Obesity: Are We Food Obsessed?

According to a Professor Greg Whyte, writing in the Independent, when it comes to obesity, we've got an unhealthy obsession with diet. There is -

an incessant diatribe of diet propaganda purporting to possess the panacea for health... [but] the focus on diet linked to the volume and make-up of calories we consume has overshadowed the importance of the critical half of the energy balance equation: physical activity.

Clearly weight is, to a first approximation, a matter of calories in (diet) vs. calories out (physical activity). For any given diet, whether you lose or gain weight is determined by how much exercise you do, and vice versa. There's no such thing as "overeating" as such, there's just eating out of proportion to your level of exercise.

But have we forgotten that? Do we talk about the diet side of the equation more? I ran a few searches on PubMed and Google for "obesity" + various other terms to try and find out and it looks like Whyte is right.

See the graph above.

There does seem to be an imbalance, with "food" and "diet" being much more popular than "exercise" and "physical activity", both in terms of the scientific literature (PubMed), and more generally (Google). This is just a quick analysis of course, but it does suggest that when it comes to weight and obesity, we are more interested in calories in, than calories out.

I wonder why?

WAFFLE: Why Most Books Are Too Long

I have a theory about modern books.

There's a certain kind of book, let's call it the "TITLE: How This Subtitle Summarizes My Big Idea" genre.

I don't think I need to name names.

Now, I read a lot of these, and I've come to the conclusion that most of these books shouldn't books at all. That's not to say they're bad - the big idea may be brilliant, but I don't care how big your idea is, you do not need 100-200 pages to explain one idea.

They tend to contain a couple of core chapters with the good stuff and maybe 4 or 5 chapters of what can best be called waffle. Anecdotes, backstory, additional illustrations, etc. Like a waffle this may be perfectly pleasant - but it's not very nutritious.

Here's why I think this is - publishers (we are told) increasingly want books with a single big idea that can be summed up in a sentence. Partly because they sell, and partly because publishers are overstretched and just don't have time themselves to spend hours thinking through a complex argument to find out if it's any good.

But the problem is that, for whatever historical and business reasons, books are meant to be a certain length, say 100 pages bare minimum. No-one prints 50 page books and few people would buy one, except children etc.

So there's a gap in the profile of the length of non-fiction writing. There are all kinds of shortish pieces - from the briefest news reports and op-eds up to long feature articles and New York Review of Books type articles. That covers all the way from 1 to up to, say, 10,000 words.

But then there's nothing until you reach the short book at (say) 35,000 words, after which, it's plain sailing again.

Think about it - have you ever read a 20,000 word piece of non-fiction? I don't think I have. It's too long for a periodical but too short to be a book. (Academic papers are an exception; I'm thinking of general interest pieces).

Yet it seems to me that a great many of today's books could have been that length, without weakening the argument or dumbing down in any way. And, if so, then they should be, because a fundamental rule of good writing is to keep things as concise as possible. The problem is that while that would make them better as pieces of writing, it would make them unmarketable as books, or anything else; there's practically no market for 20,000 good words and true.

Except... now we have ebooks.

So you could see this post as an argument in praise of ebooks, not just as a new technology but as a whole new form of writing falling somewhere between the "article" and the "book". Which is ironic because I don't even have a Kindle yet. Of course I'm not saying that all books are too long. I like books. Many are the right length, some I wish were longer; but just because an idea could be made into a book, doesn't mean it should be.

Edit: I hadn't read this when I wrote this post but it seems the industry are way ahead of me -

Yesterday, Amazon began selling its Kindle Singles online. Singles are e-books between 5,000 and 30,000 words long. According to the press release, these e-books are meant to “allow a single killer idea — well researched, well argued and well illustrated — to be expressed at its natural length.”

The Real Story On That "Antidepressant Surge"

Remember last week's story about how depression rates are soaring in Britain? It was all triggered by "new data" about an increase in antidepressant prescriptions.

At the time I was skeptical, not least because the data wasn't actually new, but I've done a bit more digging and it turns out the media coverage was even more misleading than I thought.

