Unilaterally Raising the Scientific Standard

For years, I and others have been arguing that the current system of publishing science is broken. Publishing and peer-reviewing work only after the study's been conducted and the data analysed allows bad practices - such as selective publication of desirable findings, and running multiple statistical tests to find positive results - to run rampant.

So I was extremely interested when I received an email from Jona Sassenhagen, of the University of Marburg, with subject line: Unilaterally raising the standard.

Sassenhagen explained that he's chose to pre-register a neuroscience study on a public database, the German Clinical Trials Register (DRKS).

His project, Alignment of Late Positive ERP Components to Linguistic Deviations ("P600"), is designed to use EEG to test whether the brain generates a distinct electrical response - the P600 - in response to seeing grammatical errors. The background here is that the P600 certainly exists, but people disagree on whether it's specific to language; Sassenhagen hopes to find out.

By publicly announcing the methods he'll use before collecting any data, Sassenhagen has, in my view, taken a brave and important step towards a better kind of science.

Already, most journals require trials of medical treatments to be publicly pre-registered, and the DRKS is one such registry. This study, however, is 'pure' neuroscience with nothing clinical about it, so it doesn't need to be registered - Sassenhagen just did it voluntarily.

Further, I should point out that he offered to pre-register his data analysis pipeline too by sending it to me. Unfortunately, I didn't reply to the email in time... but that was purely my fault.

I very much hope and expect that others will follow in his footsteps. Unilaterally adopting preregistration is one of the ways that I've argued reform could get started. As I said:

This would, at least at first, place these adopters at an objective disadvantage. However, by voluntarily accepting such a disadvantage, it might be hoped that such actors would gain acclaim as more trustworthy than non-adopters.

Pre-registration puts you at a disadvantage - insofar as it limits your ability to use bad practice to fish for positive results. It means you can't cheat, essentially, which is a handicap if everyone else can.

I don't know if this is the first time anyone's opted in to registering a pure neuroscience study, but it's certainly the first case I know of it being done for an entirely new experiment.

There have, however, recently been many pre-registered attempts to replicate previously published results e.g. the Reproducibility of Psychological Science; the 'Precognition' Replications; and an upcoming special issue of Frontiers in Cognition.

Replications are good, registered ones doubly so - but they're not enough to fix bad practice on their own. To do that we need to work on the source, original scientific research.

Another Scuffle In The Coma Ward

It's not been a good few weeks for Adrian Owen and his team of Canadian neurologists.

Over the past few years, Owen's made numerous waves, thanks to his claim that some patients thought to be in a vegetative state may, in fact, be at least somewhat conscious, and able to respond to commands. Remarkable if true, but not everyone's convinced.

A few weeks ago, Owen et al were criticized over their appearance in a British TV program about their use of fMRI to measure brain activity in coma patients. Now, they're under fire from a second group of critics over a different project.

The new bone of contention is a paper published in 2011 called Bedside detection of awareness in the vegetative state. In this report, Owen and colleagues presented EEG results that, they said, show that some vegetative patients are able to understand speech.

In this study, healthy controls and patients were asked to imagine performing two different actions: moving their hand, or their toe. Owen et al found that it was possible to distinguish between the 'hand' and 'toe'-related patterns of brain electrical activity. This was true of most healthy control subjects, as expected, but also of some - not all - patients in a 'vegetative' state.

The skeptics aren't convinced, however. They reanalyzed the raw EEG data and claim that it just doesn't prove anything.

This image shows that in a healthy control, EEG activity was "clean" and generally normal. However in the coma patient, the data's a mess. It's dominated by large slow delta waves - in healthy people, you only see those during deep sleep - and there's also a lot of muscle artefacts which can be seen as 'thickening' of the lines.

These don't come from the brain at all, they're just muscle twitches. Crucially, the location and power of these twitches varied over time (as muscle spikes often do).

This wouldn't necessarily be a problem, the critics say, except that the statistics used by Owen et al didn't control for slow variations over time i.e. of correlations between consecutive trials (non-independence). If you do take account of these, there's no statistically significant evidence that you can distinguish the EEG associated with 'hand' vs 'toe' in any patients.

However, in their reply, Owen's team say that:

their reanalysis only pushes two of our three positive patients to just beyond the widely accepted p=0.05 threshold for significance - to p=0.06 and p=0·09, respectively. To dismiss the third patient, whose data remain significant, they state that the statistical threshold for accepting command-following should be adjusted for multiple comparisons... but we know of no groups in this field who routinely use such a conservative correction with patient data, including the critics themselves.

I have to say that, statistical arguments aside, the EEGs from the patients just don't look very reliable, largely because of those pesky muscle spikes. A new method for removing these annoyances has just been proposed... I wonder if that could help settle this?

Goldfine, A., Bardin, J., Noirhomme, Q., Fins, J., Schiff, N., and Victor, J. (2013). Reanalysis of "Bedside detection of awareness in the vegetative state: a cohort study" The Lancet, 381 (9863), 289-291 DOI: 10.1016/S0140-6736(13)60125-7

Getting The Position Right For EEG

In science, it's often the most 'boring', easily overlooked factors that determine whether an experiment succeeds or fails.

