Psychiatry and Phrenology

The notorious John P. "Most Published Research Findings Are False" Ioannidis has turned his baleful statistical gaze upon the literature on brain volume abnormalities in psychiatric disorders.


Reports of regional volume differences in the brains of people with mental illness compared to healthy people have appeared in increasing numbers in recent years. Such studies have given plenty of positive results. People with depression have smaller hippocampi. The amygdala is bigger in people with autism. And so on.

Last month, Ioannidis took a comprehensive look at this literature and he argues that it suffers from a fairly serious case of "excess significance bias" - essentially, that scientists are somehow biased towards reporting differences between patients and controls, and are not telling people about the times when there wasn't a difference. This could be because of publication bias, p-value fishing or other scientific sins.

Scientists tend to call a difference between two groups significant if it has a p value of less than 0.05. This means that if there were no real difference, just some random noise, this result would be less than 5% likely to occur.

However, there's many ways you could end up with a low (i.e. good) p value. You would get a significant result, even if the true difference was very small, if you do a big enough study. Even a small difference will be detected if you study enough people. On the other hand, when the true difference is huge, you might only need a small study to get the same p value.

A power calculation is a way of specifying how likely a given study would be to detect a difference of a given size, based on the size of the study. These are usually used ahead of time to work out how big your upcoming study needs to be, assuming you can guess roughly how big the real effect you're interested in is going to be.

Ioannidis turned this on its head and asked: assuming that the true difference in the brain volume is what the average of all the published studies says it is, how many of the published studies were big enough that they ought to have succesfully detected it?

He found 41 seperate meta-analyses for different brain regions in various disorders. These were published in 8 papers - because each paper reported on multiple regions. He only looked at meta-analyses published in the past 4 years, but these analyses will themselves have included older work. This means that this paper is a kind of meta-meta-analysis. He didn't directly consider the raw brain scans at all.

The meta-analyses found many significant volume differences - but in 29 of those 41, there was an excess of significant papers. In other words, the papers were too small to have a good chance to detect the effect that they themselves found - suggesting that something funny was going on. Although, strangely, in 10/41 there were too few, and only in 2 were there the "right" number.


For what it's worth, studies on schizophrenia and on relatives-of-people-with-schizophrenia showed the least evidence of this problem, while autism was terrible, with 4 times as many significant papers as expected by chance. I'm not sure this is worth much, though. We don't know if this tells us more about schizophrenia vs autism, or more about the researchers that study them.

Anyway, this is an important study, and the inverse power calculation approach is certainly a useful one. It's not new, but it's not used as widely as it ought to be. It does make the assumption that the meta-analyses are "right" about the effect size, and then paradoxically concludes that they are biased. However, this means that the true bias is probably even bigger than this suggests (because if the analyses as biased, the true effect size is smaller than assumed, and the studies should have been even less likely to find it.)

Unfortunately, this doesn't tell us which of the studies are wrong, so it's not directly useful for people researching mental illness. It tells us that there is something wrong with scientific publishing, however. Truth be told, I suspect that a similar picture would emerge if you did this kind of thing in many other fields of science. The only real solution, in my book, would be to require the pre-registration of scientific studies. Ioannidis actually advocates this at the end of the paper.

Ioannidis JP (2011). Excess Significance Bias in the Literature on Brain Volume Abnormalities. Archives of general psychiatry PMID: 21464342

Psychiatry and Phrenology

The notorious John P. "Most Published Research Findings Are False" Ioannidis has turned his baleful statistical gaze upon the literature on brain volume abnormalities in psychiatric disorders.


Reports of regional volume differences in the brains of people with mental illness compared to healthy people have appeared in increasing numbers in recent years. Such studies have given plenty of positive results. People with depression have smaller hippocampi. The amygdala is bigger in people with autism. And so on.

Last month, Ioannidis took a comprehensive look at this literature and he argues that it suffers from a fairly serious case of "excess significance bias" - essentially, that scientists are somehow biased towards reporting differences between patients and controls, and are not telling people about the times when there wasn't a difference. This could be because of publication bias, p-value fishing or other scientific sins.

Scientists tend to call a difference between two groups significant if it has a p value of less than 0.05. This means that if there were no real difference, just some random noise, this result would be less than 5% likely to occur.

However, there's many ways you could end up with a low (i.e. good) p value. You would get a significant result, even if the true difference was very small, if you do a big enough study. Even a small difference will be detected if you study enough people. On the other hand, when the true difference is huge, you might only need a small study to get the same p value.

A power calculation is a way of specifying how likely a given study would be to detect a difference of a given size, based on the size of the study. These are usually used ahead of time to work out how big your upcoming study needs to be, assuming you can guess roughly how big the real effect you're interested in is going to be.

Ioannidis turned this on its head and asked: assuming that the true difference in the brain volume is what the average of all the published studies says it is, how many of the published studies were big enough that they ought to have succesfully detected it?

He found 41 seperate meta-analyses for different brain regions in various disorders. These were published in 8 papers - because each paper reported on multiple regions. He only looked at meta-analyses published in the past 4 years, but these analyses will themselves have included older work. This means that this paper is a kind of meta-meta-analysis. He didn't directly consider the raw brain scans at all.

The meta-analyses found many significant volume differences - but in 29 of those 41, there was an excess of significant papers. In other words, the papers were too small to have a good chance to detect the effect that they themselves found - suggesting that something funny was going on. Although, strangely, in 10/41 there were too few, and only in 2 were there the "right" number.


For what it's worth, studies on schizophrenia and on relatives-of-people-with-schizophrenia showed the least evidence of this problem, while autism was terrible, with 4 times as many significant papers as expected by chance. I'm not sure this is worth much, though. We don't know if this tells us more about schizophrenia vs autism, or more about the researchers that study them.

Anyway, this is an important study, and the inverse power calculation approach is certainly a useful one. It's not new, but it's not used as widely as it ought to be. It does make the assumption that the meta-analyses are "right" about the effect size, and then paradoxically concludes that they are biased. However, this means that the true bias is probably even bigger than this suggests (because if the analyses as biased, the true effect size is smaller than assumed, and the studies should have been even less likely to find it.)

