In Part 1, I discussed a paper by Jerome Wakefield examining the issue of where to draw the line between normal grief and clinical depression.


The line moved in the American Psychiatric Association's DSM diagnostic system when the previous DSM-III edition was replaced by the current DSM-IV. Specifically, the "bereavement exclusion" was made narrower.

The bereavement exclusion says that you shouldn't diagnose depression in someone whose "depressive" symptoms are a result of grief - unless they're particularly severe or prolonged when you should. DSM-IV lowered the bar for "severe" and "prolonged", thus making grief more likely to be classed as depression. Wakefield argued that the change made things worse.

But DSM-V is on its way soon. The draft was put up online in 2010, and it turns out that depression is to have no bereavement exclusion at all. Grief can be diagnosed as depression in exactly the same way as depressive symptoms which come out of the blue.

The draft itself offered just one sentence by way of justification for this. However, big cheese psychiatrist Kenneth S. Kendler recently posted a brief note defending the decision. Wakefield has just published a rather longer paper in response.

Wakefield starts off with a bit of scholarly kung-fu. Kendler says that the precursors to the modern DSM, the 1972 Feighner and 1975 RDC criteria, didn't have a bereavement clause for depression either. But they did - albeit not in the criteria themselves, but in the accompanying how-to manuals; the criteria themselves weren't meant to be self-contained, unlike the DSM. Ouch! And so on.

Kendler's sole substantive argument against the exclusion is that it is "not logically defensible" to exclude depression induced by bereavement, if we don't have a similar provision for depression following other severe loss or traumatic events, like becoming unemployed or being diagnosed with cancer.

Wakefield responds that, yes, he has long made exactly that point, and that in his view we should take the context into account, rather than just looking at the symptoms, in grief and many other cases. However, as he points out, it is better to do this for one class of events (bereavement), than for none at all. He quotes Emerson's famous warning that "A foolish consistency is the hobgoblin of little minds". It's better to be partly right, than consistently wrong.

Personally, I'm sympathetic to Wakefield's argument that the bereavement exclusion should be extended to cover non-bereavement events, but I'm also concerned that this could lead to underdiagnosis if it relied too much on self-report.

The problem is that depression usually feels like it's been caused by something that's happened, but this doesn't mean it was; one of the most insidious features of depression is that it makes things seem much worse than they actually are, so it seems like the depression is an appropriate reaction to real difficulties, when to anyone else, or to yourself looking back on it after recovery, it was completely out of proportion. So it's a tricky one.

Anyway, back to bereavement; Kendler curiously ends up by agreeing that there ought to be a bereavement clause - in practice. He says that just because someone meets criteria for depression does not mean we have to treat them:

...diagnosis in psychiatry as in the rest of medicine provides the possibility but by no means the requirement that treatment be initiated ... a good psychiatrist, on seeing an individual with major depression after bereavement, would start with a diagnostic evaluation.

If the criteria for major depression are met, then he or she would then have the opportunity to assess whether a conservative watch and wait approach is indicated or whether, because of suicidal ideation, major role impairment or a substantial clinical worsening the benefits of treatment outweigh the limitations.

A reader pointed me to this piece:

Boy Without a Cerebellum Baffles Doctors

Argh. This is going to be a bit awkward. So I'll just say at the outset that I have nothing against kids struggling with serious illnesses and I wish them all the best.


The article's about Chase Britton, a boy who apparantly lacks two important parts of the brain: the cerebellum and the pons. Despite this, the article says, Chase is a lovely kid and is determined to be as active as possible.

When he was 1 year old, doctors did an MRI, expecting to find he had a mild case of cerebral palsy. Instead, they discovered he was completely missing his cerebellum -- the part of the brain that controls motor skills, balance and emotions.

"That's when the doctor called and didn't know what to say to us," Britton said in a telephone interview. "No one had ever seen it before. And then we'd go to the neurologists and they'd say, 'That's impossible.' 'He has the MRI of a vegetable,' one of the doctors said to us."

Chase is not a vegetable, leaving doctors bewildered and experts rethinking what they thought they knew about the human brain.

Nature has a disturbing article from their Asian correspondent David Cyranoski: Thought experiment. It's open access.

In brief: a number of top Japanese psychiatrists have started offering a neuroimaging method called NIRS to their patients as a diagnostic tool. They claim that NIRS shows the neural signatures of different mental illnesses.

The technology was approved by the Japanese authorities in April 2009, and since then it's been used on at least 300 patients, who pay $160 for the privilege. However, it's not clear that it works.

To put it mildly.