A new paper reveals strong effects of body posture on brain electrical activity: Subject position affects EEG magnitudes. Just lying face-up as opposed to face-down can powerfully affect the signal measured using electroencephalography (EEG), according to Justin Rice and colleagues of New York.

Here's why: EEG uses electrodes, placed on the scalp, to measure the electrical potentials produced by brain firing.

The signal recorded depends, however, not just on the brain activity but also on the quality of the electrical conduction between the brain and the scalp: the signals have to travel through the fluids surrounding the brain, then the skull, and finally the skin, before they're detected.

EEG users sometimes think of brain-scalp conductivity as a fixed factor, that they can't control and don't have to worry about. However, Rice et al point out that the position of the brain shifts within the skull depending upon your posture.

This is because there's a bit of extra room in there, leaving space for the brain to "bounce around" a little within its fluid cavity. If you're lying on your back, the brain will lie closer to the back of the skull; if you're on your front, it'll be further forward, and so on. So the fluid layer between brain and skull will be corresponding thinner, or thicker.

In a healthy brain the change is only about 1 mm, but the fluid layer's only 3 mm at most, so that's a big change.

Others have recognized this problem before, but Rice et al's data are the clearest evidence yet that posture is a major factor. They showed that subjects lying on their back (supine) showed significantly stronger activity over the back of the brain - which makes sense, as it brings the brain closer to the electrodes. Lying face down (prone) made activity weaker and sitting was in between.

Interestingly - and worryingly - the effect was stronger depending upon the kind of activity being measured. For most kinds of brain activity it was about 40% higher but for gamma waves - the hottest thing in EEG right now - it was almost 80%.

So gamma band activity is especially sensitive to posture, and that raises the worrying possibility that even slight differences in head position between individuals could account for 'differences' in gamma power recorded, for example in studies comparing neurological patients and healthy controls; if the controls are sitting up straight while the patients are slouching back... the patients would seem to have more gamma.

Rice JK, Rorden C, Little JS, and Parra LC (2012). Subject position affects EEG magnitudes. NeuroImage PMID: 23006805

Militarization of Neuroscience?

US military tech hothouse DARPA have an exciting announcement:

Tag Team Threat-recognition Technology Incorporates Mind, Machine
DARPA links human brainwaves, improved sensors, cognitive algorithms to improve target detection...

In what is - to my knowledge - the first example of the direct militarization of neuroscience, DARPA have developed a system in which electrical responses in a human brain are an integral step.

A soldier watches a screen on which, via various cameras, possible battlefield "threats" are shown. The cameras are fancy, and fancy image-recognition algorithms prioritize images that resemble threats - stuff that looks a bit like a tank, an IEDs, etc. But that's just the set-up.

The neuroscience core is that rather than just having a guy watching this screen and pressing a button if he spots something, they have a guy wired up with EEG to record brain activity. The system registers a threat when a picture causes a P300 response.

Now, the P300 is an electrical wave triggered by stimuli that are somehow 'meaningful' to the individual person. If you ask someone to press a button whenever they see a red light, for example, and then show them various lights, red ones will elicit a P300.

Very clever. But it may be too clever for its own good.

We already have a system that can detect the P300. It's the brain. No, most of us don't think of it as in those terms - we think of it as "Oh!" or "WTF?" or "Button press time" - but that response is the P300 (or rather something that precedes it because the P300 takes 300 milliseconds to peak, but you can respond faster than that.)

So why the EEG?

You could program a computer to detect P300s in a guy's brain and set off an alarm. DARPA apparently have. But it would be easier and cheaper to just 'program' the guy's brain to detect the P300 and push an alarm button - by asking him to do that. The human brain is a supercomputer that's been in development for hundreds of millions of years and it's primary job is to detect threats and act on them as quickly as possibly. One day technology might be able to do better but I don't think we're there yet.

DARPA say:

In testing of the full CT2WS kit, the sensor and cognitive algorithms returned 810 false alarms per hour. When a human wearing the EEG cap was introduced, the number of false alarms dropped to only five per hour, out of a total of 2,304 target events per hour, and a 91% percent successful target recognition rate.

All that tells us is that having a human check the pics via EEG is better than having no human involved at all. That's fine, but would a human just checking the pics via a button, be even better? We're not told. Maybe DARPA ran those tests and it really does offer advantages, but off the top of my head I can't think of any, and it wouldn't be the first time that the allure of high-tech neuroscience has blinded smart people to the fact that there's an easier, less sexy solution.

Unless...

OK. This is going to make me sound like a conspiracy nut. But there's one scenario in which the P300 has a decided advantage: unlike a button press, it's involuntary. It would work even if the guy doesn't want to co-operate.