Here's some pretty graphs from the NHS Information Centre. I reiterate that all of these are freely available and have been for ages. Here's the one for antidepressants:

They've been rising strongly! In total prescription rates are about 60% higher now compared to in 2006. Oh dear.

What the papers didn't tell you is that pretty much every other class of drug has also increased over that period, by even more in some cases. Here's ADHD drugs, and dementia pills, which have increased by about 75% and 100% respectively:

There have also been steady increases in anticonvulsants and a 40% increase in meds for Parkinson's disease. All of the graphs are here.

So this suggests that there's been a general increase in prescriptions for brain drugs. But in fact it's even wider than that because if we look at the same data for cardiovascular system drugs, we find the same picture for most (although not all) kinds of these medications.

And for painkillers, we find over 50% increases in prescriptions of the stronger opioid drugs, a 20% increase in migraine drugs etc etc. I swear I'm not just copying and pasting the same graph.

Now clearly, all of these increased prescriptions don't mean that there are simultaneous explosions in rates of dementia, heart disease, pain, migraine, Parkinson's and ADHD, all in the past 5 years. We would have noticed if that were the case.

What's happened, clearly, is that doctors are just writing more prescriptions nowadays.

So it's misleading to say that there's been a spike in antidepressant prescriptions. Yes it's technically true but it ignores the context. The truth is that we seem to be experiencing a cultural shift in our relationship to medications - perhaps evidence of the creeping medicalization of life (although there are more prosaic explanations that need to be ruled out before we conclude that; this could be a bureaucratic change in the way prescriptions are counted.)

However, "Escalating Depression Crisis - Antidepressant Use Soars" is a better headline than "Possible Medicalization Gradually Continues For Sixth Year In Row".

The truth, sadly, has an inherent disadvantage in the battle for news coverage. If we find the truth boring, it's easy for someone to come along and make up something attention grabbing. But the only easy way to make the truth more interesting is to make it, well, less true.

Britain - the Prozac Nation? Not So Fast...

Oh no! The stress of the recession has turned us into a nation of antidepressant addicts, according to every single British newspaper this morning.

The media coverage has been predictable with lots of scary, context-free statistics, and boilerplate quotes from the usual suspects. No doubt tomorrow we'll see a selection of moralistic op-eds about this.

But not one of the many nigh-identical articles provided a link to the original data, or even a useful description of where one might find it. After contacting one of the NHS organizations named as the source, I managed to track the numbers down.

It turns out that the key figures have been publicly available since April 2011, so I'm not sure why this story appeared in British "news"papers at all. Also, it would have been easy for journalists to link to the source, if they respected the intelligence of their readers enough to do that. I just did it and it wasn't terribly hard to click "Add Link".

On that note, I actually read a bizarre article today criticizing British journalists for providing too many links to their source data... if only.

Anyway, the data. Ben Goldacre has already written an excellent piece on this (in fact, he wrote it back in April 2011, curiously enough...see above), but here's some more detail.

First off, the data are all about antidepressants, not depression. A crucial distinction, there, because nowadays, antidepressants are widely used for all kinds of other things. Everything from other psychiatric disorders like anxiety and OCD, to non-psychiatric stuff like back and joint pain, premature ejaculation, and menopausal hot flushes.

We can't tell how much of the antidepressant use was for depression. But there are clues suggesting that a lot of it wasn't. It turns out that the second most popular antidepressant (after citalopram) was the very old drug amitriptyline, with nearly 9 million prescriptions per year - or 20% of the total.

Nowadays amitriptyline is rarely used for depression, because newer, less toxic alternatives are available. However it is used, in low doses, to treat chronic pain. So I suspect that pain accounts for a large % of amitriptyline use. That would also explain why the cost to the NHS per prescription of amitryptiline was by far the lowest of all antidepressants: low doses are cheap.

How about the increase over time?

