxiety:

BBC: UK society 'increasingly fearful'

The Telegraph: Britons 'living in fear' as record numbers suffer from anxiety

The Independent: Britain is becoming a more fearful place – and the economy is paying the price. The Indie also ran a comment by Janet Street-Porter - "The main reason people feel anxious is loneliness.", thanks Janet, qualifications: none, career path: fashion journalist - and a piece by a clinically anxious person - "I reckon a root cause of my anxiety is the modern notion that we can do away with risk by anticipating every imaginable danger."

It all started with a report by the Mental Health Foundation called In The Face Of Fear. The Mental Health Foundation are a perfectly decent charity organization, although they have a prior history of endorsing slightly dodgy research. One of their previous reports, Feeding Minds: The Impact of Food on Mental Health, presented a simplistic and overblown account of the effects of nutrition upon mood and drew heavily on the "work" of Patrick Holford, vitamin pill peddler and well-documented crank. Parts of the present report are, unfortunately, dodgy as well, as you'll see below.

In The Face of Fear is actually quite thought-provoking piece of writing, but you wouldn't know that from reading the newspapers. The headlines are all about the supposed surge in anxiety amongst the British population. This, however, is the dodgiest part of the report. Firstly, the report's authors surveyed 2246 British adults in January 2009. 37% said that they get frightened or anxious more often than they used to, 28% disagreed, and 33% neither agreed nor disagreed.

That's it. That's the finding. It's really not very impressive, because quite apart from anything else, it relies upon the respondent's ability to remember how anxious they were in the past. You just can't trust people to do hard stuff like that. I know exactly what I'm worried about today - I can't remember very well what I worried about ten years ago - so I must be more worried today! Of course, this could also work in reverse, and people might forget their past lack of anxiety and wrongly say that they are less anxious today.

The survey also found that 77% of people said that "people in general" are more anxious than they used to be, while just 3% disagreed. But remember that only (at most) 37 out of those 77% said that they themselves were actually more anxious. Hmm. So the real finding here seems to be that there is a widespread perception that other people are becoming more anxious, though it's anyone's guess whether this is in fact true. The report itself does note that

more than twice as many of us agree that people in general and the world itself are becoming more frightened and frightening as agree that they themselves are more frightened and anxious

This was rather too subtle for the newspapers, though, who reported... that people are becoming more anxious.

In The Face of Fear also cites a government study on the mental health of the British population, the Adult Psychiatric Morbidity Survey. Their use of this data, however, is selective to the point of being deception. This was a household survey of a weighted sample of the British population. That section of the population who live in houses and don't mind being interviewed about their mental health, that is. Diagnoses were made on the basis of the CIS-R interview, which scores each person on a number of symptoms (including "worry", "fatigue", and "depressive ideas"). Each person is then given a total score; a total score of 12 or more is (arbitrarily) designated to indicate a "neurotic disorder".

This was done in 1993, 2000 and 2007. The 2007 report notes that overall, levels of neurotic disorders increased between 1993 and 2000, but then stayed level in 2007. In terms of anxiety disorders, there was a very small increase in "generalized anxiety disorder" (from 4.4% to 4.7%), which mostly happened between 1993 and 2000; there was an increase in phobias, from 1993 2.2% to 2007 2.6%, but rates peaked at 2.8% in 2000; and "mixed anxiety and depressive disorder" increased from 7.5% in 1993 to 9.4% in 2000 to 9.7% in 2007.

What to make of that? It's hard to know, but it's clear that any worsening in anxiety levels occured some time between 1993 and 2000. Mysteriously, while the Mental Health Foundation report cites the 1993 and the 2007 figures, and makes much of the increase, it simply ignores and does not mention the 2000 figures, which show that any increase has long since stopped. It's history, not current events. Back in 2000, you might recall, the twin towers were still standing, The Simpsons was still funny, and Who Let The Dogs Out was top of the charts.

Overall, the evidence that people in Britian are actually feeling more and more anxious is extremely thin. In fact, I would say that it's a myth. It's a very popular myth, however: 77% of the population believe it. Why? Well, the fact that the Mental Health Foundation seem determined to make the data fit that story can't be helping matters. The newspapers, not to be outdone, focussed entirely on the scariest and most pesimissitic aspects of the report.