• Matsuo et al (2000) n=9/10 elderly depressed/controls
• Suto et al (2004) n=10/13/16 depressed/schizophrenia/controls
• Kameyama et al (2006) n=17/11/17 bipolar/depression/controls
• Nishimura et al (2007) n=5/33 panic disorder/controls
• Takizawa et al (2008) n=55/70 schizophrenia/controls
• Uehara et al (2007) n=11/11 eating disorder/controls
• Suda et al (2010) n=27/27 eating disorder/controls

...when Fukuda calculates his success rates, NIRS results that match the clinical diagnosis are considered a success. If the results don’t match, Fukuda says he will ask the patient and patient’s family “repeatedly” whether they might have missed something — for example, whether a depressed patient whose NIRS examination suggests schizophrenia might have forgotten to mention that he was experiencing hallucinations.

Should a dodgy paper on antidepressants be retracted? And what's scientific retraction for, anyway?


Read all about it in a new article in the BMJ: Rules of Retraction. It's about the efforts of two academics, Jon Jureidini and Leemon McHenry. Their mission - so far unsuccesful - is to get this 2001 paper retracted: Efficacy of paroxetine in the treatment of adolescent major depression.

Jureidini is a member of Healthy Skepticism, a fantastic Australian organization that Neuroskeptic readers have encountered before. They've got lots of detail on the ill-fated "Study 329", including internal drug company documents, here.

So what's the story? Study 329 was a placebo-controlled trial of the SSRI paroxetine (Paxil, Seroxat) in 275 depressed adolescents. The paper concluded: that "Paroxetine is generally well tolerated and effective for major depression in adolescents." It was published in the Journal of the American Academy of Child and Adolescent Psychiatry (JAACAP).

There's two issues here: whether paroxetine worked, and whether it was safe. On safety, the paper concluded that "Paroxetine was generally well tolerated...and most adverse effects were not serious." Technically true, but only because there were so many mild side effects.

In fact, 11 patients on paroxetine reported serious adverse events, including suicidal ideation or behaviour, and 7 were hospitalized. Just 2 patients in the placebo group had such events. Yet we are reassured that "Of the 11, only headache (1 patient) was considered by the treating investigator to be related to paroxetine treatment."

The drug company argue that it didn't become clear that paroxetine caused suicidal ideation in adolescents until after the paper was published. In 2002, British authorities reviewed the evidence and said that paroxetine should not be given in this age group.

That's as maybe; the fact remains that in this paper there was a strongly raised risk. However, in fairness, all that data was there in the paper, for readers to draw their own conclusions from. The paper downplays it, but the numbers are there.

Study 329’s results showed that paroxetine was no more effective than the placebo according to measurements of eight outcomes specified by Martin Keller, professor of psychiatry at Brown University, when he first drew up the trial.

Two of these were primary outcomes...the drug also showed no significant effect for the initial six secondary outcome measures. [it] only produced a positive result when four new secondary outcome measures, which were introduced following the initial data analysis, were used... Fifteen other new secondary outcome measures failed to throw up positive results.

Of the depression-related variables, paroxetine separated statistically from placebo at endpoint among four of the parameters: response (i.e., primary outcome measure)...

Note: This book quotes me approvingly, so this is not quite a disinterested review.

Cordelia Fine's Delusions of Gender is an engaging, entertaining and powerfully argued reply to the many authors - who range from the scientifically respectable to the less so - who've recently claimed to have shown biological sex differences in brain, mind and behaviour.

Fine makes a strong case that the sex differences we see, in everything from behaviour to school achievements in mathematics, could be caused by the society in which we live, rather than by biology. Modern culture, she says, while obviously less sexist than in the past, still contains deeply entrenched assumptions about how boys and girls ought to behave, what they ought to do and what they're good at, and these - consciously or unconsciously - shape the way we are.

Some of the Fine's targets are obviously bonkers, like Vicky Tuck, but for me, the most interesting chapters were those dealing in detail with experiments which have been held up as the strongest examples of sex differences, such as the Cambridge study claiming that newborn boys and girls differ in how much they prefer looking at faces as opposed to mechanical mobiles.

But Delusions is not, in Steven Pinker's phrase, saying we ought to return to "Blank Slatism", and it doesn't try to convince you that every single sex difference definately is purely cultural. It's more modest, and hence, much more believable: simply a reminder that the debate is still an open one.

Fine makes a convincing case (well, it convinced me) that the various scientific findings, mostly from the past 10 years, that seem to prove biological differences, are not, on the whole, very strong, and that even if we do accept their validity, they don't rule out a role for culture as well.