The newspapers are correct that antidepressant use rose from 33.9 million prescriptions in the year 2007/8, to 43 million in 2010/2011. That's a 28% rise over 3 years. However, if we go 3 years further back to the equivalent 2004/5 Prescription Cost Analysis, we find that antidepressant prescriptions were 28.9 million. So they rose 17% in the 3 years before 2007/8, long before the recession was on the horizon.

The recent 28% rise, in other words, is unlikely to be related to the recession, at least not entirely.

We also know(1,2) that the number of antidepressant prescriptions per person has been rising over the past several years in the UK. So the increase in prescriptions might not even mean more antidepressant users - it might just mean that the same number of users are using more each. (And that could mean anything, including that bureaucracies are saving money by prescribing for shorter periods).

One study found that there was no increase in the number of people taking antidepressants for depression from 1993 to 2005, with all of the rise in prescriptions over that period being a product of more prescriptions per person.

Another study did find a true rise in users from 1995 to 2007, albeit lower than the raw figures would suggest, but those figures were limited to a particular part of Scotland and it wasn't just about depression - it included all other uses of these drugs as well.

Overall, it's just impossible to know, from these data, whether there's been a true increase in antidepressant use for depression in recent years. The most we can say is that there might have been one, and if so it might have something to do with the economy.

Potential Personal Genomics

A while ago I wrote about how new findings in genetics could herald a new kind of "eugenics", based not around selective breeding to ensure that "bad" genes aren't passed on, but rather based on using fetal genetic testing to choose which variants enter the gene pool in the first place.

I said-

In the near future, we might be able to routinely sequence the genome of any unborn child shortly after conception

But I didn't realize that this may be really very near indeed. Two recent reports have shown that it's possible to sequence fetal DNA from a maternal blood sample. In one case it was used to diagnose a 35 week fetus with a genetic deletion on chromosome 12 seemingly associated with autism, developmental delay and shortness.

In this case it was inherited from the father (which is why they decided to test for it), but this approach could equally be used to screen for the de novo mutations that account for much disease, as I discussed in the last post.

This is big. Currently, the main way to get fetal DNA is through amniocentesis, i.e. inserting a needle into the womb. It's a substantial and not entirely safe medical procedure. A blood sample would be an order of magnitude cheaper and safer, but most of all it would be something you could do at home.

No longer would you need to go to a hospital and discuss everything with a doctor. You could take some blood, send it off anonymously to a sequencing company, and get the results in an email. It would take it out of the hands of professionals and open up a space for individual choice.

The cost of whole-genome sequencing has been falling exponentially and many think it will fall below the $1000 mark within a few years. Combine that with fetal DNA testing and we might see moderately well-off parents able to sequence fetal DNA within the next decade.


When this happens I think the personal genomics industry will suddenly become extremely "hot". At the moment you can sequence your own DNA for a few thousand $ if you want. The results may be interesting but they're of little obvious use. Whatever your genes are, you're stuck with them.

But as soon as we're talking about potential human genomes, it'll kick things up a notch. Media interest and political controversy is sure to follow. Personally I think it'll the debate will begin in earnest when we start seeing selective abortions on the basis of genes for "normal" variants rather than "disease" genes.

It's one thing to not want a child with blindness, or a high risk of leukaemia. But as a society I don't think we're ready for not wanting a child because they're predicted to be a B student rather than an A student, or brunette rather than blonde. At some point soon, though, we'll have to decide what we think about that.

Peters D, Chu T, Yatsenko SA, Hendrix N, Hogge WA, Surti U, Bunce K, Dunkel M, Shaw P & Rajkovic A (2011). Noninvasive prenatal diagnosis of a fetal microdeletion syndrome. The New England journal of medicine, 365 (19), 1847-8 PMID: 22070496

Srebniak M, Boter M, Oudesluijs G, Joosten M, Govaerts L, Van Opstal D, & Galjaard RJ (2011). Application of SNP array for rapid prenatal diagnosis: implementation, genetic counselling and diagnostic flow. European journal of human genetics : EJHG, 19 (12), 1230-7 PMID: 21694736