So suppose you've captured a terrorist and you want to know who his terrorist friends are or where they've put the bomb. But he's not talking and Samuel L Jackson is off sick. So you wire him up to this system and show him a bunch of pictures of all the possible suspects or targets on your database. His brain will respond with a P300 to the ones he recognizes.

That would probably work - sometimes - and the P300 is already being trialled in some legal contexts for just that purpose although it's not clear how reliable it is.

So it's just possible that this whole soldier-scanning-the-battlefield story is merely an elaborate front (and perhaps a useful source of crucial calibration data) for a device to allow the CIA to read minds. I warned you it would make me sound crazy. Quick! Pass the tinfoil hat...!

Brains In A Dish Need Sleep Too?

All animals sleep, but despite decades of research, neuroscientists still have no clear answer as to why. Now a dramatic new study reveals that sleep may be a fundamental state that even brain cells growing in a dish need.

Swiss neuroscientists Valerie Hinard and colleagues cultured mouse cortical neurons in dishes equipped with arrays of electrodes. This allowed them to record the electrical activity produced by the growing 'brain'. They also measured the expression of different genes in the neurons, and compared these to gene expression in real mouse brains.

They found that while cultures of neurons started out fired randomly, after about 10 days, the cultures entered a state of synchronized periodic firing, with the whole population of cells firing together in slow cycles of activity - with a frequency of 1 cycle every 5 to 15 seconds. This is extremely slow - by contrast the "slow waves" characteristic of animal sleep cycle about 30 times faster - but the authors say that such ultra-slow waves have been seen in sleeping animals too.

But the dishes could be 'woken up' by adding a mixture of neurotransmitters, which abolished the burst cycles. They reappeared about 24 hours later. Gene expression changes in the cells in the 'sleep' and 'wake' state were significantly correlated with changes seen in real mice deprived of sleep.

Finally - and this might end up being the most important bit - the authors compared the biochemistry of the 'sleep deprived' dishes to the 'well rested' ones. They found remarkably few major changes, but they did observe a significant increase in the levels of lysolipids.

Lysolipids are breakdown products of phospholipids, which make up the membranes of all living cells. When present in membranes, lysolipids can act as 'detergents', distorting their structure. That's bad. These results suggest that sleep might serve to prevent the build up of lysolipids. If that pans out, it would mean that the function of sleep is very primitive, a fundamental biological necessity for any connected network of neurons, even what amounts to a random medley thrown together on a plate.

This study used cultured mouse neurons, but it's possible to grow human brain cells in a dish too. The obvious next step will be to check if human neurons exhibit the same sleep/wake-like states - and whether the very slow synchronized firing is really like human sleep. If so, could this help understand insomnia? Narcolepsy? Maybe even jetlag?

It's also got implications for all other brain-in-a-dish research. Scientists may literally need to ensure that their dishes get enough sleep in future studies.

It's all very exciting. I don't study sleep in my own research, but I try to keep up with the literature as I find it very interesting. I've covered various aspects of sleep neuroscience previously. So while I'm no expert, this seems to me like truly groundbreaking stuff, and potentially a "game changer" for the whole of neuroscience.

Hinard V, Mikhail C, Pradervand S, Curie T, Houtkooper RH, Auwerx J, Franken P, and Tafti M (2012). Key electrophysiological, molecular, and metabolic signatures of sleep and wakefulness revealed in primary cortical cultures. The Journal of neuroscience : the official journal of the Society for Neuroscience, 32 (36), 12506-17 PMID: 22956841

Cocktail-Party Neuroscience

"That's all very well, but what about the real world?"

This, or something to this effect, is a stock criticism of much of psychology and cognitive neuroscience. Studies of human behavior and brain function under carefully controlled laboratory conditions don't tell us much about everyday life, the argument goes.

It's a serious point. But a group of neuroscientists have now sought to dispel such worries in rather spectacular fashion. With the help of some nifty wireless headsets, Alan Gevins and colleagues of San Francisco took electroencephalography (EEG) out of the lab and organized an EEG party - allowing them to record brain electrical activity from 10 people as they chatted and drank vodka martinis. An electroencephalorgy one might say.

This is perhaps the only time in history that scientists have admitted, on record, to getting drunk with their research funding.

Pics or it didn't happen? They have pics:

And more:

The odd device held by the girl in blue is an alcohol breathalyser, which brings us onto the purpose of the study, which was to measure the effect of alcohol on brain activity.

The authors first measured the effect of alcohol on brain alpha, beta and theta band activity under standard lab conditions, and then checked to see if the results translated to the party. They did, surprisingly well in fact (although the whole thing relied on a multivariate model of the kind that make purists suspicious.)

Still, only 40% of the party data was deemed unusable due to electrical artifacts caused by participants speaking, swallowing, chewing and so forth, which is pretty good, and suggests that real-world EEG could be much more feasible than many neuroscientists would have predicted (given how annoying these sources of noise can be even under lab conditions I'd have guessed it would be more like 90%).

Now I'll make an admission: when I first read this paper, I was cynical. I felt sure it was some kind of advert for the authors' products, probably the nifty wireless EEG caps they used. "Oh very clever," I thought. "You run a wacky study, it goes viral, and you get free advertising. Well, it's worked on me, but I'm going to call you out on it."