A poor show all round, but - as always on Neuroskeptic - there are some important lessons here about how we think about threats, social change, and "crisis". Stay tuned for the good stuff next post.

[BPSDB]

The Hollow Mask Illusion: Beyond Charlie Chaplin

Update - This paper dragon is an even better illustration of the effect, and you can make your own (if you have a printer). Amaze your friends! Really, you will.

Everyone's talking about the hollow mask illusion, a.k.a the hollow face illusion. Wired have a nice piece about this freaky visual phenomenon, complete with YouTube video so that you can see it for yourself. It's seriously weird. Here it is again, lifted from YouTube with KeepVid.com:

The illusion is a form of depth inversion. It involves a hollow (concave) object which appears to be non-hollow (convex). This happens whether the object is stationary or moving, but it's even more striking when it's in motion, as in the video above. When the mask of Charlie Chaplin rotates so that the inside is facing you, it suddenly appears as if it's looking out at you - but rotating in the opposite direction. This happens even though you know what's really going on.

The current surge of interest in the illusion was sparked by a recent fMRI study, Understanding why patients with schizophrenia do not perceive the hollow-mask illusion using dynamic causal modelling. But the fact that people with schizophrenia are generally immune to this illusion has been known for a long time. The illusion itself is even older - in fact, in one form or another, it goes back centuries.

But why exactly does it happen? That's an important question, because if you want to understand why schizophrenics are immune to it, you really need to know why it works on "normal people". (Notice that we normal people are the ones who are fooled while schizophrenics see reality as it is - R. D. Laing would be so pleased).

Most people seem to assume that the answer is pretty simple: it's expectation. We strongly expect things to be convex, so when we see something concave our brain tries to re-interpret it as convex. Easy! Hold on. There's a bit more to it than that.

The intricacies of the mask illusion are discussed in a paper called The hollow-face illusion: Object-specific knowledge, general assumptions or properties of the stimulus? The authors, Hill and Johnston, start out by discussing three possible explanations for the illusion.


First off, it could be that the illusion is driven by object-specific knowledge, i.e. knowledge about faces. (I've previously discussed the theory that faces are "special" - that our brains are specialized to percieve human faces.) According to this account, our brains expect that faces are convex, not hollow. This "top-down" expectation is so strong that it over-rides the "bottom-up" data of our eyes, and we see what we expect to see. Presumably, we also have specific expectations about teddy-bears and pineapples, which is why we see the hollow jelly moulds (above) as convex...

But Hill and Johnston point out that there's a second possibility - maybe our brains just expect everything to be convex. Rather than being about the specific object - a mask or face - the illusion might represent a more general expectation of convexity. There's some evidence for this, because there have been reports that the illusion works even for objects which the viewer has never seen before.

A variant of this explanation claims that the illusion is all about light. Maybe we expect that light always comes from above - because after all, it usually does. So we assume that the hollow mask is actually a convex face lit from above. This isn't a very good theory, however, especially because in the video above, the light actually comes from the side...

The final possible explanation considered by Hill & Johnston has nothing to do with expectation at all. Some people have claimed that the illusion occurs because the information reaching our eyes is ambiguous - it simply doesn't tell us whether the object is convex or concave. However, as Hill and Johnston point out, this is only true of information reaching one eye. We have two eyes, which gives us depth perception, meaning that we should be able to tell that the mask is hollow. Also, this wouldn't explain why the hollow mask never looks hollow. If it were ambiguous, it should be 50-50 whether it looks convex or concave.

They then go on to report the results of six different experiments investigating various aspects of the illusion. These are worth reading as they're a good example of the ways in which even something as subjective as visual illusions can be scientifically studied. After considering all of the resuls Hill & Johnston conclude

In summary, the hollow-face illusion appears to reflect a combination of the explanations offered. Some ambiguously interpretable bottom-up data must be present.That, coupled with a general bias towards convexity, is sufficient to generate the illusion, even when this interpretation is incompatible with other, unambiguous, bottom-up data. However, familiar orientations and patterns of shading and surface-colour information can greatly enhance this effect for both faces and other familiar objects.