Unfortunately, this doesn't tell us which of the studies are wrong, so it's not directly useful for people researching mental illness. It tells us that there is something wrong with scientific publishing, however. Truth be told, I suspect that a similar picture would emerge if you did this kind of thing in many other fields of science. The only real solution, in my book, would be to require the pre-registration of scientific studies. Ioannidis actually advocates this at the end of the paper.

Ioannidis JP (2011). Excess Significance Bias in the Literature on Brain Volume Abnormalities. Archives of general psychiatry PMID: 21464342

The Neuro-Recession

Everyone's favourite British psychopharmacologist David "Ecstasy Vs Horseriding" Nutt joins four other leading neuroscientists to discuss the impact of the financial crisis on neuroscience, in an article over at NR:N: Neuroscience in recession?

It's interesting to get an international perspective. Susan Amara, President of the Society for Neuroscience, says that American scientists were encouraged by the surprise $10bn boost to NIH funds that made it into the 2009 economic stimulus package. But these funds are due to run out in 2012.

Meanwhile, in Europe, some countries have slashed funding as part of their austerity programmes - Greece most of all - while the larger and richer nations like France and Germany have protected science. Japan has also opted against major cuts, so far, but with a massive deficit, researchers fear that the axe will fall in coming years.

A repeated complaint is that biomedical research has faced a rate of inflation much higher than the rate experienced by the economy as a whole. Nutt says that if the overall inflation rate is 4% per year, the rate paid by scientists is more like 10%. As a result, even if nominal budgets are protected, the real budget will fall. The current British government has decided to keep nominal science funding flat, while cutting pretty much everything else, which is nice, but it still means falling real investment.

So everyone pretty much agrees that there are cuts, and cuts are bad. OK. Where things get more interesting is in the debate over what this means for individual scientists. Susan Amara says that she fears that investigator-initiated "R01" grants are in danger. These are when a scientist gets an idea, writes it up as a proposal and says "Isn't this cool? Can we have some money to do it?"

Amara warns that this kind of thing seems to be getting harder, while established, ongoing research programmes are being protected. But Tom Insel, head of the NIMH and, therefore, the guy with ultimate responsibility for these R01 grants, says the exact opposite. Insel claims that R01s are being protected in favour of the big programmes! "Where have we cut back in order to preserve R01 grants? ... We have reduced the budget of our intramural research programme."

Who's right on this point? I'm not sure. Maybe US readers might be able to comment.

The authors express particular worry that young neuroscientists (postdocs and PhD students) will suffer, either directly, as a result of not being able to find money, or indirectly in terms of poor morale and a sense that their talents might be better rewarded outside of science - leading to long-term harm to the next generation of neuroscientists.

They offer some words of encouragement, though, saying that the pendulum will swing back towards more investment in the future. Until then, hang on as best you can, even if it means being willing to move to find work with a supervisor, or in a country, which does have good funding prospects...

Amara SG, Grillner S, Insel T, Nutt D, & Tsumoto T (2011). Neuroscience in recession? Nature reviews. Neuroscience, 12 (5), 297-302 PMID: 21505517

The Neuro-Recession

Everyone's favourite British psychopharmacologist David "Ecstasy Vs Horseriding" Nutt joins four other leading neuroscientists to discuss the impact of the financial crisis on neuroscience, in an article over at NR:N: Neuroscience in recession?

It's interesting to get an international perspective. Susan Amara, President of the Society for Neuroscience, says that American scientists were encouraged by the surprise $10bn boost to NIH funds that made it into the 2009 economic stimulus package. But these funds are due to run out in 2012.

Meanwhile, in Europe, some countries have slashed funding as part of their austerity programmes - Greece most of all - while the larger and richer nations like France and Germany have protected science. Japan has also opted against major cuts, so far, but with a massive deficit, researchers fear that the axe will fall in coming years.

A repeated complaint is that biomedical research has faced a rate of inflation much higher than the rate experienced by the economy as a whole. Nutt says that if the overall inflation rate is 4% per year, the rate paid by scientists is more like 10%. As a result, even if nominal budgets are protected, the real budget will fall. The current British government has decided to keep nominal science funding flat, while cutting pretty much everything else, which is nice, but it still means falling real investment.

So everyone pretty much agrees that there are cuts, and cuts are bad. OK. Where things get more interesting is in the debate over what this means for individual scientists. Susan Amara says that she fears that investigator-initiated "R01" grants are in danger. These are when a scientist gets an idea, writes it up as a proposal and says "Isn't this cool? Can we have some money to do it?"

Amara warns that this kind of thing seems to be getting harder, while established, ongoing research programmes are being protected. But Tom Insel, head of the NIMH and, therefore, the guy with ultimate responsibility for these R01 grants, says the exact opposite. Insel claims that R01s are being protected in favour of the big programmes! "Where have we cut back in order to preserve R01 grants? ... We have reduced the budget of our intramural research programme."

Who's right on this point? I'm not sure. Maybe US readers might be able to comment.

The authors express particular worry that young neuroscientists (postdocs and PhD students) will suffer, either directly, as a result of not being able to find money, or indirectly in terms of poor morale and a sense that their talents might be better rewarded outside of science - leading to long-term harm to the next generation of neuroscientists.

They offer some words of encouragement, though, saying that the pendulum will swing back towards more investment in the future. Until then, hang on as best you can, even if it means being willing to move to find work with a supervisor, or in a country, which does have good funding prospects...

Amara SG, Grillner S, Insel T, Nutt D, & Tsumoto T (2011). Neuroscience in recession? Nature reviews. Neuroscience, 12 (5), 297-302 PMID: 21505517

The Schizophrenic Computer

All over the world, inanimate objects are getting schizophrenia. Last week, it was a dish (full of neurons).

Before that, it was a computer program. That's according to a paper, which appeared in Biological Psychiatry last month, although it involved no biology, called Using Computational Patients to Evaluate Illness Mechanisms in Schizophrenia.

The authors set up a neural network model, called DISCERN, and trained it to "read" stories. The nuts and bolts are, we're reassured, not something that readers of Biological Psychiatry need to worry about: "Its details, many of which are not essential in understanding this study..."

