Social Science and Language, Again

On Sunday I asked, Why Don't Social Scientists Want To Be Read? I accused much of social science of using unnecessarily complex jargon.

This post prompted many excellent comments - including responses on other blogs e.g. Andy Balmer and Graham Davey.

The most common argument against my post was, in essence: Every science has a specialized, technical vocabulary. You wouldn't criticize a neuroscience abstract for being inaccessible to a layperson, so it's unfair to expect that from sociology.

This is a good and convincing point. Yet I think that, on closer inspection, it relies on some rather major assumptions.

The natural sciences do have a 'specialized' vocabulary, but only because they deal with things that are of special interest. What is 'special' or 'technical' about the word forebrain (to borrow an example from Andy Balmer) is merely that only neuroscientists are interested in the object, forebrains. It's not part of the everyday English language, because it's not part of everyday life.

There's nothing inherently 'academic' about forebrain, in other words. Plenty of similar terms like 'forearm' and 'foreskin' are part of everyday English, not because they're somehow less precise or less formal, but just because they crop up more often.

Everyday English is inadequate for natural science because scientists study things outside everyday experience. But the major object of the social sciences is everyday human life. Social scientists are interested in things that everyone is interested in - why people think, feel and behave the way they do.

So if the social sciences have need of a technical vocabulary, in the same way as the natural sciences, this would imply is that our everyday language is fundamentally inadequate to understanding the everyday world - in other words, that it is just inadequate, period.

Everyday English has developed to allow people to talk to one another. And the main thing people talk about, is one another, i.e. about society. Like any other branch of science, the social sciences need a rich vocabulary to describe all of the things they study: but don't they already have one - English?

Maybe not. It may be that ordinary English can't express the truth about society. But if you take that seriously, that's a pretty radical claim, akin to saying that the great majority of people are in the dark about how the world works. It's much more radical than saying that chemistry or neuroscience needs special words.

To be clear, I'm not making the populist argument that "Social science is all rubbish - the average man in the street knows better than these eggheads!" The average person is wrong about all kinds of important things, but I suspect that they're sometimes in the right ballpark, as it were, and that their errors are not a matter of lacking the proper words.

Why Don't Social Scientists Want To Be Read?

Here's the abstract of a paper just out called In pursuit of leanness: The management of appearance, affect and masculinities within a men's weight loss forum.

In a somatic society which promotes visible, idealized forms of embodiment, men are increasingly being interpellated [sic] as image-conscious body-subjects. Some research suggests that men negotiate appearance issues in complex and varied ways, partly because image concerns are conventionally feminized. However, little research has considered how overweight men construct body projects in the context of weight loss, or how men talk to each other about weight management efforts. Since sources of information and support for overweight men are now provided online, including dedicated weight loss discussion forums, our analysis focuses on one such forum, linked to a popular male-targeted magazine. We conducted a thematic analysis of selected extracts from seven threads on the forum. Our analysis suggests a widespread focus on appearance, as well as the use of emotion categories when describing difficult bodily experiences. Invariably, however, such talk was carefully constructed and constrained by hegemonic masculinities founded on discipline, work-orientation, pragmatism and self-reliance. The findings are discussed in relation to magazine masculinities and aesthetics, as well as literature on male embodiment.

Phew. Now I think it's fair to say that this is a typical example of what might be called the "social sciences style" of writing. That's why I've chosen to blog about it; nothing I'm going to say is a criticism of this paper as such, but rather of the whole genre.

Why do social scientists write like this?

This paper is about a really interesting topic - the mixed messages men get about what it means to be "a man" or "manly" in today's society. Very topical, not at all 'niche', and important in lots of ways. So why is it written in a way which makes it impenetrable to all except specialists?

I don't think it has to be that way. I've rewritten this abstract, and I've tried to say the same thing without the jargon:

Modern men face a dilemma: society tells them that they ought to have an attractive body, but they are also warned that being concerned about beauty and body image is a feminine trait. However, little research has considered how overweight men think and talk about weight loss. Online weight loss forums offer a window onto such issues, so we analyzed seven threads from one such site, linked to a popular men's magazine. We found that while men took part in (often emotional) discussions of their own appearances and bodies, they always framed such talk strictly within conventionally "masculine" terms such as discipline, work-orientation, pragmatism and self-reliance. We discuss this, in the context of men's magazines treatment of masculinity and male beauty, and relate this to previous work.