This latter point is, I think, especially important. Take, for example, the fact that in every country on record, men roughly between the ages of 16-30 are responsible for the vast majority of violent crimes. This surely reflects biology somehow; whether it's the fact that young men are physically the strongest people, or whether it's more psychological, is by the by.

But this doesn't mean that young men are always violent. In some countries, like Japan, violent crime is extremely rare; in other countries, it's tens of times more common; and during wars or other periods of disorder, it becomes the norm. Young men are always, relatively speaking, the most violent but the absolute rate of violence varies hugely, and that has nothing to do with gender. It's not that violent places have more men than peaceful ones.

Gender, in other words, doesn't explain violence in any useful way - even though there surely are gender differences. The same goes for everything else: men and women may well have, for biological reasons, certain tendencies or advantages, but that doesn't automatically explain (and it doesn't justify) all of the sex differences we see today; it's only ever a partial explanation, with culture being the other part.

Can fMRI scans be used to detect deception?

It would be nice, although a little scary, if they could. And there have been several reports of succesful trials under laboratory conditions. However, a new paper in Neuroimage reveals an easy way of tricking the technology: Lying In The Scanner.

The authors used a variant of the "guilty knowledge test" which was originally developed for use with EEG. Essentially, you show the subject a series of pictures or other stimui, one of which is somehow special; maybe it's a picture of the murder weapon or something else which a guilty person would recognise, but the innocent would not.

You then try to work out whether the subject's brain responds differently to the special target stimulus as opposed to all the other irrelevant ones. In this study, the stimuli were dates, and for the "guilty" volunteers, the "murder weapon" was their own birthday, a date which obviously has a lot of significance for them. For the "innocent" people, all the dates were random.

What happened? The scans were extremely good at telling the "guilty" from the "innocent" people - it managed a 100% accuracy with no false positive or false negatives. The image above shows the activation associated with the target stimulus (birthdays) over and above the control stimuli. In two seperate groups of volunteers, the blobs were extremely similar. So the technique does work in principle, which is nice.

But the countermeasures fooled it entirely, reducing accuracy to well below random chance. And the countermeasures were very simple: before the scan, subjects were taught to associate an action, a tiny movement of one of their fingers or toes, with some of the "irrelevant" dates. This, of course, made these dates personally relevant, just like the really relevant stimuli, so there was no difference between them, making the "guilty" appear "innocent".

Maybe it'll be possible in the future to tell the difference between brain responses to really significant stimuli as opposed to artifical ones, or at least, to work out whether or not someone is using this trick. Presumably, if there's a neural signiture for guilty knowledge, there's also one for trying to game the system. But as it stands, this is yet more evidence that lie detection using fMRI is by no means ready for use in the real world just yet...

Ganis G, Rosenfeld JP, Meixner J, Kievit RA, & Schendan HE (2010). Lying in the scanner: Covert countermeasures disrupt deception detection by functional magnetic resonance imaging. NeuroImage PMID: 21111834

According to the BBC (and many others)...

Libido problems 'brain not mind'

Scans appear to show differences in brain functioning in women with persistently low sex drives, claim researchers.

The US scientists behind the study suggest it provides solid evidence that the problem can have a physical origin.

Reboxetine is an antidepressant. Except it's not, because it doesn't treat depression.

This is the conclusion of a much-publicized article just out in the BMJ: Reboxetine for acute treatment of major depression: systematic review and meta-analysis of published and unpublished placebo and SSRI controlled trials.

Reboxetine was introduced to some fanfare, because its mechanism of action is unique - it's a selective norepinephrine reuptake inhibitor (NRI), which has no effect on serotonin, unlike Prozac and other newer antidepressants. Several older tricyclic antidepressants were NRIs, but they weren't selective because they also blocked a shed-load of receptors.

So in theory reboxetine treats depression while avoiding the side effects of other drugs, but last year, Cipriani et al in a headline-grabbing meta-analysis concluded that in fact it's the exact opposite: reboxetine was the least effective new antidepressant, and was also one of the worst in terms of side effects. Oh dear.

And that was only based on the published data. It turns out that Pfizer, the manufacturers of reboxetine, had chosen to not publish the results of most of their clinical trials of the drug, because the data showed that it was crap.

The new BMJ paper includes these unpublished results - it took an inordinate amount of time and pressure to make Pfizer agree to share them, but they eventually did - and we learn that reboxetine is:

• no more effective than a placebo at treating depression.
• less effective than SSRIs, which incidentally are better than placebo in this dataset (a bit).
• worse tolerated than most SSRIs, and much worse tolerated than placebo.
  

The first direct evidence of a genetic link to attention-deficit hyperactivity disorder has been found, a study says.

