The Wriggling Brain

What do we mean when we talk about "the brain"?

Easy, right? It's this:

Certainly, this is the image that comes to my mind.

But this is not an image of a brain. It's an image of a dead brain.

In a living brain, all kinds of interesting things are happening. Things we literally can't begin to imagine. Because these are hard to visualize, they can't enter the mental picture.

To picture the living brain as just a yellowy lump is like picturing Wikipedia as a disc. It's accurate as far as it goes, but it misses the whole point. You could download Wikipedia onto a BluRay disc, and then you could describe that disc as "Wikipedia" and you wouldn't be wrong, but Wikipedia is much more than a silver circle.

It doesn't help much that we know that there's more to the living brain than a yellowy lump. Yes, most of us know that the living brain is somehow responsible for thought, feeling, perception, and consciousness.

But we have no idea of how it does so, we don't have any feel for this relationship. We agree with the idea that brain = mind, but that's just an abstract equation. Just as most of us know that e=mc2, but only physicists understand it.

All this leads to philosophical problems. Wittgenstein wrote:

Look at a stone and imagine it having sensations. - One says to oneself: How could one so much as get the idea of ascribing a sensation to a thing? One might as well ascribe it to a number! - And now look at a wriggling fly and at once these difficulties vanish and pain seems able to get a foothold here.

What he meant is that we only feel that we can ascribe pain (or any "internal" mental state or event) to something which is behaving "externally".

Now in most cases, that's fine. Most inanimate objects really don't have mental states. But brains do. The brain, we feel, is inanimate; it's just a yellowy lump. By itself the brain is like Wittgenstein's stone - it seems.

So, we feel, the brain itself can't really have mental states, only walking, talking, behaving people can, like wriggling flies. Except we know on an abstract level that brains do have mental states; so we tie ourselves into philosophical knots about "brains" and "persons", asking whether a person is more or less or the same as a brain, and so on.

The whole problem could be removed, I think, if instead of a yellowy lump, we could picture the living brain in all its active complexity; if we could talk about "the brain", not as an inanimate object, but as the most animate thing in the world.

In the brain there are hundreds of billions of cells, and each one is a hive of movement - not visible to the naked eye or even to a microscope, but the movement of ions and neurotransmitters and ultimately information.

I think many philosophical puzzles would lose their edge if we could somehow get a feel for all that; if we could replace the accurate, but misleading, yellowy lump picture of "the brain" with one that captures the complexity and dynamism of the thing: a city, a hive of insects, a vast machine.

Take Your Placebos, Or Die

People who take their medication as directed are less likely to die - even when that "medication" is just a sugar pill.

This is the surprising finding of a paper just published, Adherence to placebo and mortality in the Beta Blocker Evaluation of Survival Trial (BEST). 

BEST was a clinical trial of beta blockers, drugs used in certain kinds of heart disease. The patients were aged about 60 and they all suffered from heart failure. Everyone was randomly assigned to get a beta blocker or placebo, then followed up for 3 years to see how they did.

Here's the big finding: in the placebo group of 1174 patients, the people who took all of their placebo pills on time (the good adherers), were significantly less likely to die than the patients who missed lots of doses. People who took over 75% as directed were 40% less likely to die than those with less than 75% adherence:

That's pretty interesting. The pills were placebos - they can't have had any benefit. So what's going on?

It gets even better. You might be tempted to write off these results as obvious: "Clearly, people who follow the study instructions are just 'healthy' people in other ways - maybe they take more exercise, eat better, etc. and that's what protects them."

Certainly, that's what I'd have said.

But what's remarkable is that when the authors corrected the statistics for all the confounding variables they measured - including things like age, gender, ethnicity, smoking, body mass index and blood pressure - it barely changed the effect. Some of the factors did correlate with adherence, but not in a way that it could explain the adherence effect on mortality.

This isn't the first study to find this effect. The authors themselves have already reported it, as have other researchers going back decades (many of which also tried, and failed, to explain it through confounding factors.) They say that it's unlikely to be a case of publication bias.