Anyway, it's basically a series of connectionist models. These are computer simulations of a large number of simple units, or nodes, which can have "activations" of varying strengths, and which have "connections" to other nodes. The model "learns" by modifying the strength of these connections according to some kind of simple learning rule.

Connectionist models are a bit like brains, in other words. A bit. They're several orders of magnitude simpler than a real brain, in several different respects. Still, they can "learn" to do some quite complicated things. You can train them to recognise faces and stuff, which is not trivial.


Anyway, DISCERN is a connectionist model of language, but it's not necessary a model of how the human brain actually learns language. Because we just have no idea how the human brain does that. We don't even know if our brain acts as a connectionist network at all, above the cellular level. Some cognitive scientists think it is, but others think that those guys are talking out of an orifice connected to their mouth, but not their mouth. Not in so many words you understand.

So they set up this system and got it to learn 28 stories, each of which consisted of multiple sentences. Some of the stories were the autobiography of a doctor - "I was a doctor. I worked in New York. I liked my job. I was good doctor" - he was not a great communicator, clearly. Others were a story about gangster ("Tony was a gangster. Tony worked in Chicago..." etc.) The network had to read these stories and then recall them.

The core of the study was that they tested to see what happened when they interfered with the program by introducing certain bugs - interfering with the activations or connections of nodes in particular parts of the model. They tried 8.

They compared the computer's performance to that of 37 actual patients with schizophrenia (or the related schizoaffective disorder) who were tested on a similar task, compared to 20 healthy controls. When the human patients came to recall the stories they'd read, they tended to make more errors of particular kinds: mixing up who did what ("agent switching"), and adding stuff that wasn't in the story ("derailment").

What they found was that DISCERN made the same kinds of errors when it was given 2 particular deficits, "working memory disconnection" and "hyperlearning". The other 6 deficits didn't cause the same pattern of findings. Hyperlearning was the best match.

They comment that

A majority of three-parameter best-fit hyperlearning simulations also recurrently confused specific agents in personal stories (including the self-representation) with specific agents in crime stories (and vice versa) in a highly nonrandom fashion.

Noteworthy was the high frequency of agent-slotting exchanges between the hospital boss, Joe, and the Mafia boss, Vito, and parallel confusions between the “I” self-reference and underling Mafia members, suggesting generalization of boss/underling relationships.

Insofar as story scripts provide templates for assigning intentions to agents, a consequence of recurrent agent-slotting confusions could be assignment of intentions and roles to autobiographical characters (possibly including the self) that borrow from impersonal stories derived from culture or the media.

Confusion between agent representations in autobiographical stories and those in culturally determined narratives could account for the bizarreness of fixed, self-referential delusions, e.g., a patient insisting that her father-in-law is Saddam Hussein or that she herself is the Virgin Mary.

So if you believe it, they've just made a program that experiences schizophrenic-type paranoid delusions.

It's fair to say that this is speculative. On the other hand, it's an interesting approach, and at least it's theory-based, rather than just an attempt to use ever more powerful genetic, neuroimaging and biological techniques to find differences between a patient group and a control group.

Hoffman RE, Grasemann U, Gueorguieva R, Quinlan D, Lane D, & Miikkulainen R (2011). Using computational patients to evaluate illness mechanisms in schizophrenia. Biological psychiatry, 69 (10), 997-1005 PMID: 21397213

The Schizophrenic Computer

All over the world, inanimate objects are getting schizophrenia. Last week, it was a dish (full of neurons).

Before that, it was a computer program. That's according to a paper, which appeared in Biological Psychiatry last month, although it involved no biology, called Using Computational Patients to Evaluate Illness Mechanisms in Schizophrenia.

The authors set up a neural network model, called DISCERN, and trained it to "read" stories. The nuts and bolts are, we're reassured, not something that readers of Biological Psychiatry need to worry about: "Its details, many of which are not essential in understanding this study..."

Anyway, it's basically a series of connectionist models. These are computer simulations of a large number of simple units, or nodes, which can have "activations" of varying strengths, and which have "connections" to other nodes. The model "learns" by modifying the strength of these connections according to some kind of simple learning rule.

Connectionist models are a bit like brains, in other words. A bit. They're several orders of magnitude simpler than a real brain, in several different respects. Still, they can "learn" to do some quite complicated things. You can train them to recognise faces and stuff, which is not trivial.


Anyway, DISCERN is a connectionist model of language, but it's not necessary a model of how the human brain actually learns language. Because we just have no idea how the human brain does that. We don't even know if our brain acts as a connectionist network at all, above the cellular level. Some cognitive scientists think it is, but others think that those guys are talking out of an orifice connected to their mouth, but not their mouth. Not in so many words you understand.

So they set up this system and got it to learn 28 stories, each of which consisted of multiple sentences. Some of the stories were the autobiography of a doctor - "I was a doctor. I worked in New York. I liked my job. I was good doctor" - he was not a great communicator, clearly. Others were a story about gangster ("Tony was a gangster. Tony worked in Chicago..." etc.) The network had to read these stories and then recall them.

The core of the study was that they tested to see what happened when they interfered with the program by introducing certain bugs - interfering with the activations or connections of nodes in particular parts of the model. They tried 8.

They compared the computer's performance to that of 37 actual patients with schizophrenia (or the related schizoaffective disorder) who were tested on a similar task, compared to 20 healthy controls. When the human patients came to recall the stories they'd read, they tended to make more errors of particular kinds: mixing up who did what ("agent switching"), and adding stuff that wasn't in the story ("derailment").

What they found was that DISCERN made the same kinds of errors when it was given 2 particular deficits, "working memory disconnection" and "hyperlearning". The other 6 deficits didn't cause the same pattern of findings. Hyperlearning was the best match.

They comment that

A majority of three-parameter best-fit hyperlearning simulations also recurrently confused specific agents in personal stories (including the self-representation) with specific agents in crime stories (and vice versa) in a highly nonrandom fashion.

Noteworthy was the high frequency of agent-slotting exchanges between the hospital boss, Joe, and the Mafia boss, Vito, and parallel confusions between the “I” self-reference and underling Mafia members, suggesting generalization of boss/underling relationships.

Insofar as story scripts provide templates for assigning intentions to agents, a consequence of recurrent agent-slotting confusions could be assignment of intentions and roles to autobiographical characters (possibly including the self) that borrow from impersonal stories derived from culture or the media.