Whether I've succeeded, I'll leave others to judge, but I think I have and there's no trick to it - I just read the original, tried to understand it, and wrote down my thoughts.

I'm not saying that the original abstract was "badly written". I suspect it was quite expertly written but that the purpose of writing it was less to communicate ideas clearly, than to satisfy some set of criteria of what 'serious social science' should be like.

If I'm right - isn't that a shame? The ideas here deserve a wide audience, so why aren't they aimed at one?

Bennett E, and Gough B (2012). In pursuit of leanness : The management of appearance, affect and masculinities within a men's weight loss forum. Health (London, England : 1997) PMID: 22815334

Catching Fraud: Simonsohn Says

Everyone's been talking about psychologist Uri Simonsohn and his role in the downfall of two scientific fraudsters.

When the story first broke, the methods Simonsohn used that allowed him to spot the dodgy data were mysterious - which only added to the buzz. The paper revealing the approach is now up online and it's a must-read. It's not often a statistics paper offers the train-wrecky schadenfreude of watching two fraudsters' careers come to a well-deserved end.

What's rather disturbing about the article, however, is that it doesn't really contain much that's new, in principle. Simonsohn used statistics to spot data in published papers that was, in effect, 'too good to be true'. He then followed up seemingly dodgy cases with some more stats, using simulations of what real data ought to look like, to verify that it was in fact made up. A simple idea in retrospect but one that's never been tried before. I don't think there's a single "Simonsohn method", rather, the paper uses multiple techniques, each one tailored to the particular data in question.

But it shouldn't have come to this. Someone else ought to have spotted that the data looked dodgy.

Take this table from one of Simonsohn's conquests, a soon-to-be-retracted paper by Lawrence J Sanna et al:

We now know that the data from Studies 2,3 and 4 were all made up. Each study compared 3 conditions, and what makes these data dodgy is that the standard deviations of the 3 sets of results for each study were almost identical. The chances of that happening are very low and it suggests that someone has (clumsily) made the data up.

I'm going to say that these data are obviously suspicious, at least to anyone who has worked with real data. Maybe you'll say that hindsight is 20/20, but Simonsohn didn't need hindsight and the stats he used were nothing remarkable. I'm not saying that to belittle his achievements, he deserves plenty of credit. But other people deserve blame.

Namely, whoever peer reviewed this paper should have spotted that these data looked unusual - and they should not have needed any special statistical tools to do so.

Simonsohn calls for journals to require that the raw data be made available for all published work, on the grounds that. That's a great idea - and not just because it would help catch bad science: it would facilitate proper research and teaching no end. But Simonsohn didn't need the raw data to detect these cases of fraud - he only checked the raw results to confirm the suspicions based on the published data.

Checking that the data are valid is the job of peer reviewers, and they dropped the ball. Instead Simonsohn had to conduct his own private crusade against fraud... a bit like Batman. Batman is awesome, but the point about Batman is that he's only needed because the police can't or won't cope on their own. He's not a superhero, he's just a guy with the will.

Peer reviewers are the police of science, but all too often, they're asleep on the job. Not just in psychology. Retraction Watch provides plenty of examples of published results in biology that were faked, often in comically crude fashion, and should have been obvious to anyone paying attention.

Peer reviewers are usually anonymous. I wonder if a policy of retrospectively naming and shaming the reviewers when a paper turns out to have been fraudulent, might help motivate them...?

Search Trends Reveal Sexual Seasons

Americans are most likely to search for sex online during the early summer and the winter, according to research just published in the Archives of Sexual Behavior.

The authors looked at the Google Trends for a selection of naughty words and phrases, and this revealed a pretty marked 6 month cycle for searches originating from the USA, with two yearly peaks in the search volumes. There was no such pattern for some non-sexual control words.