Only 57 out of the 366 children with ADHD had the genetic variant supposed to be a cause of the illness. That would suggest that other factors are the main cause in the vast majority of cases. Genes hardly explain at all why some kids have ADHD and not others.

the findings allow us to refute the hypothesis that ADHD is purely a social construct, which has important clinical and social implications for affected children and their families.

There's a paradox at the heart of modern psychiatry, according to an important new paper by Dr Charles E. Dean, Psychopharmacology: A house divided.

It's a long and slightly rambling article, but Dean's central point is pretty simple. The medical/biological model of psychiatry assumes that there are such things as psychiatric diseases. Something biological goes wrong, presumably in the brain, and this causes certain symptoms. Different pathologies cause different symptoms - in other words, there is specificity in the relationship between brain dysfunction and mental illness.

Psychiatric diagnosis rests on this assumption. If and only if we can use a given patient's symptoms to infer what kind of underlying illness they have (schizophrenia, bipolar disorder, depression), diagnosis makes sense. This is why we have DSM-IV which consists of a long list of disorders, and the symptoms they cause. Soon we'll have DSM-V.

The medical model has been criticized and defended at great length, but Dean doesn't do either. He simply notes that modern psychiatry has in practice mostly abandoned the medical model, and the irony is, it's done this because of medicines.

If there are distinct psychiatric disorders, there ought to be drugs that treat them specifically. So if depression is a brain disease, say, and schizophrenia is another, there ought to be drugs that only work on depression, and have no effect on schizophrenia (or even make it worse.) And vice versa.

But, increasingly, psychiatric drugs are being prescribed for multiple different disorders. Antidepressants are used in depression, but also all kinds of anxiety disorders (panic, social anxiety, general anxiety), obsessive-compulsive disorder, PTSD, and more. Antipsychotics are also used in mania and hypomania, in kids with behaviour problems, and increasingly in depression, leading some to complain that the term "antipsychotics" is misleading. And so on.

So, Dean argues, in clinical practice, psychiatrists don't respect the medical model - yet that model is their theoretical justification for using psychiatric drugs in the first place.

He looks in detail at one particularly curious case: the use of atypical antipsychotics in depression. Atypicals, like quetiapine (Seroquel) and olanzapine (Zyprexa), were originally developed to treat schizophrenia and other psychotic states. They are reasonably effective, though most of them are no more so than older "typical" antipsychotics.

Recently, atypicals have become very popular for other indications, most of all mood disorders: mania and depression. Their use in mania is perhaps not so surprising, because severe mania has much in common with psychosis. Their use in depression, however, throws up many paradoxes (above and beyond how one drug could treat both mania and its exact opposite, depression.)

Antipsychotics block dopamine D2 receptors. Psychosis is generally considered to be a disorder of "too much dopamine", so that makes sense. The dopamine hypothesis of psychosis and antipsychotic action is 50 years old, and still the best explanation going.

But depression is widely considered to involve too little dopamine, and there is lots of evidence that almost all antidepressants (indirectly) increase dopamine release. Wouldn't that mean that antidepressants could cause psychosis (they don't?). And why, Dean asks, would atypicals, that block dopamine, help treat depression?

Maybe it's because they also act on other systems? On top of being D2 antagonists, atypicals are also serotonin 5HT2A/C receptor blockers. Long-term use of antidepressants reduces 5HT2 levels, and some antidepressants are also 5HT2 antagonists, so this fits. However, it creates a paradox for the many people who believe that 5HT2 antagonism is important for the antipsychotic effect of atypicals as well - if that were true, antidepressants should be antipsychotics as well (they're not.) And so on.

There may be perfectly sensible answers. Maybe atypicals treat depression by some mechanism that we don't understand yet, a mechanism which is not inconsistent with their also treating psychosis. The point is that there are many such questions standing in need of answers, yet psychopharmacologists almost never address them. Dean concludes:

it seems increasingly obvious that clinicians are actually operating from a dimensional paradigm, and not from the classic paradigm based on specificity of disease or drug... the disjunction between those paradigms and our approach to treatment needs to be recognized and investigated... Bench scientists need to be more familiar with current clinical studies, and stop using outmoded clinical research as a basis for drawing conclusions about the relevance of neurochemical processes to drug efficacy. Bench and clinical scientists need to fully address the question of whether the molecular/cellular/anatomical findings, even if interesting and novel, have anything to do with clinical outcome.

The dust is starting to settle after the Hauser-gate scandal which rocked psychology a couple of weeks back.

Harvard Professor Marc Hauser has been investigated by a faculty committee and the verdict was released on the 20th August: Hauser was "found solely responsible... for eight instances of scientific misconduct." He's taking a year's "leave", his future uncertain.