Confusion between agent representations in autobiographical stories and those in culturally determined narratives could account for the bizarreness of fixed, self-referential delusions, e.g., a patient insisting that her father-in-law is Saddam Hussein or that she herself is the Virgin Mary.

So if you believe it, they've just made a program that experiences schizophrenic-type paranoid delusions.

It's fair to say that this is speculative. On the other hand, it's an interesting approach, and at least it's theory-based, rather than just an attempt to use ever more powerful genetic, neuroimaging and biological techniques to find differences between a patient group and a control group.

Hoffman RE, Grasemann U, Gueorguieva R, Quinlan D, Lane D, & Miikkulainen R (2011). Using computational patients to evaluate illness mechanisms in schizophrenia. Biological psychiatry, 69 (10), 997-1005 PMID: 21397213

Slipping Through Time In Autism

Have you ever felt like you're reliving the past?


Have you ever felt like you're reliving the past? A curious paper from Japan: ‘Time slip’ phenomenon in adolescents and adults with autism spectrum disorders. Have you ever felt like you're...OK, sorry. I'll stop that.

The paper describes the cases of two young men with autism, who suffered from an unusual affliction - very vivid memories of a single past event. These recollections were so unpleasant that they led to outbursts of violence. In the first case, the event was somewhat traumatic in itself:

Case 1, a male patient, was 16 years old at the time of his first visit to our hospital. He had not shown any delay in language development but had been isolated and unable to make friends since his infancy... He had been bullied by a classmate when he was in the 8th grade; thereafter he refused to go to school and began to stay indoors.

One day, he clearly recalled the bullying incident that had occurred a few years earlier and re-experienced the feelings of fear and frustration as if he were once again experiencing that event. Thereafter, he often had similar experiences, even though he did not purposely intend to recall the event, and he became strongly distressed.

He and his family stated that the recalled content was always the same. He thought that the distress could only be relieved by obtaining revenge on the boy who had bullied him, and he visited the boy’s house with a knife. He was subsequently admitted to the emergency ward of our hospital.

This is not, perhaps, very surprising and sounds a bit like post-traumatic stress disorder. The second case, however, is more mysterious because the event that was remembered was, in itself, completely trivial - someone throwing away a cigarette end:

Case 2, a male patient, was 27 years old at the time of his first visit. Since an early age, he had exhibited disturbed reciprocal sociality and did not have any close friendships. His interest was limited to collecting figures of comic characters. He began to be bullied during junior high school. He entered senior high school but quit during the second year. Thereafter, he tended to seclude himself at home.

One day, he watched his neighbor discarding a cigarette butt in front of his home. Thereafter, he began to be annoyed by that memory. Almost every time he heard the voice of that neighbor or saw that man, he would leave his home and curse at the neighbor. His behavior became more violent and he eventually threatened the neighbor with a wooden sword.

The authors end by saying that out of seven autistic patients who presented to their psychiatric emergency ward, no less than four of them experienced "time slips", though it's not clear how this was diagnosed and patients presenting to the emergency ward are a highly selected population - mostly people who have suddenly become violent or aggressive.

The "time slip" phenomenon seems unknown outside of Japan. Google reveals that the only papers discussing it are Japanese. Is it something that only happens in Japan, like buru-sera? Are people with autism elsewhere experiencing this, and going unnoticed?

Tochimoto S, Kurata K, & Munesue T (2011). 'Time slip' phenomenon in adolescents and adults with autism spectrum disorders: Case series. Psychiatry and clinical neurosciences PMID: 21489047

Slipping Through Time In Autism

Have you ever felt like you're reliving the past?


Have you ever felt like you're reliving the past? A curious paper from Japan: ‘Time slip’ phenomenon in adolescents and adults with autism spectrum disorders. Have you ever felt like you're...OK, sorry. I'll stop that.

The paper describes the cases of two young men with autism, who suffered from an unusual affliction - very vivid memories of a single past event. These recollections were so unpleasant that they led to outbursts of violence. In the first case, the event was somewhat traumatic in itself:

Case 1, a male patient, was 16 years old at the time of his first visit to our hospital. He had not shown any delay in language development but had been isolated and unable to make friends since his infancy... He had been bullied by a classmate when he was in the 8th grade; thereafter he refused to go to school and began to stay indoors.

One day, he clearly recalled the bullying incident that had occurred a few years earlier and re-experienced the feelings of fear and frustration as if he were once again experiencing that event. Thereafter, he often had similar experiences, even though he did not purposely intend to recall the event, and he became strongly distressed.

He and his family stated that the recalled content was always the same. He thought that the distress could only be relieved by obtaining revenge on the boy who had bullied him, and he visited the boy’s house with a knife. He was subsequently admitted to the emergency ward of our hospital.

This is not, perhaps, very surprising and sounds a bit like post-traumatic stress disorder. The second case, however, is more mysterious because the event that was remembered was, in itself, completely trivial - someone throwing away a cigarette end:

Case 2, a male patient, was 27 years old at the time of his first visit. Since an early age, he had exhibited disturbed reciprocal sociality and did not have any close friendships. His interest was limited to collecting figures of comic characters. He began to be bullied during junior high school. He entered senior high school but quit during the second year. Thereafter, he tended to seclude himself at home.

One day, he watched his neighbor discarding a cigarette butt in front of his home. Thereafter, he began to be annoyed by that memory. Almost every time he heard the voice of that neighbor or saw that man, he would leave his home and curse at the neighbor. His behavior became more violent and he eventually threatened the neighbor with a wooden sword.

The authors end by saying that out of seven autistic patients who presented to their psychiatric emergency ward, no less than four of them experienced "time slips", though it's not clear how this was diagnosed and patients presenting to the emergency ward are a highly selected population - mostly people who have suddenly become violent or aggressive.

The "time slip" phenomenon seems unknown outside of Japan. Google reveals that the only papers discussing it are Japanese. Is it something that only happens in Japan, like buru-sera? Are people with autism elsewhere experiencing this, and going unnoticed?

Tochimoto S, Kurata K, & Munesue T (2011). 'Time slip' phenomenon in adolescents and adults with autism spectrum disorders: Case series. Psychiatry and clinical neurosciences PMID: 21489047

Schizophrenia In A Dish...?