One in Four Revisited

In a recent Telegraph article, professional contrarian Brendan O'Neill argues against the idea that one in four people experience mental illness - and indeed against the idea that one in four people are bullied, abused or whatever else:

Can it really be true that a quarter of Brits are bullied or beaten up at home or are mentally ill, or is this simply a case of social campaigners exaggerating how bad life is in order that they can continue to make headlines, make an impact, and get funding? I reckon it's the latter. Next time you see the "one in four" figure, be very sceptical – it's probably Dickensian-style doom-mongering disguised as social research, where the aim is to convince us, against the evidence of our own eyes and ears, that loads of the people we encounter everyday are basket cases in need of rescue.

I say "argues against", but he doesn't actually provide any arguments. He just links to the claims and says they're silly.

As Neuroskeptic readers know, I am myself skeptical of the idea that one in four people are mentally ill, but I'm skeptical of it because I've looked at the evidence and it doesn't support that figure. Actually, if you take the available evidence at face value, it says that the true figure for the lifetime prevalence is much higher than one in four. I don't think those figures are very useful however because of various methodological issues.

So in my view we just don't know how many people are mentally ill, largely because we don't have any clear definition of what "mentally ill" means. But that doesn't mean we can just assume that it can't possibly be one in four just because "our own eyes and ears" tell us that most people are not "basket cases".

Much mental illness goes undiagnosed and unnoticed, and I'd imagine also that Brendan O'Neill and the kind of people who read him don't tend to "encounter everyday" people from groups such as the unemployed, the elderly and so forth, in whom the rates are higher.

But even beyond that, it's a silly argument because of selection bias. If you as a healthy person encounter someone everyday, chances are they're not severely ill - mentally or physically - because if they were, they'd be less likely to be around in places for you to encounter. Unless you're a doctor or whatever, you live your life in the world of healthy people.

It's like saying that you don't believe children or the elderly exist, because in your life as a working age adult, you never meet any of them.

Modern War-fMRI : Graphics Cards for Science

Videogames and neuroscience have a rocky relationship.

On the one hand you have Susan Greenfield and her games-hurt-the-brain theory. But she's not representative of neuroscientists as a whole: games have also helped neuroscience, for example, in this study of the neural correlates of "flow" experiences.

Now neuroscientists have another reason to be thankful for games, according to a new paper. It turns out that modern 3D graphics cards - which mostly exist in order to render videogame visuals - can be used to do fMRI data analysis.

According to Sweden's Eklund et al, a graphics card can perform intensive fMRI analysis hundreds of times faster than a regular processor of the equivalent speed, because graphics processors make use of parallel computing optimized for 3D images and that's ultimately what all brain scans are.

They developed a way to run non-parametric statistical analyses of brain imaging data. Proponents say that non-parametric stats have many advantages over conventional parametric ones - and they're certainly becoming increasingly popular. But they involve doing far more calculations. Thousands of times more, in some cases.

It turns out though that armed with 2.5 GHz CPU and three NVidia GTX 480s, and making use of NVidia's graphics programming language, they were able to cut the time to analyse one person's brain with 100,000 permutations, from 24 hrs to just 9 minutes. The whole setup cost $4000, so it's not cheap, but they say it's "a fraction of the price for a PC cluster with equivalent computational performance" i.e. one relying on lots of general purpose processors, rather than graphics cards. Even on GTX480 did the job very well.

Best of all, this gives neuroscientists an excuse to spend their grant money on awesome gaming rigs. Why do I want the latest GForce on my work computer? To do non-parametric data analysis, obviously. Sure, it would also allow me to run Modern Warfare 3 at the highest settings... but that's not why I want it.

Eklund A, Andersson M, Knutsson H (2011). Fast random permutation tests enable objective evaluation of methods for single-subject FMRI analysis. International journal of biomedical imaging, 2011 PMID: 22046176

The Transexual Brain

According to a new paper, the brains of male-to-female transexuals are no more "female" than those of men.

The authors write that "The present data do not support the notion that brains of male-to-female transexuals are feminized" and conclude "The present study does not support the dogma that male-to-female transexuals have atypical sex dimorphism in the brain".