However, the authors were one step ahead, because the paper assures readers that:

The authors are employed by the San Francisco Brain Research Institute and SAM Technology which are 100% supported by competing research grants from the U.S. Federal Government... The organization only performs research and offers no services or products. None of the authors perform consulting work. It is very unlikely that any corporation, investor, etc. would find it commercially worthwhile to buy or license the technologies that the authors have made to do their research.

OK then.

Gevins A, Chan CS, and Sam-Vargas L (2012). Towards measuring brain function on groups of people in the real world. PloS one, 7 (9) PMID: 22957099

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

Tired Brains Are More Excitable

An important new study shows how being awake causes progressive changes to the brain. This could shed light on the function of sleep - but it also raises warnings for neuroscientists.

Italian researchers Huber et al report that Human Cortical Excitability Increases with Time Awake. The experiment was conceptually simple - they measured cortical excitability when people were well rested and then looked to see how it changed as they were kept awake for over 24 hours.

The participants woke up at 7 am on Day 1 and were kept awake all of that day, all of the subsequent night, and all of Day 2. The excitability measurements spanned a period of 30 hours, from 9 am to 3 pm the next day. They were finally allowed to go to sleep on the next night and one final session took place on Day 3. I hope they got well paid for taking part.

The results showed a nice linear increase in excitability with increasing time spent awake. Sleep put this back to normal - mostly:

"Excitability" was measured using electroencephalography (EEG) combined with transcranial magnetic stimulation (TMS). Essentially, they zapped the brain (left frontal cortex) with a strong magnetic pulse, and measured the electrical activity that this provoked in the brain.

It was a small study but the findings look solid, with all six participants showing clearly higher stimulation-evoked potentials after sleep deprivation. EEG cortical theta band activity was also correlated with time spent awake, replicating previous findings.

The authors say that these data fit with the idea that the function of sleep is to prevent the brain from becoming too excitable. I previously described this as the "defragmentation" hypothesis of sleep.

The theory goes that while we're awake, our brains are constantly forming new and stronger synaptic connections, as we learn and remember. Most of the new connections are excitatory. However this creates a problem because the brain must maintain a delicate balance between excitation and inhibition. Too much neural excitation and you'll have a seizure, amongst other things. So some researchers believe that during sleep, the brain "prunes" the new excitatory connections in such a way that the information they store is preserved, but the overall excitability is reset.

These data are the first clear-cut human evidence in favor of the theory. Most of the previous work was in animals.

So sleep researchers will be very interested by this paper, but all neuroscientists should take note. If being awake changes cortical excitability, it means that the time of day that you conduct your experiments could have an impact on your results. EEG researchers should pay particular notice, but it could well be that these changes also affect the fMRI signal.

This could be a serious confounding factor in your data. Suppose, for example, that your healthy controls are more likely to have jobs than your patients with, say, autism or depression - which is sadly all too common. Now people with jobs would naturally prefer to attend your study later in the day, after work, leaving those with more flexible schedules to come in bright and early... you see the problem.

Huber, R., Maki, H., Rosanova, M., Casarotto, S., Canali, P., Casali, A., Tononi, G., and Massimini, M. (2012). Human Cortical Excitability Increases with Time Awake Cerebral Cortex DOI: 10.1093/cercor/bhs014

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

Dream Action, Real Brain Activation

A neat little study has brought Inception one step closer to reality. The authors used fMRI to show that dreaming about doing something causes similar brain activation to actually doing it.

The authors took four guys who were all experienced lucid dreamers - able to become aware that they're dreaming, in the middle of a dream. They got them to go to sleep in an fMRI scanner. Their mission was to enter a lucid dream and move their hands in it - first their left, then their right, and so on. They also moved their eyes to signal when they were about to move their hands.

Unfortunately, only one of the intrepid dream-o-nauts succeeded, even though each was scanned more than once. Lucid dreaming isn't easy you know. Two didn't manage to enter a lucid dream. One thought he'd managed it, but the data suggested he might have actually been awake.

But one guy made it and the headline result was that his sensorimotor cortex was activated in a similar way to when he made the same movements in real life, during the lucid dream -  although less strongly. Depending on which hand he was moving in the dream, the corresponding side of the brain lit up:

EEG confirmed that he was in REM sleep and electromyography confirmed that his muscles were not in fact being activated. (During REM sleep, an inhibitory mechanism in the brain prevents muscle movement. If the EMG shows activity this is a sign that you're actually partially awake).

They also repeated the experiment with another way of measuring brain activation, NIRS. Out of five dudes, one made it. Interesting this showed the same pattern of results - weak sensorimotor cortex activation during movement - but it also showed stronger than normal supplementary motor area activation, which is responsible for planning movements.

This is rather cool but in many ways not surprising. After all, if you think about it, dreaming presumably involves all of the neural structures that are involved in really perceiving or doing whatever it is you're dreaming about. Otherwise, why would we experience it so clearly as being a dream about that thing?