Here's the graph for pornography searches, with an idealized 6 month cycle also shown for comparison. The data were similar for two other categories of sexual words: prostitution and dating websites. Overall the results seem solid, although in studies like this, I always worry a bit about how the included search terms were chosen; there is a potential for cherry picking (no pun intended).

Those words in full:

The pornography keyword set included 10 keywords used in previous research that individuals tend to use when searching for pornography (‘‘porn,’’ ‘‘boobs,’’ ‘‘xvideos,’’ ‘‘tits,’’‘‘sex,’’ ‘‘pussy,’’ ‘‘hentai,’’ ‘‘xxx,’’ ‘‘nude,’’ and ‘‘milf’’).

In a similar manner, the prostitution keyword set included five keywords that individuals might use to engage in sexual activities that are often illegal (‘‘call girl,’’ ‘‘escort,’’ ‘‘massage parlor,’’ ‘‘brothel,’’ and ‘‘prostitute’’).

Finally, the mate-seeking keyword set included the names of 10 popular websites that individuals often use to find potential mates (‘‘eHarmony,’’ ‘‘Yahoo Personals’’, ‘‘AOL Personals,’’ ‘‘Plenty of Fish,’’ ‘‘Zoosk,’’ ‘‘Singles Net’’ ‘‘Friend Finder,’’ ‘‘JDate,’’ ‘‘Match.com,’’ and ‘‘Okcupid’’).

Heh. I'm not sure I should be quoting those, it might attract some weird traffic to the blog. But oh well.

The authors note that a six-month sexual cycle has been reported before. It crops up in everything from abortion rates, to condom sales, and diagnosis of sexually transmitted infections. But why?

One possibility is that it's purely a social construction driven by the fact that in Western cultures, Christmas and summer are the main holiday seasons; but it could reflect a more primitive biological cycle. Google ought to offer a way to find that out, actually; find a country with a similar climate to the USA, but with different major holidays. China, maybe?

Markey PM, and Markey CN (2012). Seasonal Variation in Internet Keyword Searches: A Proxy Assessment of Sex Mating Behaviors. Archives of sexual behavior PMID: 22810997

A Case Study in Voodoo Genetics

A new review of published studies looking at the relationship between a gene and brain structure offers a sobering lesson in how science goes wrong.

Dutch neuroscientists Marc Molendijk and colleagues took all of the studies that compared a particular variant, BDNF val66met, and the volume of the human hippocampus. It's a long story, but there are various biological reasons that these two things might be correlated.

It turns out that the first published reports found large genetic effects, but that ever since then, the size of the effects has dropped, with the latest studies finding no effects at all -

A cumulative meta-analysis confirms that as more studies on BDNF val66met have appeared, the overall effect estimate has steadily declined -

Finally, the authors found signs of publication bias: there were three small, imprecise studies that reported very large effects of the gene, but no such studies finding no effect (or a reverse effect). You'd expect that small and noisy studies would have a lot of random variation so they wouldn't all be positive even if there was a true effect; that all of the published ones were positive, suggests that null findings are out there, unreported.

Overall, this suggests that val66met probably isn't associated with hippocampus volume after all, and that the early studies showing that it was, were misleading. There's no reason to think that the early studies were wrong as such - they may have accurately reported an effect in the small sample of people they looked at, but it was only a chance finding.

I know a lot of neuroscientists who are now fairly skeptical of this whole genre of candidate gene studies; there was much excitement 5 or 10 years ago, but in retrospect, most of these studies were too small, and the publication process meant that it was the random chance findings that were most likely to get published.

However, we need to avoid any sense of complacency. Until we fix the scientific process, the same thing will happen again.

Molendijk ML, Bus BA, Spinhoven P, Kaimatzoglou A, Voshaar RC, Penninx BW, van Ijzendoorn MH, and Elzinga BM (2012). A systematic review and meta-analysis on the association between BDNF val(66) met and hippocampal volume American journal of medical genetics B Neuropsychiatric genetics PMID: 22815222

Brain Scanning... Or Vein Scanning?