That last sentence has gained quite a bit of coverage, including a quote on the Wikipedia page for "transgender".

But is it so simple?

Structural MRI scans were used to compare the size of various brain structures between three groups of volunteers: heterosexual men, heterosexual women and the transexuals (or "MtF"s as I will call them for short) who were diagnosed with gender dysphoria and were "genetically and phenotypically males".

There were 24 in each group, which makes it a decent sized study. None of the MtFs had started hormone treatment yet, so that wasn't a factor, and none of the women were on hormonal contraception.

The scans showed that the non-transsexual male and female brains differed in various ways. Male brains were larger overall but women had increases in the relative volumes of various areas. Male brains were also more asymmetrical.

The key finding was that on average, the MtF brains were not like the female ones. There were some significant differences from the male brains, but they weren't the same differences that distinguished the females from the males.

This is a fairly crude approach. It looks at the groups on average. It's a finding, but there's more you could with this data. It would be better perhaps to look at the male and female groups, and then try to work out which group each individual MtF is most similar to. You could do that using a Support Vector Machine such as was previously used to detect autism.

This would also have the advantage that it would integrate the results across different brain areas: maybe the important thing is not just the size of individual areas but the relative size of one area to another area.

My real problem though is with the language used to discuss the data. The authors say that the study doesn't support "atypical sex dimorphism in the brain" yet this wasn't a study of "the brain". It was a study of one specific aspect of the brain, namely the volume of different regions. There could be all kinds of chemical and microstructural differences that don't show up on these scans.

There are lots of people with severe epilepsy, for example, whose brains clearly differ in some major way from people without epilepsy, yet they look completely normal on MRI. Only using other methods, like EEG, reveals the difference. Because the difference is chemical, not structural.

I have no idea how, or if, the brains of MtF transsexuals are "feminized" but this study doesn't rule it out. Now I'm sure the authors know all this. And in fact they themselves recently published a paper showing atypical neural responses to smelling "oderous steroids" in transsexual people. But while neuroscientists will know what they meant, I worry that studies like this could be miscontrued by other people (like Wikipedia readers) as a result of overenthusiastic language in papers.

Link: Also blogged at BPS Research Digest.

Savic I, & Arver S (2011). Sex dimorphism of the brain in male-to-female transsexuals. Cerebral cortex (New York, N.Y. : 1991), 21 (11), 2525-33 PMID: 21467211

Susan Greenfield's Dopamine Disaster

It's Susan Greenfield again.

Continuing her campaign warning of the dangers of modern technology in terms of their effects on the vulnerable brains of the young, the British neuroscientist and Baroness has written another article. This is the latest of many. None of them have been in peer reviewed academic journals.

This one's behind the Great Times Paywall so I can't link to it, but it's called Are video games taking away our identities?

The first part of the article is hard to argue against. Either you'll agree with it or you won't. Personally, videogames as Greenfield describes them bear little resemblance to any games that I've played recently. Similarly for her account of the Internet. But maybe this rings true for some:

Screen images do not depend for their impact on seeing one thing in terms of anything else. Their premium lies invariably in their raw sensory content... we are perhaps heading towards a much weaker sense of identity by engaging in a world where we are the passive recipient of senses and where there is no fixed narrative of past and future but an atomised thrill of the moment. One could even suggest that the constant self-centred readout on Twitter belies a more childlike insecurity, an existential crisis.

Greenfield then moves into discussing the brain, and this is where the science comes in. This is her "home turf" - she's Professor of physiology at Oxford. Yet it's a shambles.

There is one alarm bell ringing, which suggests that increasing 2D screen existence may be having undesirable effects: it is the threefold increase over the past decade in prescriptions for drugs for attention deficit hyperactivity disorder.

While this could be due to changes in doctors’ prescribing procedures, or indeed to a greater recognition and medicalisation of attentional problems, a third possibility could indeed be that if the young brain is exposed from the outset to a world of fast action-reaction, of instant new screen images flashing up with each press of a key, then such rapid interchange might lead to a shorter attention span.