It may be, however, that lucid dreaming is different, and that the motor cortex isn't activated in this way in normal dreams. I suppose it depends what the dream was about.

That raises the interesting question of what someone with brain damage would dream about. On the theory that dream experiences come from the same structures as normal experiences, you shouldn't be able to dream about something that you couldn't do in real life... I wonder if there's any data on that?

Dresler M, Koch SP, Wehrle R, Spoormaker VI, Holsboer F, Steiger A, Sämann PG, Obrig H, & Czisch M (2011). Dreamed Movement Elicits Activation in the Sensorimotor Cortex. Current biology : CB PMID: 22036177

Life With Low Serotonin, Revisited

Last year I covered the case of a young man born with a genetic disorder which caused him to suffer low levels of the monoamine neurotransmitters - serotonin, dopamine, and noradrenaline.

These are the chemicals that are widely thought to be deficient in depression, and they're the target of antidepressant drugs (especially serotonin).

If low monoamines cause depression, you'd expect someone with low monoamines to be depressed, at least on the simplest view. But the case from last year had no reported mood problems, although he did show appetite, sleep and concentration problems that were cured by serotonin replacement therapy.

Now a new case report has just appeared that tells a different story. Gabriella Horvath and colleagues from British Columbia describe two sisters. Both had a normal birth and childhood, but at the ages of 11 and 15 respectively, began to suffer severe migraines and other symptoms. Sister 1:

started having hemiplegic migraine at age 11 years, initially occurring every 3–8 weeks, lasting 4–48 hours, presenting with right or left-sided numbness and paralysis, no visual disturbances, but slurred speech, associated with vomiting, headache, and confusion, followed by weakness lasting up to 7 days, and then complete recovery. The frequency of her migraine increased slowly with age up to twice a month...

Between 12 and 20 years she had developed progressive spastic paraparesis; sensory loss in stocking distribution... urinary and bowel incontinence; bladder instability... irritable bowel syndrome; sleep problems; depressed mood; and anxiety. She needed to use a wheelchair for most of the time by the age of 17.

Sister 2 had a rather different course:

The older sister originally presented at the age of 15 years with a history of hemiplegic migraine and seizures and myoclonic jerks. EEG showed generalized spike-and-wave activity, and polyspikes with photoconvulsive [light-induced seizures] response, in keeping with juvenile myoclonic epilepsy. Her seizures were brief and infrequent and not associated with the migraine episodes...

She subsequently developed progressive weakness, frequent falls, depression, and mild bladder instability...

Various blood and genetic tests failed to get to the bottom of it. MRI scans showed abnormalities in the spinal cord and parts of the brainstem in both cases, but why?

Spinal tap studies in Sister 1 revealed very low levels of 5HIAA, which is a by-product of brain serotonin (5HT). This suggested low 5HT levels. So doctors started her on 5HTP to try to boost it.

They report that 5HTP treatment caused "improvement" in all symptoms, including the migraines, slurred speech, depression, and movement, but not immediately. She gradually went from being in a wheelchair to being able to walk around the house on crutches, although she used a wheelchair outside. However, after 3 years of treatment, at age 20, she suddenly fell into a coma lasting 2 months. She is now recovering.

Sister 2 also had low 5HIAA, and was given 5HTP. She also reported symptomatic improvement.

Blood tests reported very low platelet serotonin levels. 5HTP treatment increased this but they were still below normal. Platelet 5HT reuptake rate was also low, suggesting a problem with the 5HT reuptake transporter protein 5HTT.

But the 5HTT gene (famously known as "The Happiness Gene" although that's questionable) seemed entirely normal in these patients. The authors say however that the symptoms are, in some ways, reminiscent of mice who lack the 5HT reuptake protein (5HTT knockout mice), who also show low serotonin. Also, if it were genetic, that wouldn't explain why there were no problems at all during childhood.

So this case is a mystery. The low serotonin has no known cause, and it might just be a side effect of a deeper underlying problem, but serotonin has long been linked to migraines so it might account for some of the symptoms. The fact that 5HTP helped supports this, though it wasn't a controlled trial so we can't know for sure.

As for the depression and anxiety, improved by 5HTP, this could have been a result of low serotonin, but it could also have been a psychological reaction to the severe medical problems. It's impossible to know.

Horvath GA, Selby K, Poskitt K, Hyland K, Waters PJ, Coulter-Mackie M, & Stockler-Ipsiroglu SG (2011). Hemiplegic migraine, seizures, progressive spastic paraparesis, mood disorder, and coma in siblings with low systemic serotonin. Cephalalgia : an international journal of headache PMID: 22013141

The Partly Asleep Brain

Some animals - such as dolphins and whales - are able to "sleep with half their brain". One side of the brain goes into sleep-mode activity while the other remains awake.


But a remarkable new study has revealed that something similar may happen in humans as well - every night.