Many fMRI studies of brain activity could be biased by the effect of large blood vessels, according to an interesting new report: Origins of intersubject variability of BOLD and arterial spin labeling fMRI.

fMRI measures BOLD, the Blood Oxygenation Level Dependent response. As the name says, BOLD is when a bit of the brain becomes more active, it uses more oxygen, and the oxygenation level of the blood in the area drops - although it then increases to compensate, and it's the increase that most fMRI picks up.

There's a catch though: blood flows. Specifically, it flows from arteries, into tissues - the brain, in this case - and then into veins. Blood leaving the brain tends to end up in the larger veins and, being large, these exert a large effect on BOLD - even though they're some distance from the true site of neural activation.

So, the worry is that BOLD blobs may be shifted towards the nearest large vein, reducing the accuracy of fMRI. It's a well-recognized issue, but it's not clear just how serious it is... or what we can do about it.

Enter Canadian researchers Ismael Gaxiola-Valdez and Bradley Goodyear. By comparing BOLD to the alternative method of ASL - They show that the large vessel effect does happen to BOLD signals, shifting the activation blobs nearer to the surface of the brain (where veins are.) However, the effect is more pronounced when the blobs represent absolute BOLD changes. When blobs represent the z score - which they usually do - the difference is smaller.

That's somewhat reassuring... but here's the bad news. Some peoples' brains show larger BOLD changes than others. Gaxiola-Valdez and Goodyear show that these individual differences in BOLD magnitude are probably driven by large vessel effects because as the pic at the top shows, BOLD was most variable (between people) at the surface, i.e. near the veins, while ASL, less subject to the vein bias, was most variable deep in the brain, as you'd expect.

Worse, the size of people's BOLD and ASL signal changes (to the same task) were not correlated (or only weakly) when the BOLD study used short task blocks. This calls into question short-block or event-related fMRI experiments that measure differences between people or between groups: the differences might be in the veins, not the brain. With longer task blocks, however, there was a good correlation with the ASL.

Overall, it's an important paper and a reminder that, although neuroscientists sometimes treat the brain as separate from the rest of the body, it's not.

Gaxiola-Valdez I, and Goodyear BG (2012). Origins of intersubject variability of blood oxygenation level dependent and arterial spin labeling fMRI: implications for quantification of brain activity. Magnetic resonance imaging PMID: 22795932

Whole Brain Teaching...?

Oh dear. The Kansas City Star asks: Teachers learn ways to keep students' attention, but are brain claims valid?

Probably not. Unless you're buying a brain scanner or a plush brain, product 'brain claims' are generally just marketing patter. But let's see.

When Chris Biffle called out the word "Class!" Wednesday morning at Walsh University, 450 teachers and administrators yelled back, "Yes!"

"Class class?" he said. "Yes! Yes!" they replied.

"Classity classity," he said.
"Yessity yessity," they chanted back.

Biffle, one of the co-founders of Southern California-based Whole Brain Teaching LLC, is leading a two-day conference about his method. He calls the technique "Class-Yes." Whole Brain Teaching's website says "Class Yes" activates the prefrontal cortex of the brain and "readies students for instruction"...

Whole Brain Teaching reminds me of Brain Gym, a notorious bit of British neuro-nonsense from a few years ago. According to the WBT research page, they have over 50,000 registered teachers and 2 million views of their videos. This also informs us that:

Class-Yes: Our primary attention-getter activates the prefrontal cortex, often called the CEO of the brain... Little if any learning can take place if the prefrontal cortex is not engaged.

while even "mirror neurons" have a role to play:

Mirror: Many brain scientists believe that we learn by mirroring the gestures and activities of others. They have identified mirror neurons scattered throughout the brain that are activated by mimicking the behavior we observe. Our own experience in WBT classroom indicates that when a class mirrors our gestures and, when appropriate, repeats our words, a powerful learning bond is created between students and teachers.