...or a storm in a teacup?


According to a new paper just out in Nature from the prestigious Salk Institute, schizophrenia may be associated with differences in neural wiring which can be observed in cells grown in the lab, thus offering a window into the normally inaccessible development of the human brain.

The paper is here, and here's an open-access Nature news bit discussing it: Schizophrenia 'in a dish'. It's certainly an incredible piece of biology. They took fibroblasts, a cell found in the skin, from 4 patients with schizophrenia and 6 healthy controls.

Using genetically modified viruses, they turned these cells into human induced pluripotent stem cells (hiPSCs), which have the ability to become any other type of cell in the human body. Then, they made those hiPSCs turn into neurons by putting them in a dish with various brain-related chemicals and culturing them for three months. Not entirely unlike those brains-in-a-vat that philosophers like to talk about...

To test the connectivity of these cells, they then infected them with a modified rabies virus, after first infecting them yet another modified virus to make that work. Rabies can only spread from cell to cell via synapses between cells; they could spot the infected cells because the rabies was modified to carry a special fluorescent protein. So they could tell how many connections the neurons made.

What they found was that cultures derived from schizophrenia patients made fewer connections:


The distinct lack of red in the schizophrenia patient's dish shows that the rabies virus was less able to travel from cell to cell; the normal amount of green, yellow and blue shows that this wasn't just because it couldn't get into the cells in the first place.

OK, that's extremely cool. But then it gets a bit tricky. They tried adding five different antipsychotic drugs to the dishes for 3 weeks. Four did nothing; one, loxapine, made the cells form more connections. But it's odd that it was loxapine, a drug with unremarkable efficacy, which did this; they also tried clozapine, the only antipsychotic which is verifiably more effective than any others, and it didn't.

Loxapine is similar to (and metabolized to) amoxapine, an antidepressant; that's an issue, I would say, because we already know that antidepressants cause cells to sprout new connections. It would have been good to have used some antidepressants and some other medications as a control.

They did a lot of other work, but the data are hard to interpret. The cells "mis-expressed" about 600 genes, but we're not hold how many genes they tested. 25% of them had been previously linked to schizophrenia, but you could say that of lots of genes: is that more than would be expected by chance alone?

The patients were also unusual. Patient 1 suffered an onset of schizophrenia at age 6, and died by suicide aged 22; childhood-onset schizophrenia is extremely rare. Patients 2 and 3 were brother and sister; this means their data may not be independent, so there are (being conservative) only really 3 patients here.

Overall it's a great idea, a technical tour-de-force, and I'm sure we'll be seeing much more work along these lines on schizophrenia and other neurological and psychiatric disorders. However, as it stands, schizophrenia remains mysterious.

Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S, Li Y, Mu Y, Chen G, Yu D, McCarthy S, Sebat J, & Gage FH (2011). Modelling schizophrenia using human induced pluripotent stem cells. Nature PMID: 21490598

Callaway, E. (2011). Schizophrenia 'in a dish' Nature DOI: 10.1038/news.2011.232

Schizophrenia In A Dish...?

...or a storm in a teacup?


According to a new paper just out in Nature from the prestigious Salk Institute, schizophrenia may be associated with differences in neural wiring which can be observed in cells grown in the lab, thus offering a window into the normally inaccessible development of the human brain.

The paper is here, and here's an open-access Nature news bit discussing it: Schizophrenia 'in a dish'. It's certainly an incredible piece of biology. They took fibroblasts, a cell found in the skin, from 4 patients with schizophrenia and 6 healthy controls.

Using genetically modified viruses, they turned these cells into human induced pluripotent stem cells (hiPSCs), which have the ability to become any other type of cell in the human body. Then, they made those hiPSCs turn into neurons by putting them in a dish with various brain-related chemicals and culturing them for three months. Not entirely unlike those brains-in-a-vat that philosophers like to talk about...

To test the connectivity of these cells, they then infected them with a modified rabies virus, after first infecting them yet another modified virus to make that work. Rabies can only spread from cell to cell via synapses between cells; they could spot the infected cells because the rabies was modified to carry a special fluorescent protein. So they could tell how many connections the neurons made.

What they found was that cultures derived from schizophrenia patients made fewer connections:


The distinct lack of red in the schizophrenia patient's dish shows that the rabies virus was less able to travel from cell to cell; the normal amount of green, yellow and blue shows that this wasn't just because it couldn't get into the cells in the first place.

OK, that's extremely cool. But then it gets a bit tricky. They tried adding five different antipsychotic drugs to the dishes for 3 weeks. Four did nothing; one, loxapine, made the cells form more connections. But it's odd that it was loxapine, a drug with unremarkable efficacy, which did this; they also tried clozapine, the only antipsychotic which is verifiably more effective than any others, and it didn't.

Loxapine is similar to (and metabolized to) amoxapine, an antidepressant; that's an issue, I would say, because we already know that antidepressants cause cells to sprout new connections. It would have been good to have used some antidepressants and some other medications as a control.

They did a lot of other work, but the data are hard to interpret. The cells "mis-expressed" about 600 genes, but we're not hold how many genes they tested. 25% of them had been previously linked to schizophrenia, but you could say that of lots of genes: is that more than would be expected by chance alone?

The patients were also unusual. Patient 1 suffered an onset of schizophrenia at age 6, and died by suicide aged 22; childhood-onset schizophrenia is extremely rare. Patients 2 and 3 were brother and sister; this means their data may not be independent, so there are (being conservative) only really 3 patients here.

Overall it's a great idea, a technical tour-de-force, and I'm sure we'll be seeing much more work along these lines on schizophrenia and other neurological and psychiatric disorders. However, as it stands, schizophrenia remains mysterious.

Brennand KJ, Simone A, Jou J, Gelboin-Burkhart C, Tran N, Sangar S, Li Y, Mu Y, Chen G, Yu D, McCarthy S, Sebat J, & Gage FH (2011). Modelling schizophrenia using human induced pluripotent stem cells. Nature PMID: 21490598

Callaway, E. (2011). Schizophrenia 'in a dish' Nature DOI: 10.1038/news.2011.232

Who Gets Autism?