So what we have is a large effect, which cannot be causal, yet which can't be explained by any obvious confounds. Logically then, it must be the result of a confound (or more than one) that aren't obvious.

This is an important lesson. It's common for someone to do a study and find an interesting / scary / controversial correlation between two things. Often one is some kind of lifestyle factor, diet, environmental exposure, or whatever, and the other is some nasty disease. "And it wasn't explained by confounds!", such studies often conclude.

What the placebo adherence effect demonstrates is that there may be confounds no-one has thought of. They might even be impossible to measure. And if these mystery confounds can literally kill you, they can probably cause all kinds of other effects too.

In other words this illustrates the truism that correlation is not causation - not even when you're really sure it is...

Pressman, A., Avins, A., Neuhaus, J., Ackerson, L., and Rudd, P. (2012). Adherence to placebo and mortality in the Beta Blocker Evaluation of Survival Trial (BEST) Contemporary Clinical Trials DOI: 10.1016/j.cct.2011.12.003

The Hidden Face Within

One of these two images contains a hidden picture of a face. Which one?

This was the question faced by participants in a remarkable psychology experiment just published, Measuring Internal Representations from Behavioral and Brain Data.

Five healthy volunteers were presented with a series of random black and white grid patterns. Each grid square was either black or white, and this was randomly determined on each trial.

There was no pattern to the images, they were completely random. But the subjects were told that half of the patterns contained a hidden face, and that their job was to work out which ones did. Each subject saw over 10,000 random images and they took about 1 second to judge each one.


The volunteers "detected" a face in 44% of the images. Somehow, all five of them convinced themselves that they were seeing faces in many of the grids. The authors say that

Upon completion of the experiment we debriefed observers, and all expressed shock that no face was ever presented.

That's strange enough in itself, but here's the really clever bit. The authors compared the patterns which were declared to contain a face, to the ones that were reported as empty. The image below shows the average "face" grid, minus the average "non face" grid, for each individual subject:

As you can see, this reveals...a face! Kind of. The top half shows the raw average; the bottom half shows the statistically significant differences from random noise.

In Subjects 1 and 2, the face is pretty clear, with eyes, a nose and a mouth. For 3 and 4, it's less coherent, but you might be able to see it if you look hard enough. For Subject 5, not really.

What this means is that people (at least, most of them) were not just seeing faces in any noise. They tended to see faces when the random patterns happened to resemble a kind of primitive face, but it was a different face for each person. The authors say that these strange faces correspond to the individual's internal representations, or models, of "a face", that each subject was "seeing" in the noise.

Finally, the whole experiment was conducted while EEG data was being recorded from the participant's brains. The EEG results revealed that there was a clear difference in the neural activity associated with "face" compared to "nonface" stimuli - except in Subject 5, who you'll remember had the least coherent "internal face".

What's exciting about this approach is that it investigates perception in a purely "top down" way. Normally, when we look at anything, what we end up perceiving is a product of "bottom up" influences - the raw data - and "top down" ones - what we expect to see. In this experiment, there was no real "bottom up" data; it was all "top down".

This is a form of pareidolia - perceiving familiar things in random stimuli. Seeing the face of Jesus in your sock, that kind of thing. It works for sounds too: in the famous White Christmas Experiment, people report "hearing" music in pure white noise - when told to expect it. Real-life examples of this include the "Islam Is The Light" doll, and my personal favorite, the singing paedophile Christmas mouse.

Finally, I wonder what embodied cognition theorists make of this paper. Because this paper claims to be "Measuring Internal Representations from Behavioral and Brain Data"; embodied cognition (at least the radical kind) is the theory that "internal representations" either don't exist, or at least don't explain anything about human cognition.

Smith, M., Gosselin, F., and Schyns, P. (2012). Measuring Internal Representations from Behavioral and Brain Data Current Biology DOI: 10.1016/j.cub.2011.11.061

The Trojan Horses of Medicine

Dodgy science is being smuggled into medical journals thanks to a loophole in the regulations, say Italian psychiatrists Barbui and Cipriani in an important article.

They focus on agomelatine, a recently-approved antidepressant. But their point applies to all of medicine, not just psychiatry.