There are lots of problems here, but here's the most fundamental: the theory behind the system seems to be that activating particular parts of students' brains, through a special task, will help them to use that part of their brain when it comes to the actual lesson a few minutes later. But I know of no evidence that bits of the brain "warm up" like that; if anything they're more likely to "wear out" through lack of energy and nutrients although I don't think that's likely either.

If such warm-ups did work, your best bet for activating your primary visual cortex, for example, would be to stare at a rapidly-changing pattern of random colors for a few minutes. That wouldn't improve your vision. It would just give you a headache.

In fact, why not just activate your entire noggin, pharmacologically? Just grab some pentylenetetrazol - a drug that blocks inhibitory signals between brain cells. Snort a few lines of that and if you survive the resulting seizure, go and learn something and see if you're really good at it.

I'm not saying Whole Brain Teaching is useless, I'm not saying anything about the method itself, but the "brain" claims are misleading. Many of the things they recommend are teaching aids and classroom exercises, and no doubt those are helpful. Plus, psychological factors like teacher motivation, student engagement, and a positive atmosphere are vital in learning, and it doesn't matter if you achieve them through neurosciencey gimmicks, they're still going to help... well, except in terms of educating people to spot neurosciencey gimmicks.

But that's teaching. It's nothing to do with the brain.

BOLD Blobs Brighten Baby Brains

Babies born prematurely show the same kind of brain activation seen in adults: but it's a lot slower. That's according to an interesting study using fMRI scanning.

The authors, Tomoki Arichi and colleagues of London, measured brain activation in response to mild sensory stimulation (touching the right hand) in three groups: adults, "preterm" infants who were just 38 weeks old since conception, and "term" infants who'd been conceived about 42 weeks before scanning, although many of these had also been born prematurely.

Activation was observed in the same part of the brain in all three groups, showing that the BOLD blood oxygenation response measured by fMRI is present even early in life. However, in the pre-term infants, it was delayed: while in adults and typical infants it peaked about 6 seconds after stimulation, in the preterms it was more like 12 seconds. The size of the response was much smaller than in adults in both cases, though.

The authors say that the brain itself is probably not the source of the difference. Rather, they argue that in preterm infants, the blood supply to the brain takes longer to respond to the need for more oxygen.

Arichi T, Fagiolo G, Varela M, Melendez-Calderon A, Allievi A, Merchant N, Tusor N, Counsell SJ, Burdet E, Beckmann CF, and Edwards AD (2012). Development of BOLD signal Hemodynamic Responses in the Human Brain. NeuroImage PMID: 22776460

The Coming Age of Fetal Genomics

It's 2020. A young woman and her partner have just found out that she's pregnant with her first child. and they're going to be parents.

They're overjoyed, of course. But they're also worried. They've seen the adverts warning parents-to-be about the risk of de novo mutations - genetic mistakes that occur inside sperm or egg cells, and affect the child. These mutations, the ads say, are much more common than previously believed and they can cause all kinds of problems: intellectual disabilities, autism, infertility, mental illness, heart malformations - pretty much anything.

The scariest part? Because these are new mutations, out of the blue, they can affect any family. A clear family history is no protection. They don't discriminate by race or lifestyle. It's just the luck of the draw - except that older parents are at much higher risk, especially older fathers. In the case of our couple, she's 28 and he's 32. Perfectly normal for this day and age - but very old in biological terms. Humans evolved to be grandparents by 32, not parents. "The stakes couldn't be higher. Why leave it to chance?"

So they don't. Instead, they buy a $100 test kit, they each provide a small blood sample and send it off to one of the companies offering fetal genome testing. At the testing lab, they can separate out the mother's DNA from that of the fetus, both of which are present in the mother's blood. By comparing the fetal genome to the mother's and father's, it's easy to spot de novo mutations. If a certain gene doesn't match either the mother or the father's sequence, it's mutated.

A few days later the results are back. There are several mismatches detected. Most are benign - they're not predicted to have any biological effects. But there's one, a deletion of a few thousand bases in a gene involved in brain development. This deletion is predicted to raise the risk of epilepsy and autism from 1% to 10% apiece.

The parents now have a decision to make. The mutation is a one off, it's not inherited. If they conceive again... roll the dice again... and it'll be gone. Do they terminate?