According to a major new report from Australia, social and family factors associated with autism are associated with a lower risk of intellectual disability - and vice versa. But why?


The paper is from Leonard et al and it's published in PLoS ONE, so it's open access if you want to take a peek. The authors used a database system in the state of Western Australia which allowed them to find out what happened to all of the babies born between 1984 and 1999 who were still alive as of 2005. There were 400,000 of them.

The records included information on children diagnosed with either an autism spectrum disorder (ASD), intellectual disability aka mental retardation (ID), or both. They decided to only look at singleton births i.e. not twins or triplets.

In total, 1,179 of the kids had a diagnosis of ASD. That's 0.3% or about 1 in 350, much lower than more recent estimates, but these more recent studies used very different methods. Just over 60% of these also had ID, which corresponds well to previous estimates.

There were about 4,500 cases of ID without ASD in the sample, a rate of just over 1%; the great majority of these (90%) had mild-to-moderate ID. They excluded an additional 800 kids with ID associated with a "known biomedical condition" like Down's Syndrome.

So what did they find? Well, a whole bunch, and it's all interesting. Bullet point time.

• Between 1984 to 1999, rates of ID without ASD fell and rates of ASD rose, although there was a curious sudden fall in the rates of ASD without ID just before the end of the study. In 1984, "mild-moderate ID" without autism was by far the most common diagnosis, with 10 times the rate of anything else. By 1999, it was exactly level with ASD+ID, and ASD without ID was close behind. Here's the graph; note the logarithmic scale:
  

• Boys had a much higher rate of autism than girls, especially when it came to autism without ID. This has been known for a long time.
  
• Second- and third- born children had a higher rate of ID, and a lower rate of ASD, compared to firstborns.
  
• Older mothers had children with more autism - both autism with and without ID, but the trend was bigger for autism with ID. But they had less ID. For fathers, the trend was the same and the effect was even bigger. Older parents are more likely to have autistic children but less likely to have kids with ID.
  

• Richer parents had a strongly reduced liklihood of ID. Rates of ASD with ID were completely flat, but rates of ASD without ID were raised in the richer groups, though it was not linear (the middle groups were highest. - and effect was small.)
  

To summarize: the risk factors for autism were in most cases the exact opposite of those for ID. The more “advantaged” parental traits like being richer, and being older, were associated with more autism, but less ID. And as time went on, diagnosed rates of ASD rose while rates of ID fell (though only slightly for severe ID).

Why is this? The simplest explanation would be that there are many children out there for whom it's not easy to determine whether they have ASD or ID. Which diagnosis any such child gets would then depend on cultural and sociological factors - broadly speaking, whether clinicians are willing to give (and parents willing to accept) one or the other.

The authors note that autism has become a less stigmatized condition in Australia recently. Nowdays, they say, a diagnosis of ASD may be preferable to a diagnosis of "just" "plain old" ID, in terms of access to financial support amongst other things. However, it is also harder to get a diagnosis of ASD, as it requires you to go through a more extensive and complex series of assessments.

Clearly some parents will be better able to achieve this than others. In other countries, like South Korea, autism is still one of the most stigmatized conditions of childhood, and we'd expect that there, the trend would be reversed.

The authors also note the theory that autism rates are rising because of some kind of environmental toxin causing brain damage, like mercury or vaccinations. However, as they point out, this would probably cause more of all neurological/behavioural disorders, including ID; at the least it wouldn't reduce the rates of any.

These data clearly show that rates of ID fell almost exactly in parallel with rates of ASD rising, in Western Australia over this 15 year period. What will the vaccine-vexed folks over at Age of Autism make of this study, one wonders?

Leonard H, Glasson E, Nassar N, Whitehouse A, Bebbington A, Bourke J, Jacoby P, Dixon G, Malacova E, Bower C, & Stanley F (2011). Autism and intellectual disability are differentially related to sociodemographic background at birth. PloS one, 6 (3) PMID: 21479223

Who Gets Autism?

According to a major new report from Australia, social and family factors associated with autism are associated with a lower risk of intellectual disability - and vice versa. But why?


The paper is from Leonard et al and it's published in PLoS ONE, so it's open access if you want to take a peek. The authors used a database system in the state of Western Australia which allowed them to find out what happened to all of the babies born between 1984 and 1999 who were still alive as of 2005. There were 400,000 of them.

The records included information on children diagnosed with either an autism spectrum disorder (ASD), intellectual disability aka mental retardation (ID), or both. They decided to only look at singleton births i.e. not twins or triplets.

In total, 1,179 of the kids had a diagnosis of ASD. That's 0.3% or about 1 in 350, much lower than more recent estimates, but these more recent studies used very different methods. Just over 60% of these also had ID, which corresponds well to previous estimates.

There were about 4,500 cases of ID without ASD in the sample, a rate of just over 1%; the great majority of these (90%) had mild-to-moderate ID. They excluded an additional 800 kids with ID associated with a "known biomedical condition" like Down's Syndrome.

So what did they find? Well, a whole bunch, and it's all interesting. Bullet point time.

• Between 1984 to 1999, rates of ID without ASD fell and rates of ASD rose, although there was a curious sudden fall in the rates of ASD without ID just before the end of the study. In 1984, "mild-moderate ID" without autism was by far the most common diagnosis, with 10 times the rate of anything else. By 1999, it was exactly level with ASD+ID, and ASD without ID was close behind. Here's the graph; note the logarithmic scale:
  

• Boys had a much higher rate of autism than girls, especially when it came to autism without ID. This has been known for a long time.
  
• Second- and third- born children had a higher rate of ID, and a lower rate of ASD, compared to firstborns.
  
• Older mothers had children with more autism - both autism with and without ID, but the trend was bigger for autism with ID. But they had less ID. For fathers, the trend was the same and the effect was even bigger. Older parents are more likely to have autistic children but less likely to have kids with ID.
  

• Richer parents had a strongly reduced liklihood of ID. Rates of ASD with ID were completely flat, but rates of ASD without ID were raised in the richer groups, though it was not linear (the middle groups were highest. - and effect was small.)
  