The research used a combination of scalp EEG, and electrodes planted inside the brain, to record brain activity from 5 people undergoing surgery to help cure severe epilepsy. The subjects were then allowed to go to sleep for the night, while recording took place.

As expected, after falling asleep, the EEG showed delta wave activity - strong, slow waves of electrical activity (0.5 to 4 Hz) which are typical of deep, dreamless "slow wave sleep".

However, the electrodes inside the brain told a different story. While they recorded delta waves most of the time, they also showed that there were episodes, lasting from a few seconds to up to 2 minutes, in which the motor cortex suddenly went into "waking mode". Delta waves disappeared, and were replaced with fast, unpredictable activity.

This image shows one episode, lasting just 5 seconds. The hotter the color, the more activity in a particular frequency. The higher the band, the higher the frequency. This shows a clear burst of high frequency activity in the motor cortex. The other parts of the brain showed the opposite effect - even stronger slow wave activity - at the same time.

Another area, the dorsolateral prefrontal cortex, also showed this phenomenon occasionally, but it was much less common than in the motor cortex.

There's a few caveats. These patients had severe epilepsy, and they were taking anti-convulsant drugs. This wouldn't obviously create the effects seen here, but we can't rule it out. Still, these results are intriguing.

They challenge the view of slow wave sleep as a "whole brain" phenomenon. We've known for a while that this isn't true of animals, and in people with certain sleep disorders, but this is first demonstration in healthy humans.

It may help to explain the mysterious fact that, although slow wave sleep is often referred to as "dreamless", there are consistent reports that people woken up from this phase of sleep do report dreaming (or at least thinking) about things.

While episodic arousal of the motor cortex probably wouldn't explain this per se, if the same thing happens in the visual cortex or other sensory areas, it might create dreams.

Nobili L, Ferrara M, Moroni F, De Gennaro L, Russo GL, Campus C, Cardinale F, & De Carli F (2011). Dissociated wake-like and sleep-like electro-cortical activity during sleep. NeuroImage PMID: 21718789

Gamma Waves: The Brain's Clock, Or Neural Noise?

Gamma waves are very hot at the moment.


Gamma band activity is a term for electrical oscillations recorded from the brain that have a frequency of over 25 Hz. In most brains, a peak frequency of about 40 Hz is seen. This makes gamma waves the fastest brain waves.

If you believe some recent claims, gamma waves are the answer to all the mysteries of life and the universe. They're said to underlie the symptoms of schizophrenia and autism, and they've been invoked to answer deep questions such as the binding problem and maybe conciousness itself. You can even buy a Nintendo game that promises to boost them.

A new paper from Burns et al casts doubt on all of these grand claims. Gamma-based theories of brain function all assume that gamma waves act a bit like a clock, with a consistent rhythm of about 40 Hz. Activity of about 40 Hz is indeed observed in brain recordings but is that just because the brain is randomly generating all kinds of signals, and only the 40 Hz ones "get through"?

To put it another way, imagine that you got a letter in the mail at 9 am every morning. That could be because someone is sending you one letter each day like clockwork. But it could also be that loads of people are sending you letters at random times, and your mailman only has room in his sack to deliver one each morning.

Here's the key data, recorded using electrodes implanted into the brains of two male macaque monkeys:


This shows that the monkey data closely resemble what you'd expect if gamma activity were filtered noise, and are not what you'd see if it were a more meaningful "clock". The "triangle" on the graph shows the number of bursts of a given frequency and duration.
The data also show that the phase of the gamma activity isn't consistent, which it would be if it were clocklike. In fact, the phases change entirely randomly.

So if gamma is just "filtered noise", what's the "filter"? Why 40 Hz, not 80 or 4000? Probably because this is just the maximum frequency at which neurons can fire. It takes a certain finite amount of time for cells to communicate with each other: a silicon chip can get a clock speed of many billions of hertz, but a cell just physically can't.

There's a catch, though. These monkeys were asleep, anaesthetized with the powerful opiate sufentanil. This is a good choice of drug: unlike most other sedatives and anaesthetics, you wouldn't expect an opiate to directly affect gamma oscillations. But still. If you believe that coherent gamma waves are the key to high-level concious experience, as many do, you might not expect to see much of that in the primary visual cortex in asleep animals.

However, this is clearly a very important issue, and it's not the first gamma-skeptic paper. In 2008, Yuval-Greenberg et al reported that many attempts to measure gamma activity using EEG were contaminated by electrical activity from scalp muscles. Rather than coming from the brain, the "gamma" activity reflected nothing more than tiny eye movements. The implications are still being debated.

This paper attacks the gamma hypothesis from a completely different angle, saying that even the "real" gamma in the brain, may be nothing more interesting than filtered noise.

Burns SP, Xing D, & Shapley RM (2011). Is gamma-band activity in the local field potential of v1 cortex a "clock" or filtered noise? The Journal of neuroscience : the official journal of the Society for Neuroscience, 31 (26), 9658-64 PMID: 21715631

Consciousness? FFS...

An interesting paper on the neurobiology of conscious awareness: Unconscious High-Level Information Processing.