Like the adverts say, "Some people disagree with this, but we say there's only one person who really matters: your baby."

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This is likely to become possible in the next few years.

A paper just published in Nature reports on the Non-invasive prenatal measurement of the fetal genome. The technique relies on the fact that the blood of a pregnant woman contains DNA: hers, obviously, but also that of the unborn child. This cell-free DNA can be extracted and genotyped.

This has been possible for a few years, but until now, only fairly crude genetic information could be detected. An extra chromosome, such as in Down syndrome, is pretty easy to spot. This technique is already used to diagnose Down's syndrome and a few other disorders prenatally.

But those diseases are just the low-hanging fruit at the tip of the iceberg, if you see what I mean. To gather the kind of detailed genomic information that could diagnose thousands of disorders is harder: the fetal and maternal genomes are mixed up, and the challenge is to tease them apart. But according to the Stanford geneticists behind the Nature paper, and other teams, it's now possible as early as the first trimester.

What makes the new method so revolutionary is that it is, as the title of the paper says, non-invasive. It's already possible to sequence a fetal genome, but it takes a surgical procedure involving inserting a needle into the womb, and a degree of risk. It's not something you can just sit down and do - but blood samples are. So cell-free DNA will make fetal genomics a personal choice, a commercial product.

The resolution's still not 100%, but inevitably, it will become cheaper, faster and more accurate as technology advances. This year we're expected to see the cost of reading a whole human genome falling below $1000. Fetal genomes will be more expensive, but not enormously so. In 5 or 10 years, it's likely to be affordable.

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What will happen? I think there'll be demand for such services. Most parents won't do it, but enough people will that it will be a major issue. Just look at countries where boys are more valued than girls: a lot of sex-selective abortion happens. Today, it's limited to gender, because it's easier to determine a fetus's sex than its genome. In 5 or 10 years, they'll both be easy.

With demand will come companies to supply these services and, inevitably, advertizing. I doubt these adverts will be on TV, because there will be opposition to the whole idea and boycotts of broadcasters who run them. But we'll be getting spam emails about it. People will worry even over the harmless mutations: a variant won't need to be really associated with a disease, just believed to be, to make people panic.

Socially, it's likely to be divisive. The anti-abortion types will obviously not approve. But it will drive a wedge between those who support abortion but oppose "discriminatory" abortion against the disabled, and those who support the right to terminations 'for any reason, or none'.

Politically, there will be pressure to regulate this, but legally, it'll be tricky. I can't see how you'd prove that any given abortion is motivated by genetic concerns, so unless you ban abortion outright, that won't work. Banning fetal (or all) genomics except under medical supervision might be possible, but people could always go (or send a few drops of blood) abroad to get around that.

I'm not sure where I'll stand on this, but it looks very likely that we'll each have to make a decision in the coming years.

Fan HC, Gu W, Wang J, Blumenfeld YJ, El-Sayed YY, and Quake SR (2012). Non-invasive prenatal measurement of the fetal genome. Nature PMID: 22763444

Why Blogs Fail

I can think of several new neuroscience blogs that started out with some really nice content, but then they disappeared after a few weeks or months. I'm sure the same must be true of other genres. This is a shame.

Thinking back over the early days of Neuroskeptic, my advice to new bloggers is: it gets better. The early days of any blog are psychologically tough because almost inevitably, your first posts are not going to get the recognition they deserve.

That's because people tend to really pour their hearts into early posts - these are the ones that express thoughts you've been mulling over for ages and are finally writing about - and then inevitably, hardly anyone reads them, because it's a new blog and no-one even knows it's there yet. Certainly that was my experience.

Luckily, it doesn't stay that way. Your first posts will flop, at least in relation to your own expectations, but remember that a) it's nothing personal and b) no-one except you cares. Only you can see your traffic stats and whatever, but even if everyone knew them, they wouldn't mind. You need to push on through that stage and once you do, you won't care about it either.