To summarize: the risk factors for autism were in most cases the exact opposite of those for ID. The more “advantaged” parental traits like being richer, and being older, were associated with more autism, but less ID. And as time went on, diagnosed rates of ASD rose while rates of ID fell (though only slightly for severe ID).

Why is this? The simplest explanation would be that there are many children out there for whom it's not easy to determine whether they have ASD or ID. Which diagnosis any such child gets would then depend on cultural and sociological factors - broadly speaking, whether clinicians are willing to give (and parents willing to accept) one or the other.

The authors note that autism has become a less stigmatized condition in Australia recently. Nowdays, they say, a diagnosis of ASD may be preferable to a diagnosis of "just" "plain old" ID, in terms of access to financial support amongst other things. However, it is also harder to get a diagnosis of ASD, as it requires you to go through a more extensive and complex series of assessments.

Clearly some parents will be better able to achieve this than others. In other countries, like South Korea, autism is still one of the most stigmatized conditions of childhood, and we'd expect that there, the trend would be reversed.

The authors also note the theory that autism rates are rising because of some kind of environmental toxin causing brain damage, like mercury or vaccinations. However, as they point out, this would probably cause more of all neurological/behavioural disorders, including ID; at the least it wouldn't reduce the rates of any.

These data clearly show that rates of ID fell almost exactly in parallel with rates of ASD rising, in Western Australia over this 15 year period. What will the vaccine-vexed folks over at Age of Autism make of this study, one wonders?

Leonard H, Glasson E, Nassar N, Whitehouse A, Bebbington A, Bourke J, Jacoby P, Dixon G, Malacova E, Bower C, & Stanley F (2011). Autism and intellectual disability are differentially related to sociodemographic background at birth. PloS one, 6 (3) PMID: 21479223

BBC: Something Happened, For Some Reason

According to the BBC, the British recession and spending cuts are making us all depressed.


They found that between 2006 and 2010, prescriptions for SSRI antidepressants rose by 43%. They attribute this to a rise in the rates of depression caused by the financial crisis. OK there are a few caveats, but this is the clear message of an article titled Money woes 'linked to rise in depression'. To get this data they used the Freedom of Information Act.

What they don't do is to provide any of the raw data. So we just have to take their word for it. Maybe someone ought to use the Freedom of Information Act to make them tell us? This is important, because while I'll take the BBC's word about the SSRI rise of 43%, they also say that rates of other antidepressants rose - but they don't say which ones, by how much, or anything else. They don't say how many fell, or stayed flat.

Given which it's impossible to know what to make of this. Here are some alternative explanations:

• This just represents the continuation of the well-known trend, seen in the USA and Europe as well as the UK, for increasing antidepressant use. This is my personal best guess and Ben Goldacre points out that rates rose 36% during the boom years of 2000-2005.
  
• Depression has not got more common, it's just that it's more likely to be treated. This overlaps with the first theory. Support for this comes from the fact that suicide rates haven't risen - at least not by anywhere near 40%.
  
• Mental illness is no more likely to be treated, but it's more likely to be treated with antidepressants, as opposed to other drugs. There was, and is, a move to get people off drugs like benzodiazepines, and onto antidepressants. However I suspect this process is largely complete now.
• Total antidepressant use isn't rising but SSRI use is because doctors increasingly prescribe SSRIs over opposed to other drugs. This was another Ben Goldacre suggestion and it is surely a factor although again, I suspect that this process was largely complete by 2007.
  
• People are more likely to be taking multiple different antidepressants, which would manifest as a rise in prescriptions, even if the total number of users stayed constant. Add-on treatment with mirtazapine and others is becoming more popular.
• People are staying on antidepressants for longer meaning more prescriptions. This might not even mean that they're staying ill for longer, it might just mean that doctors are getting better at convincing people to keep taking them by e.g. prescribing drugs with milder side effects, or by referring people for psychotherapy which could increase use by keeping people "in the system" and taking their medication. This is very likely. I previously blogged about a paper showing that in 1993 to 2005, antidepressant prescriptions rose although rates of depression fell, because of a small rise in the number of people taking them for very long periods.
  
• Mental illness rates are rising, but it's not depression: it's anxiety, or something else. Entirely plausible since we know that many people taking antidepressants, in the USA, have no diagnosable depression and even no diagnosable psychiatric disorder at all.
• People are relying on the NHS to prescribe them drugs, as opposed to private doctors, because they can't afford to go private. Private medicine in the UK is only a small sector so this is unlikely to account for much but it's the kind of thing you need to think about.
• Rates of depression have risen, but it's nothing to do with the economy, it's something else which happened between 2007 and 2010: the Premiership of Gordon Brown? The assassination of Benazir Bhutto? The discovery of a 2,100 year old Japanese melon?
  

Personally, my money's on the melon.

BBC: Something Happened, For Some Reason

According to the BBC, the British recession and spending cuts are making us all depressed.


They found that between 2006 and 2010, prescriptions for SSRI antidepressants rose by 43%. They attribute this to a rise in the rates of depression caused by the financial crisis. OK there are a few caveats, but this is the clear message of an article titled Money woes 'linked to rise in depression'. To get this data they used the Freedom of Information Act.

What they don't do is to provide any of the raw data. So we just have to take their word for it. Maybe someone ought to use the Freedom of Information Act to make them tell us? This is important, because while I'll take the BBC's word about the SSRI rise of 43%, they also say that rates of other antidepressants rose - but they don't say which ones, by how much, or anything else. They don't say how many fell, or stayed flat.

Given which it's impossible to know what to make of this. Here are some alternative explanations:

• This just represents the continuation of the well-known trend, seen in the USA and Europe as well as the UK, for increasing antidepressant use. This is my personal best guess and Ben Goldacre points out that rates rose 36% during the boom years of 2000-2005.
  
• Depression has not got more common, it's just that it's more likely to be treated. This overlaps with the first theory. Support for this comes from the fact that suicide rates haven't risen - at least not by anywhere near 40%.
  
• Mental illness is no more likely to be treated, but it's more likely to be treated with antidepressants, as opposed to other drugs. There was, and is, a move to get people off drugs like benzodiazepines, and onto antidepressants. However I suspect this process is largely complete now.
• Total antidepressant use isn't rising but SSRI use is because doctors increasingly prescribe SSRIs over opposed to other drugs. This was another Ben Goldacre suggestion and it is surely a factor although again, I suspect that this process was largely complete by 2007.
  