Unfortunately, there has been no official news on what exactly the misconduct was, and how much of Hauser's work is suspect. According to Harvard, only three publications were affected: a 2002 paper in Cognition, which has been retracted; a 2007 paper which has been "corrected" (see below), and another 2007 Science paper, which is still under discussion.

But what happened? Cognition editor Gerry Altmann writes that he was given access to some of the Harvard internal investigation. He concludes that Hauser simply invented some of the crucial data in the retracted 2002 paper.

Essentially, some monkeys were supposed to have been tested on two conditions, X and Y, and their responses were videotaped. The difference in the monkey's behaviour between the two conditions was the scientifically interesting outcome.

In fact, the videos of the experiment showed them being tested only on condition X. There was no video evidence that condition Y was even tested. The "data" from condition Y, and by extension the differences, were, apparently, simply made up.

If this is true, it is, in Altmann's words, "the worst form of academic misconduct." As he says, it's not quite a smoking gun: maybe tapes of Y did exist, but they got lost somehow. However, this seems implausible. If so, Hauser would presumably have told Harvard so in his defence. Yet they found him guilty - and Hauser retracted the paper.

So it seems that either Hauser never tested the monkeys on condition B at all, and just made up the data, or he did test them, saw that they weren't behaving the "right" way, deleted the videos... and just made up the data. Either way it's fraud.

Was this a one-off? The Cognition paper is the only one that's been retracted. But another 2007 paper was "replicated", with Hauser & a colleague recently writing:

In the original [2007] study by Hauser et al., we reported videotaped experiments on action perception with free ranging rhesus macaques living on the island of Cayo Santiago, Puerto Rico. It has been discovered that the video records and field notes collected by the researcher who performed the experiments (D. Glynn) are incomplete for two of the conditions.

Glynn was not an author on the only paper which has actually been retracted [the Cognition 2002 paper that Altmann refers to]... according to his resume, he didn't arrive in Hauser's lab until 2005.

Following on from fMRI in 1000 words, which seemed to go down well, here's the next step: how to analyze the data.

There are many software packages available for fMRI analysis, such as FSL, SPM, AFNI, and BrainVoyager. The following principles, however, apply to most. The first step is pre-processing, which involves:

• Motion Correction aka Realignment – during the course of the experiment subjects often move their heads slightly; during realignment, all of the volumes are automatically adjusted to eliminate motion.
• Smoothing – all MRI signals contain some degree of random noise. During smoothing, the image of the whole brain is blurred. This tends to smooth out random fluctuations. The degree of smoothing is given by the “Full Width to Half Maximum” (FWHM) of the smoother. Between 5 and 8 mm is most common.
• Spatial Normalization aka Warping – Everyone’s brain has a unique shape and size. In order to compare activations between two or more people, you need to eliminate these differences. Each subject’s brain is warped so that it fits with a standard template (the Montreal Neurological Institute or MNI template is most popular.)

An unassuming little paper in the latest Journal of Affective Disorders may change everything in the debate over antidepressants: Not as golden as standards should be: Interpretation of the Hamilton Rating Scale for Depression.

Bear with me and I'll explain. It's less boring than it looks, trust me.

The Hamilton Scale (HAMD) is the most common system for rating the severity of depression. If you're only a bit down you get a low score, if you're extremely ill you get a high one. The maximum score's 52 but in practice it's extremely rare for someone to score more than 30.

First published in 1960, the HAMD is used in most depression research including almost all clinical trials of antidepressants. It's come under much criticism recently, but that's not the point here. The authors of the new paper, Kristen & von Wolff, simply asked: what does a given HAMD score mean in terms of severity?

It turns out that people have proposed no less than 5 different systems for interpreting HAMD scores. Do they all agree? Ha. Guess.

The pretty colors are mine. Just a glance shows a lot of variability, but the obvious outlier is the second one. That's the American Psychiatric Association (APA)'s official 2000 recommendations. Their interpretations of a given point on the scale tend to be worse than everyone else's.

This is most apparent at the top end. The APA use the terminology "Very Severe", which doesn't even appear on other scales. Much of what they class as "Very Severe" (23-26), two other scales class as "Moderate" depression! Amusingly, British authorities NICE seem to have been so unimpressed with this that they simply copied the APA's scale and toned everything down a notch for their 2009 criteria.

antidepressants reach... conventional criteria for clinical significance only for patients at the upper end of the very severely depressed category.

antidepressants reach... conventional criteria for clinical significance only for patients with major depression, of moderate-to-severe severity.