The human condition can be basically divided into two alternating modes, first described by Euripedes... the rational “bread force”, characterised by a strong cognitive take on the world — a personalised past, present and future, in turn related to an active prefrontal cortex and lower levels of the brain chemical dopamine; and the “wine force”, more the state of young children or those adults indulging in “letting themselves go”, in situations perhaps involving wine, women and song, where a strong sensory environment demands less reflection, more passive reaction.

...An increase in physiological arousal can be linked to excessive release of dopamine. Could the screen experience be tilting this ancient balance in favour of the more infantile, senses-driven brain state?

Greenfield says that high dopamine and low prefrontal cortex activity is associated with irrationality and a deficit in attention. Video games are causing a flood of dopamine and causing ADHD. That would make sense, if ADHD was caused by too much dopamine, and if drugs for ADHD reduced dopamine release.

The problem is that it's the exact opposite. Drugs for ADHD increase dopamine release and ADHD is widely believed (although it's controversial) to be caused by a dopamine deficit.

Greenfield then says "We know too that dopamine suppresses the activity of neurons in the prefrontal cortex", but this is a serious oversimplification. Dopamine has complex effects on target neurons. It can inhibit firing, but it can also excite it. It all depends on the conditions. Here's what the authors of an influential scientific review said in 2004: "It is agreed by most researchers is that dopamine is a neuromodulator and is clearly not an excitatory or inhibitory neurotransmitter"

Some say that dopamine helps to "tune" the prefrontal by increasing the signal to noise ratio - more signal, less noise. Here's one of the most cited papers about dopamine and the PFC: Cognitive deficit caused by regional depletion of dopamine in prefrontal cortex of rhesus monkey.

Remember that drugs for ADHD like Ritalin, which are sometimes used illicitly by students without that disorder to help them focus and concentrate, cause dopamine release. If Greenfield were right, it would be the exact opposite.

...[other] people characterised by an underactive prefrontal cortex are those with schizophrenia, this time not due to physical damage but rather a chemical imbalance, in particular an excessive amount of the transmitter dopamine. In schizophrenia, like children, the patient is easily distracted, cannot interpret proverbs, is not strong on metaphor but takes the world literally; it is a vibrant world that can implode on, and overwhelm, the fragile firewall of the schizophrenic mindset.

This again is a serious simplification. Actually, you don't need to be a neuroscientist to work that out. Just recall the earlier bit: Greenfield has said that ADHD is caused by too much dopamine leading to an underactive prefrontal cortex. Now she says that schizophrenia is the same. So why are the symptoms of ADHD completely different from schizophrenia?

Why is it, in fact, that Ritalin and similar dopamine releasing drugs help with ADHD, but can make schizophrenia worse?

As a neuroscientist, I can tell you that we don't really know what's going on with dopamine in ADHD or schizophrenia. There's decent evidence that dopamine is involved in schizophrenia, but not in any straightforward sense. Schizophrenia is now believed to be linked to reduced dopamine in the prefrontal cortex, and too much in other areas.

As for ADHD, remember: the leading theory is that it's about too little dopamine. Not too much.

The only disease that we know certainly is associated with too little dopamine is Parkinson's. Contrary to Greenfield's theory, people with Parkinson's often have cognitive and mood problems as well as the better known difficulties with movements. They're not super intelligent, prefrontal-cortex-wielding geniuses.

I appreciate that an opinion piece in the Times is never going to be a rigorously argued scientific paper, but the fact that Greenfield's article contains several claims which are the exact opposite of the truth (or at least of current scientific thinking) calls her credibility into serious question.

Who Should Catch Fraud?

Whose job is it to detect scientific fraud?

You've probably heard of Diederik Stapel, a Dutch psychologist who's just admitted to scientific fraud on a grand scale, with dozens and maybe over 100 papers published based on made-up data. This comes just months after Harvard's Marc Hauser resigned over unspecified data-meddling activities.