• People are more likely to be taking multiple different antidepressants, which would manifest as a rise in prescriptions, even if the total number of users stayed constant. Add-on treatment with mirtazapine and others is becoming more popular.
• People are staying on antidepressants for longer meaning more prescriptions. This might not even mean that they're staying ill for longer, it might just mean that doctors are getting better at convincing people to keep taking them by e.g. prescribing drugs with milder side effects, or by referring people for psychotherapy which could increase use by keeping people "in the system" and taking their medication. This is very likely. I previously blogged about a paper showing that in 1993 to 2005, antidepressant prescriptions rose although rates of depression fell, because of a small rise in the number of people taking them for very long periods.
  
• Mental illness rates are rising, but it's not depression: it's anxiety, or something else. Entirely plausible since we know that many people taking antidepressants, in the USA, have no diagnosable depression and even no diagnosable psychiatric disorder at all.
• People are relying on the NHS to prescribe them drugs, as opposed to private doctors, because they can't afford to go private. Private medicine in the UK is only a small sector so this is unlikely to account for much but it's the kind of thing you need to think about.
• Rates of depression have risen, but it's nothing to do with the economy, it's something else which happened between 2007 and 2010: the Premiership of Gordon Brown? The assassination of Benazir Bhutto? The discovery of a 2,100 year old Japanese melon?
  

Personally, my money's on the melon.

Neurology vs Psychiatry

Neurology and psychiatry are related fields - if for no other reason, because neurological disorders can often manifest as, and get misdiagnosed as, psychiatric ones.

But what's the borderline between neurology and psychiatry? What makes one disease "neurological" and another "mental"? Are some psychiatric disorders more "neurological" than others?

It's a rather philosophical question and you could discuss it for as long as you wanted. Rather than doing that I thought I'd have a look to see which disorders are, at the moment, considered to fall into each category.

To do this I did a quick search the archives of two journals, Neurology which the world's leading journal of... well, guess, and the American Journal of Psychiatry. I looked to see how many papers from the past 20 years had either a Title or an Abstract which referred to various different diseases. You can see the results above. Note that the total number of papers varied, obviously, and I've only plotted the proportion.

Some interesting results. Schizophrenia, which is probably considered "the most neurological" psychiatric disorder, is in fact the least talked about in Neurology. Depression is top amongst the "core" psychiatric ones.

Autism occupies a middle ground, discussed by psychiatrists at 70% and neurologists at 30%. That didn't surprise me, but what did was that ADHD is almost as neurological as autism. Mental retardation is also intermediate, though it's 30:70 in favour of neurology. Whether autism is really less neurological than mental retardation, is a good question.

Then out of the disorders with a known neuropathology, Alzheimer's disease, Huntington's disease and "dementia" (which overlaps with Alzheimer's) are a bit psychiatric while stuff like headache and epilepsy is almost 100% neurological. Why this is, is not entirely clear, since both dementia and epilepsy are caused by neurological damage, and they can both cause "psychiatric" symptoms.

I suspect the difference is that it's just much harder to treat Alzheimer's, Huntington's and dementia. With epilepsy or meningitis, neurologists have a very good chance of controlling the symptoms and few patients will be left with ongoing psychiatric problems. But with the neurodegenerative disorders, neurologists can't really do much, leaving a large pool of people for psychiatrists to study.

Someone once said that neurologists take all of the curable diseases and leave psychiatrists with the ones they can't help. These figures suggest that there may be some truth in this.

Neurology vs Psychiatry

Neurology and psychiatry are related fields - if for no other reason, because neurological disorders can often manifest as, and get misdiagnosed as, psychiatric ones.

But what's the borderline between neurology and psychiatry? What makes one disease "neurological" and another "mental"? Are some psychiatric disorders more "neurological" than others?

It's a rather philosophical question and you could discuss it for as long as you wanted. Rather than doing that I thought I'd have a look to see which disorders are, at the moment, considered to fall into each category.

To do this I did a quick search the archives of two journals, Neurology which the world's leading journal of... well, guess, and the American Journal of Psychiatry. I looked to see how many papers from the past 20 years had either a Title or an Abstract which referred to various different diseases. You can see the results above. Note that the total number of papers varied, obviously, and I've only plotted the proportion.

Some interesting results. Schizophrenia, which is probably considered "the most neurological" psychiatric disorder, is in fact the least talked about in Neurology. Depression is top amongst the "core" psychiatric ones.

Autism occupies a middle ground, discussed by psychiatrists at 70% and neurologists at 30%. That didn't surprise me, but what did was that ADHD is almost as neurological as autism. Mental retardation is also intermediate, though it's 30:70 in favour of neurology. Whether autism is really less neurological than mental retardation, is a good question.

Then out of the disorders with a known neuropathology, Alzheimer's disease, Huntington's disease and "dementia" (which overlaps with Alzheimer's) are a bit psychiatric while stuff like headache and epilepsy is almost 100% neurological. Why this is, is not entirely clear, since both dementia and epilepsy are caused by neurological damage, and they can both cause "psychiatric" symptoms.

I suspect the difference is that it's just much harder to treat Alzheimer's, Huntington's and dementia. With epilepsy or meningitis, neurologists have a very good chance of controlling the symptoms and few patients will be left with ongoing psychiatric problems. But with the neurodegenerative disorders, neurologists can't really do much, leaving a large pool of people for psychiatrists to study.

Someone once said that neurologists take all of the curable diseases and leave psychiatrists with the ones they can't help. These figures suggest that there may be some truth in this.

"1 Boring Old Man" Blog Isn't

Just wanted to let everyone know about a blog called 1 boring old man, which is a very poor name as it isn't boring at all.


I don't know if it's written by an old man or not, one can only assume so, but whoever writes it, it has got a lot of extremely good stuff about psychiatry and psychiatric drugs. Fans of Daniel Carlat's blog or even former readers of the now seemingly defuct Furious Seasons will find it extremely interesting.

It's actually been going since 2005, but for some reason I've only just found out about it (many thanks to regular Neuroskeptic commentator Bernard Carroll).