The authors propose that consciousness may be associated, not with activation in any given area of the brain, but with recurrent information processing between areas, a kind of neural ping-pong.

When presented with sensory information, say the sight of an object, signals travel up through the brain from "primary" sensory areas to "higher" areas associated with more complicated processing. They call this the Fast Feedforward Sweep, or "FFS". Maybe not the best acronym.

Anyway, depending on the nature of the stimulus, this can lead to activation in almost any part of the brain. However, they say that it's not enough to generate consciousness; only if the later areas feedback to the earlier areas, and start a recurrent processing loop, does this happen.

This stands in contrast to the popular view, which seems to fit with common sense, that primary areas are unconscious and that consciousness is directly associated with activity in the higher areas, in particular, the prefrontal cortex (PFC).

The authors refer to fMRI and EEG studies showing that even "high level" processes, such as selective attention to stimuli, and inhibition of an action, can be triggered by subconscious cues, and that this is associated with activation in the prefrontal cortex - unconscious activation.

The details of these studies are fairly arcane but the point is that the prefrontal cortex is generally agreed to be the most developed, "highest level" part of the brain. If anywhere in the brain was going to be the seat of the soul, it's the PFC.


This shouldn't come as a surprise, though. While it's tempting to look for a part of the brain which "does" conscious experience - the "me module" - Daniel Dennet pointed out a while ago that this temptation is motivated by a fundamental confusion.

Likewise, while it seems common sense that conciousness is the "highest mental function" and therefore must be located in the highest brain area, this is a presumption: consciousness is a mystery, and we don't know if it's a high level function or not, or whether that question even makes sense.

Nor should the fact that consciousness isn't an inevitable consequence of high-level cognition come as a shock: in fact, that would be impossible. As Ryle pointed out in The Concept of Mind, this would create an infinite regression. Any conscious experience has to come from somewhere.

Right now I'm concious of choosing certain words rather than others in typing this post, in a conscious attempt to make it read better. But I'm not aware of all of the rules and experiences that guide my choices. I just feel that some words work. This feeling seems to come out of nowhere, or rather, out of the words themselves.

It isn't, of course, it's a product of calculations taking place in my brain, but I've no idea what they are. I wouldn't want to be, either: I'm too busy typing.

van Gaal S, & Lamme VA (2011). Unconscious High-Level Information Processing: Implication for Neurobiological Theories of Consciousness. The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry PMID: 21628675

Free Will Is In The Brain

Warning: this post may change your brain.


Well, all of my posts change your brain, because everything changes your brain. But this one might make a rather bigger impact than usual.

According to a new paper in Psychological Science, reading a short article which argues that free will is an illusion causes measurable changes in brain function: Inducing Disbelief in Free Will Alters Brain Correlates of Preconscious Motor Preparation.

The authors took 30 people and randomly assigned them to read one of two passages from this book. One of the quotes was a fairly forceful attack on the concept of free will, saying that all of our actions are determined by our genes and environment. The other, placebo extract, was the same length and talked about conciousness but made no reference to free will.

After that, all the volunteers were given EEG while performing the Libet Task. This was invented by the neuroscientist Benjamin Libet, and it's famous as evidence against free will. Basically, the task just involves pushing a button, and you can make an entirely free choice as to when to push it. You then report, with the help of a clock, the moment at which you decided to push it.

What Libet found, using EEG recording, was that there's an electrical change in the brain, a negative voltage called the readiness potential, which starts about 2 seconds before you move. However, most people report "deciding" to move just 200 milliseconds before the actual button click - long after "their brain decided to move", in terms of the readiness potential. Maybe.

Anyway, in the current study they found that reading about determinism reduced the size of the readiness potential, although it still happened:

So ironically, reading an argument against free will reduces the size of a phenomenon which is itself used as an argument against free will... it's enough to make your head spin. The authors say that this fits with earlier work showing that "The early RP...is restricted to movements that are executed with the 'introspective feelings of the willful realization of the intention to move at a particular time'."

This is interesting, but there's a few caveats. The result was nicely significant with a p value of 0.011, but we're not shown the data from individual participants, only the group averages so the effect might be driven by one or two outliers with huge or absent readiness potentials.

Also, it's possible that the effect wasn't about belief in free will as such, but just some kind of distraction. Maybe being confronted with the idea that free will is an illusion just shook the participants up and got them thinking hard, distracting them from the task. To their credit the authors did try to control for this by also measuring EEG responses to simple visual stimuli, finding no effect, but ideally I'd want to see a control consisting of a very controversial, non-free-will article.

In case you were wondering, here's the start of the readiness-potential-reducing passage:

“You,” your joys and your sorrows, your memories and your ambitions, your sense of personal identity and free will, are in fact no more than the behavior of a vast assembly of nerve cells and their associated molecules. Who you are is nothing but a pack of neurons.