What disturbs me is not just that this fraud happened, but the way it was detected. Both Stapel and Hauser were busted by their own junior lab members. Browsing Retraction Watch and reading over other fraud cases reveals that fraud is almost always detected either by 1) By readers of published papers who notice oddities in the data, or 2) by internal whistleblowers, almost always junior lab members

But these are both ad hoc methods. They rely heavily on individual vigilance and courage in speaking out (especially in the latter case). It seems to me that there's no working mechanism for catching fraud. If there were, such acts of individual heroism wouldn't be needed.

So whose job is it to catch fraud? At the moment, it's all the work of private investigators. Where are the police?

First off, is it the job of journals? That seems plausible. Journals publish scientific papers and by doing so they are saying, implicitly, that the papers are good quality. The way this works is meant to be through peer review.
But peer review is failing to catch many cases of fraud. I guess we don't know how many fraudlent papers are caught at the peer review stage and never published. But one would hope that such cases would come to light anyway because reviewers who suspect fraud ought to alert the relevant authorities. I can't think of any recent cases in which fraud investigations were started by peer reviewers, or at least not that we know about.

Maybe it's up to the institution that employs the fraudster? It's the institution that carries out investigations, "convicts" the fraudster and enacts the punishment. Clearly it's in their interests to do this because they don't want to be seen as soft on misconduct. But rarely do they go out and proactively try and catch or prevent fraud. It's not in their interests to do that.

Undetected fraud does no harm to anyone's reputation. On the contrary fraudsters are often the "stars" of their faculty until they get caught. Hauser and Stapel were. Plus, a department that got a reputation for hard-hitting anti-fraud measures might struggle to recruit people, even perfectly innocent ones who just found it annoying.

So what we see is departments who perform (fairly) good investigations into fraud, but only when someone else tells them to.

Maybe it's the funding bodies? They're paying for the research, so they clearly have an interest in making sure their money is well spent. At present, though, they lack the mechanisms to investigate it.

So those are the three possibilites as I see them - journals, institutions and grant awarders. While all of these organizations have policies for investigating and punishing fraud when it comes to light, they rarely (if ever) actually catch it, leaving this hazardous and stressful job to individuals.

Is there a better way?

The Facebook Brain

Facebook friend tally is associated with differences in brain structure

People with lots of Facebook friends have denser grey matter in three regions of the brain, a study suggests

When I heard about this, my heart sank. The Facebook area of the brain? It had all the hallmarks of a piece of media neuro-nonsense: a hook (Facebook!), a simplistic neo-phrenological story (bigger brains are better!)... so I was expecting to discover that the fuss was all about some tiny, statistically questionable study, which wasn't really about what the newspapers said it was, as is so often the case.

So I was very surprised to find that it's actually an extremely good paper.

Kanai et al from London took 125 young Facebookers (mostly students) and correlated their friend count with grey matter density across the brain. They found some correlations:

The numbers seem solid. It was a large study. They used whole-brain correction for multiple comparisons (a=0.05 FWE corrected), controlling for age, gender and overall brain grey matter.

Most importantly, they included a replication sample, something that very few neuroscience papers do. After having done the first 125 people, they got another 40, and looked in the areas where they'd previously found results. They found the same correlation in all three cases - in fact, it was even stronger.

They even made sure to only display the scatterplots from the replication sample, thus avoiding the dreaded voodoo correlations problem that so often plagues such graphs. Note that the correlations are actually with the square root of the number of friends.

As if this wasn't enough, they confirmed a previously reported correlation between amygdala size and social network size, in both of their samples. And to cap it all, they show that Facebook friends are correlated (albeit not hugely) with other measures of number of friends.

So, as unlikely as it sounds, this Facebook finding is stronger than a good 90% of similar papers.

What does it mean that the size of the amygdala, left MTG, right STS and right entorhinal cortex are correlated with your Friend count? Good question. The authors discuss the result in terms of the known functions of these areas, e.g. the entorhinal cortex is involved in learning to associate pairs of stimuli, such as matching names to faces, which might be related to keeping track of your friends... but frankly this is just a post-hoc story.