In other words, the illusion probably is driven by expectation, but it also relies on their being some ambigious information in the first place. And while the expectations in question don't need to be about specific objects, like faces, it helps if they are.

Hill, H., & Johnston, A. (2007). The hollow-face illusion: Object-specific knowledge, general assumptions or properties of the stimulus? Perception, 36 (2), 199-223 DOI: 10.1068/p5523

The Hollow Mask Illusion: Beyond Charlie Chaplin

Update - This paper dragon is an even better illustration of the effect, and you can make your own (if you have a printer). Amaze your friends! Really, you will.

Everyone's talking about the hollow mask illusion, a.k.a the hollow face illusion. Wired have a nice piece about this freaky visual phenomenon, complete with YouTube video so that you can see it for yourself. It's seriously weird. Here it is again, lifted from YouTube with KeepVid.com:

The illusion is a form of depth inversion. It involves a hollow (concave) object which appears to be non-hollow (convex). This happens whether the object is stationary or moving, but it's even more striking when it's in motion, as in the video above. When the mask of Charlie Chaplin rotates so that the inside is facing you, it suddenly appears as if it's looking out at you - but rotating in the opposite direction. This happens even though you know what's really going on.

The current surge of interest in the illusion was sparked by a recent fMRI study, Understanding why patients with schizophrenia do not perceive the hollow-mask illusion using dynamic causal modelling. But the fact that people with schizophrenia are generally immune to this illusion has been known for a long time. The illusion itself is even older - in fact, in one form or another, it goes back centuries.

But why exactly does it happen? That's an important question, because if you want to understand why schizophrenics are immune to it, you really need to know why it works on "normal people". (Notice that we normal people are the ones who are fooled while schizophrenics see reality as it is - R. D. Laing would be so pleased).

Most people seem to assume that the answer is pretty simple: it's expectation. We strongly expect things to be convex, so when we see something concave our brain tries to re-interpret it as convex. Easy! Hold on. There's a bit more to it than that.

The intricacies of the mask illusion are discussed in a paper called The hollow-face illusion: Object-specific knowledge, general assumptions or properties of the stimulus? The authors, Hill and Johnston, start out by discussing three possible explanations for the illusion.


First off, it could be that the illusion is driven by object-specific knowledge, i.e. knowledge about faces. (I've previously discussed the theory that faces are "special" - that our brains are specialized to percieve human faces.) According to this account, our brains expect that faces are convex, not hollow. This "top-down" expectation is so strong that it over-rides the "bottom-up" data of our eyes, and we see what we expect to see. Presumably, we also have specific expectations about teddy-bears and pineapples, which is why we see the hollow jelly moulds (above) as convex...

But Hill and Johnston point out that there's a second possibility - maybe our brains just expect everything to be convex. Rather than being about the specific object - a mask or face - the illusion might represent a more general expectation of convexity. There's some evidence for this, because there have been reports that the illusion works even for objects which the viewer has never seen before.

A variant of this explanation claims that the illusion is all about light. Maybe we expect that light always comes from above - because after all, it usually does. So we assume that the hollow mask is actually a convex face lit from above. This isn't a very good theory, however, especially because in the video above, the light actually comes from the side...

The final possible explanation considered by Hill & Johnston has nothing to do with expectation at all. Some people have claimed that the illusion occurs because the information reaching our eyes is ambiguous - it simply doesn't tell us whether the object is convex or concave. However, as Hill and Johnston point out, this is only true of information reaching one eye. We have two eyes, which gives us depth perception, meaning that we should be able to tell that the mask is hollow. Also, this wouldn't explain why the hollow mask never looks hollow. If it were ambiguous, it should be 50-50 whether it looks convex or concave.

They then go on to report the results of six different experiments investigating various aspects of the illusion. These are worth reading as they're a good example of the ways in which even something as subjective as visual illusions can be scientifically studied. After considering all of the resuls Hill & Johnston conclude

In summary, the hollow-face illusion appears to reflect a combination of the explanations offered. Some ambiguously interpretable bottom-up data must be present.That, coupled with a general bias towards convexity, is sufficient to generate the illusion, even when this interpretation is incompatible with other, unambiguous, bottom-up data. However, familiar orientations and patterns of shading and surface-colour information can greatly enhance this effect for both faces and other familiar objects.