To get past the first stage, you need to "sell" your blog. I think a lot of new bloggers forget this, or think it somehow won't apply to them, which sets them up for disappointment. Of course, good content is essential - no matter how hard you try, you can't sell crap. But great writing alone is not enough. No, not even yours.

Promotion is part of blogging, but once you get into the right mindset, you'll realize that it's not a chore so much as a natural extension of writing. You write something, and then you go and find people who'll be interested in it, and who might have interesting comments about it, and try and get them involved. Or you get involved in conversations about the topics you're interested in.

Sell, don't beg. Outright asking more established people for links, retweets etc. rarely works and it looks bad. Get people interested in it. If that's a chore, then it means you're not really interested in your own stuff, in which case that's a problem.

If you've done this for, say, a year, then I'd say you've given blogging a good shot and you can make an informed decision as to whether or not it's for you. But if you quit after just a couple of months because "I tried blogging and it didn't work out" or "I had a blog but no-one read it" then I'd say you're probably making a mistake. You haven't experienced all of blogging, only the start of it, which is the toughest and least rewarding part. It gets better.

When Data Filtering Introduces Bias

Oh no. Another worrying methods problem for neuroscience, this time for electrophysiologists: Systematic biases in early ERP and ERF components as a result of high-pass filtering.

The event-related potential (ERP) and event-related field (ERF) techniques provide valuable insights into the time course of processes in the brain. Researchers commonly filter the data to increase the signal-to-noise ratio. However, filtering may distort the data, leading to false results. Using our own EEG data, we show that acausal high-pass filtering can generate a systematic bias easily leading to misinterpretations of neural activity... among 185 relevant ERP/ERF publications, 80 used cutoffs above 0.1Hz. As a consequence, part of the ERP/ERF literature may need to be re-analyzed.

The problem in brief: many researchers use a high-pass filter on their electroencephalography (EEG) and magnetoencephalography (MEG) recordings of brain electrical activity. A high-pass filter removes low frequency (i.e. slow) changes from the signal. These slow fluctuations are often considered to be mere "noise".

The problem is that these filters have side effects: as well as 'cleaning up' the data, they can also distort it. There are two main kinds of filter: causal filters are well-known to mutate the signal. Acausal high-pass filters avoid these dramatic artefacts -

But David Acunzo and colleagues point out that acausal filters can actually be more dangerous, because they still distort the data, just in more subtle ways that are harder to spot. In particular, acausal filters can alter the signal at time points before the true signal begins. See the pic above.

That's not necessarily a problem in all cases, but it's certainly bad news for researchers interested in measuring exactly when neural responses happen.

The authors highlight an area of neuroscience where this problem could be misleading researchers. The very earliest brain responses to visual stimuli, about 90 milliseconds after the stimulus onset, is called the "C1" response. Classically, it was thought that the size of the C1 wave was purely a 'bottom-up' phenomenon, determined only by the brightness etc. of the stimulus. But recently, studies have reported 'top down' modulation of C1 by attention, emotional state, etc.

Acunzo et al point out that many of these studies used strong acausal filtering and that what might be happening is that attention actually causes late changes to the visual response, but that due to filtering artefacts, these late changes appear in the data sooner than they really happen. They advise that only weak (low threshold) high-pass filters should be used, and that interesting findings in filtered signals need to be checked against the raw data.

Acunzo DJ, Mackenzie G, and van Rossum MC (2012). Systematic biases in early ERP and ERF components as a result of high-pass filtering. Journal of neuroscience methods PMID: 22743800

Can You Learn To Be Synaesthetic?

A neat study from Dutch psychologists Olympia Colizoli, Jaap Murre and Romke Rouw claims that it's possible to train people to have something a bit like synaesthesia - which they call Pseudo-Synesthesia through Reading Books with Colored Letters.

Synaesthesia generally comes out of the blue - some people just have it while others don't. Those who do experience it typically report that they've always had it. But could it be learned?

Colizoli et al recruited 17 non-synaesthetes and got them to read books specially printed such that 4 common letters, "a", "e", "s" and "t", were always printed in a certain colour: red, orange, green or blue. The idea was that constant exposure to the coloured letters might trigger grapheme-color synaesthesia, which is a relatively common 'naturally occurring' form of the condition.
 