You could tell an equally convincing tale about almost any part of the brain, if you found a correlation there. And as the authors point out, they didn't find correlations with other "social" areas you might expect like the mirror neuron system.

But that doesn't change the fact that the results of the study seem rock solid. So what's going on? It could be that having lots of friends makes your brain bigger. Or it could be the reverse, that having a certain kind of brain wins you friends, or at least Facebook ones. Or it could be that there's some third factor underlying the correlation, although who knows what that is.

Kanai, R., Bahrami, B., Roylance, R., & Rees, G. (2011). Online social network size is reflected in human brain structure Proceedings of the Royal Society B: Biological Sciences DOI: 10.1098/rspb.2011.1959

You Use Your Partner To Phone And Play Angry Birds. Literally.

WITH lots of weddings expected on Tuesday, people in love across the world are getting ready for their latest fix.

But should we really characterize the intense devotion shown by people in love, as love? A recent experiment that I carried out using neuroimaging technology suggests that love-related terms like “romance” and “soulmates” aren’t scientifically accurate - not compared to a word we use to describe our relationships with our smartphones. That word is “owning an iPhone.”

As a branding consultant, why am I even writing this article for the NYT? Never mind. Earlier this year, I carried out an fMRI experiment to find out whether iPhones were really, truly addictive, no less so than alcohol, cocaine, shopping or video games (sic)... wait, are those last two actually addictive? Whatever, let's just say they are.

In conjunction with the San Diego-based firm MindSign Neuromarketing (kerching! Wait, did I write that, or just think it?), I enlisted eight men and eight women between the ages of 18 and 25. Our 16 subjects were exposed separately to audio and to video of a wife or husband.

In each instance, the results showed activation in both the audio and visual cortices of the subjects’ brains. In other words, when they were exposed to the video, our subjects’ brains didn’t just see their partner, they “heard” them, too. This powerful cross-sensory phenomenon is known as "the brain storing information about people and objects, and retrieving it in response to related stimuli", or "memory" to use the technical term.

But most striking of all was the flurry of activation in the insular cortex of the brain, which has also been associated with seeing an iPhone. The subjects’ brains responded to the sound of their partner as they would respond to the presence or proximity of a top of the range smartphone (with free WiFi in thousands of locations!)

In short, the subjects didn’t demonstrate the classic brain-based signs of addiction when they were shown pictures of their lovers. Instead, they made calls and played Angry Birds on them.

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The silliness of equating insula activation on fMRI with love and using this to argue that we love our iPhones as a recent crap OpEd in the New York Times did, has been excellently covered over at [Citation Needed], Neurocritic and many others. I'm sure you've heard plenty about this story already.

But let's set aside the fact that loads of other things, by no means limited to disgust and drug addiction, are known to involve the insula in fMRI. Let's assume (as the NYT piece did) that the only two things that had ever been shown to activate the insula were seeing an iPhone and seeing someone you love.

This study still wouldn't show that people love their phones. You could equally well turn the whole thing on its head and argue that it shows that we think of people we love as something to make phone calls with. Hey, the brain activity is the same as when you look at an iPhone.

This might strike you as implausible, but given the fMRI data alone, you have no grounds for saying one interpretation is more or less plausible than the other.

There are countless other interpretations, each equally plausible given the imaging data. Maybe the insula is only about love, and the activation to the iPhone is due to conditioned association (you call people you love on it). Maybe it's about objects you see every day, which includes your phone and people you love. Maybe...

The only reason to prefer any particular interpretation would be because you have evidence from outside neuroimaging - from other areas of neuroscience or psychology. So if you discovered that insula lesions cause people to be unable to fall in love (they don't, as far as I know) then you could make a case for the love interpretation. But only then.

Neuroimaging, on its own, can't tell us anything about the brain. It's like a peek under the hood of your car. If you already know how a car works, you can look under the hood and work out what's going on, and what's gone wrong. But only if you have that prior knowledge. Otherwise, it's just a big set of metal pipes.