Here's the problem. Nowadays, major medical journals have rules governing systematic reviews and meta-analyses of clinical trial data. If you want to review the evidence about how well a certain drug works, or its safety, you've got to do it properly. You have to consider all of the data, not just focus on the results that suit you. And so on.

However, these rules don't apply to "narrative" review papers, which is a broad term meaning any kind of article meant to give a discussion of the pharmacology, history, chemistry etc. behind a particular drug. For a narrative review, there are no rules.

In particular, you can write about the clinical trial data in such articles with no restrictions. Unlike in a proper systematic review, you can cherry-pick trials and so on to your heart's content. Some narrative reviews have so much clinical data in them that they end up being, in effect, a bad systematic review. One that would never have been deemed acceptable as a systematic review.

Barbui and Cipriani argue that narrative reviews are often used in this way, namely to paint drugs in a positive light. In the case of agomelatine, they mention a number of recent narrative reviews which were supposedly about the drug's mechanism of action, but which actually contained extensive (but biased) reviews of the clinical trial data.

It's not hard to see how pharmaceutical companies might take advantage of this process.

However, the problem is surely not limited to agomelatine. It's a loophole that affects every branch of medicine:

Most medical journals require adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). It is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. Adherence to PRISMA is not required in review articles dealing with basic science issues as these articles are not focused on clinical trials.

In practice, however, the agomelatine case indicates that clinical data are regularly included and reviewed with no reference to the rigorous requirements of the PRISMA approach. These articles have this way became a modern Trojan horse for reintroducing the brave old world of narrative-based medicine into medical journals.

How do we stop this? It's simple, the authors say: just make all references to clinical data subject to PRISMA, or other accepted regulations, whatever the supposed 'primary focus' of the paper:

We argue that medical journals should urgently apply this higher standard of reporting, which is already available, easy to implement and inexpensive, to any form of clinical data presentation.

Of course, there are plenty of good narrative reviews that really do cover the pharmacology or other science in a useful way. The problem is not narrative reviews as such, but the way they're used.

Barbui, C., and Cipriani, A. (2012). Agomelatine and the brave old world of narrative-based medicine Evidence-Based Mental Health, 15 (1), 2-3 DOI: 10.1136/ebmh.2011.100485

The Age (Cohort) of Autism

New data shed light on the recent mysterious rise in the number of kids being diagnosed with autism.

The new research doesn't explain the increase, but it tells us more about it. It shows that the rise in Californian autism diagnoses (reported to the state DDS) over the period 1996 to 2005 was a cohort effect, meaning that the rates of diagnosis have got higher, the later a child was born.

A child who's 10 today (born 2002) has double of the chance of having a recorded diagnosis compared to a 14-year-old born just four years earlier, in 1998.

"That doesn't tell us anything new!" you might object (I did at first). "All that means is that rates have risen, and we knew that already". But actually it does tell us something important. Because the data could have turned out differently; rates could have risen without a cohort effect, if, in recent years, lots of diagnoses were being handed to children regardless of their age.

That didn't happen. Almost all children in California who get a diagnosis, get it at age 3 or 4. In more recent years, the average age at diagnosis actually fell slightly. The peak used to be age 4, it's now 3.

So it's not that children in general have been getting diagnosed with autism more. It's that young children are getting diagnosed more; children aren't being diagnosed "retrospectively", as it were.

Another interesting finding is that the rise in rates of 'high-functioning' autism has been much bigger than the rise in low-functioning autism (i.e. autism alongside intellectual disability), although that has risen as well. Edit: but note that their defintion of 'functioning' is rather unique; see the comments.

So what does this mean?

These data are consistent with various interpretations. It could be that rates of autism have really risen in California over this time period. But it could also be that people are getting more likely to detect and diagnose it - in young children.

Keyes, K., Susser, E., Cheslack-Postava, K., Fountain, C., Liu, K., and Bearman, P. (2011). Cohort effects explain the increase in autism diagnosis among children born from 1992 to 2003 in California International Journal of Epidemiology DOI: 10.1093/ije/dyr193