On average each volunteer read 100,000 words of the polychromatic prose. They also got a special browser plug-in to colour internet text in the same way, however, most people didn't use it.

What happened? The subjects experienced a colour-letter Stroop interference effect consistent with the idea that they'd learned particular colour-letter associations, although on another task there was no effect. But what was it actually like, subjectively? The size of the Stroop effect was correlated with self-reported synaesthetic experience on the question "I am experiencing color when thinking about certain letters".

However, the average answer to this question was only 2.5 on a scale from 1 to 5, which doesn't seem very high, and of course there was no control group, so this is hard to interpret. They don't seem to have quizzed people about the subjective experience in much detail, which is a bit of a shame. Six months later, participants could barely remember the letter-color pairs better than guessing.

So to be honest, it's all a bit inconclusive, but it's a cool idea.

Although you might expect the coloured text arrangement to be annoying, many participants said that they quite enjoyed it once they got used to it. Only 2 out of the 17 gave up before finishing a book, while several volunteered to read additional books. So if you want to try and give yourself synaesthesia, it could be doable.

Colizoli O, Murre JM, and Rouw R (2012). Pseudo-Synesthesia through Reading Books with Colored Letters. PloS one, 7 (6) PMID: 22761905

The Racist Brain?

Is the human brain... a racist?

There are some worrying indications that it could be. After all, the cerebrum is largely composed of so-called "white" matter, and the only black area is a little 'ghetto' at the bottom called, shockingly, the substantia nigra...!

Seriously though. There's a paper just out in Nature Neuroscience from Kubota et al that looks at The Neuroscience Of Race. It's a fine review as far as it goes, but to me at least, it really shows up the limits of contemporary neuroscience.

We are told that

A network of interacting brain regions is important in the unintentional, implicit expression of racial attitudes and its control. On the basis of the overlap in the neural circuitry of race, emotion and decision-making, we speculate as to how this emerging research might inform how we recognize and respond to variations in race and its influence on unintended race-based attitudes and decisions.

So there have been studies investigating which bits of American's brains activate in response to looking at photos of black people vs. white people. It emerges that "a network of interacting brain regions" light up. But so what?

Sure, the brain reacts differently to seeing people of different races. Of course it does - it reacts differently to everything, so long as we can perceive a difference; that's how we perceive a difference. And of course race, a deeply emotive issue in American politics and culture, activates 'emotional' parts of the brain - that's how it's emotive.

The included studies all scanned Americans and (presumably) mostly college students. Now most American college students are not active racists, and indeed I'd imagine that their emotional brains are more likely to be worrying self-referentially about racism than about the actual race of the stimuli. No-one seems to have scanned card-carrying members of the KKK. Furthermore, "race" in these studies almost always means "blackness". What about Latinos, Asians?

So what have we learned?

I don't think we've learned much about race. "Race" after all is a confused mixture of emotions, attitudes and beliefs. These differ greatly from person to person, and even the same individual may experience conflicting feelings in different contexts. Kubota et al note this and say that it may explain the mixed findings (black faces activate the amygdala more than white in some studies, not in others) but I'd have said that in this case, only inconsistent results are credible.

What does it tell us about the brain? I'd say not much. The authors weave a neat little narrative - in response to seeing black faces, the amygdala and other emotional areas activate as a negative emotional response; the ACC then detects this racist response and sees that it's unacceptable, and the DLPFC then suppresses it like a parent hurriedly interrupting a young child who's making a faux pas.

But all the elements of this story - the automatic, emotional amygdala, the supervisory DLPFC - are borrowed from other neuroscience studies so at best the race literature confirms these theories but it doesn't even really do that, because there are many other possible interpretations.

I'd say that we need to know much more in terms of the 'basic' neuroscience of emotion, attitudes and beliefs because we can tackle the hornet's nest of race in the brain.

Kubota JT, Banaji MR, and Phelps EA (2012). The neuroscience of race. Nature neuroscience, 15 (7), 940-8 PMID: 22735516