In other words, the illusion probably is driven by expectation, but it also relies on their being some ambigious information in the first place. And while the expectations in question don't need to be about specific objects, like faces, it helps if they are.

Hill, H., & Johnston, A. (2007). The hollow-face illusion: Object-specific knowledge, general assumptions or properties of the stimulus? Perception, 36 (2), 199-223 DOI: 10.1068/p5523

Annotated Links

Sydney Spiesel writes about the myriad claimed treatments for autism in Slate. He's skeptical

If there is any illness for which 100 treatments are available, you can be sure that none of them works.

True. But he doesn't do a great job of addressing why parents swear by such ineffective treatments. His answer is the "Hawthorne Effect". I think there's rather more to it than that. For one thing, Spiesel does not consider the possibility that a treatment might have no effect at all - not even a non-specific "placebo effect" - and still become popular.

But that happens. A PLoS ONE paper, From Traditional Medicine to Witchcraft, tries to explain why. Although it features some maths and lots of graphs, the argument is summed up in a sentence

Superstitious treatments and maladaptive practices can spread because their very ineffectiveness results in sick individuals demonstrating the practice for longer than efficacious treatments, leading to more salient demonstration and more converts

In other words, the less well a treatment works, the longer it gets used, and therefore, the more likely it is for other people to see it being used and adopt it. Of course this only holds under when people are completely unable to tell whether treatments used by others work or not. This may be a valid assumption.


Psychology Today interviews rebellious British psychiatrist David Healy about his new book, Mania, which I really need to read. Healy notes that bipolar disorder became a fashionable diagnosis starting in the mid 1990s. A while back I plotted a graph showing how often bipolar disorder was mentioned in the British media. It became much more popular after about 2000 - which sort of makes sense.

Healy's one of the few people who manages to be deeply skeptical of much about modern psychiatric diagnosis and treatment while avoiding Tom Cruiseist anti-psychiatry. His last book was a homage to ECT, ferchrisakes. A lot of people felt actively betrayed by that. But if you still doubt Healy's intellect, his use in the interview of a Buffy metaphor to explain the history of "mood stabilizing drugs" should set you straight. Genius.

Annotated Links

Sydney Spiesel writes about the myriad claimed treatments for autism in Slate. He's skeptical

If there is any illness for which 100 treatments are available, you can be sure that none of them works.

True. But he doesn't do a great job of addressing why parents swear by such ineffective treatments. His answer is the "Hawthorne Effect". I think there's rather more to it than that. For one thing, Spiesel does not consider the possibility that a treatment might have no effect at all - not even a non-specific "placebo effect" - and still become popular.

But that happens. A PLoS ONE paper, From Traditional Medicine to Witchcraft, tries to explain why. Although it features some maths and lots of graphs, the argument is summed up in a sentence

Superstitious treatments and maladaptive practices can spread because their very ineffectiveness results in sick individuals demonstrating the practice for longer than efficacious treatments, leading to more salient demonstration and more converts

In other words, the less well a treatment works, the longer it gets used, and therefore, the more likely it is for other people to see it being used and adopt it. Of course this only holds under when people are completely unable to tell whether treatments used by others work or not. This may be a valid assumption.


Psychology Today interviews rebellious British psychiatrist David Healy about his new book, Mania, which I really need to read. Healy notes that bipolar disorder became a fashionable diagnosis starting in the mid 1990s. A while back I plotted a graph showing how often bipolar disorder was mentioned in the British media. It became much more popular after about 2000 - which sort of makes sense.

Healy's one of the few people who manages to be deeply skeptical of much about modern psychiatric diagnosis and treatment while avoiding Tom Cruiseist anti-psychiatry. His last book was a homage to ECT, ferchrisakes. A lot of people felt actively betrayed by that. But if you still doubt Healy's intellect, his use in the interview of a Buffy metaphor to explain the history of "mood stabilizing drugs" should set you straight. Genius.