Most religions hold that some kind of spirit exists that persists after one’s bodily death and, to some degree, embodies the essence of that human being. Religions may not have all the same beliefs, but they do have a broad agreement that people have souls. Yet the common belief of today has a totally different view. It is inclined to believe that the idea of a soul, distinct from the body and not subject to our known scientific laws, is a myth.

It is quite understandable how this myth arose without today’s scientific knowledge of nature of matter and radiation, and of biological evolution. Such myths, of having a soul, seem only too plausible. For example, four thousand years ago almost everyone believed the earth was flat. Only with modern science has it occurred to us that in fact the earth is round.

From modern science we now know that all living things, from bacteria to ourselves, are closely related at the biochemical level. We now know that many species of plants and animals have evolved over time. We can watch the basic processes of evolution happening today, both in the field and in our test tubes and therefore, there is no need for the religious concept of a soul to explain the behavior of humans and other animals...

It goes on, but I'll stop there... for the sake of your brain.

Rigoni D, Kühn S, Sartori G, & Brass M (2011). Inducing disbelief in free will alters brain correlates of preconscious motor preparation: the brain minds whether we believe in free will or not. Psychological science : a journal of the American Psychological Society / APS, 22 (5), 613-8 PMID: 21515737

Clever New Scheme

CNS Response are a California-based company who offer a high-tech new approach to the personalized treatment of depression: "referenced EEG" (rEEG).

This is not to be confused with qEEG, which I have written about previously. What is rEEG? It involves taking an EEG recording of resting brain activity and sending it - along with a cheque, naturally - to CNS Response, who compare it to their database of over 1,800 psychiatric patients who likewise had EEGs taken before they started on various drugs. They look to see which drugs worked best in people with an EEG profile similar to yours, and give you a fancy report with their recommendations.

That's not completely implausible. It could work. Does it? CNS Response and some academic collaborators have just published a paper saying yes: The use of referenced-EEG (rEEG) in assisting medication selection for the treatment of depression. How solid is it? Well, it would be wrong to say that there are many problems with this study. But then if you run off a cliff and plummet into a volcano, you've only made one mistake.

Depressed patients were randomized to one of two groups: treatment-as-usual, which generally meant the common antidepressants bupropion, citalopram, or venlafaxine, vs. rEEG-guided personalized drug treatment. The trial was pretty large, with 114 patients randomized, and pretty long, 12 weeks. The patients had failed to respond to at least one antidepressant (mean: 1.5) during the current episode, so they were slightly "treatment-resistant", though not extremely so.

What happened? The rEEG-guided group did better on the QIDS16SR self-report scale, and on most other measures. Not enormously: take a look at the graph, notice that the vertical axis doesn't start at zero. But better.
Great, they did better. But why? The problem with this study is that the rEEG-guided group got a very different set of drugs to the control group. No less than 55% of them got stimulants, either methylphenidate (Ritalin) and dexamphetamine (speed). These drugs make you feel good. That's why they're illegal, that's why people pay good money for them on the street.

It's debatable whether stimulants are clinically useful as antidepressants in the long term, but they've got a good chance of making you feel nice for a few weeks, and make you say you feel better on a rating scale. Plus there's nothing like a pep pill to drive active placebo effects.

The authors say that "Almost all of the studies with depression not associated with medical disorders have reported minimal or no antidepressant effect of stimulants", and refer to some 1980s studies - yet their own trial has just shown that they do work in more than 50% of patients, and the latest Cochrane meta-analysis finds stimulants do work in the short term...

The other big names in the EEG group were MAOis (selegiline or tranylcypromine). These are often effective in treatment-resistant depression. Not necessarily more so than other drugs, but remember that these patients had already failed at least one SSRI(*). Yet the control group were, it seems, almost all given SSRIs - either citalopram, or venlafaxine, which is effectively an SSRI at low doses, e.g. the average dose used here, 141 mg. (It does other stuff, but only at higher doses of 225 mg or 300 mg.)

In summary, there were two groups in this trial and they got entirely different sets of drugs. One group also got rEEG-based treatment personalization. That group did better, but that might have nothing to do with the rEEG: they might have done equally well if they'd just been assigned to stimulants or MAOis etc. by flipping a coin. We cannot tell, from these data, whether rEEG offered any benefits at all.

What's curious is that it would have been very simple to avoid this issue. Just give everyone rEEG, but shuffle the assignments in the control group, so that everyone was guided by someone else's EEG. So you'd give control Patient 2 the drugs that Patient 1 should have got, and vice versa; swap 3 and 4, 5 and 6, etc.

This would be a genuinely controlled test of the personalized rEEG system, because both groups would get the same kinds of drugs. It would have been a lot easier too. For one thing it wouldn't require the additional step of deciding what drugs to give the control group. The authors decided to follow the STAR*D treatment protocol in this study, which is not unreasonable, but that must have been a bit of a hard decision.

Second, it would allow the trial to be double-blind: in this study the investigators knew which group people were in, because it was obvious from the drug choice. Thirdly, it wouldn't have meant they had to exclude people whose rEEG recommended they get the same treatment that they would have got in the control group... and so on.

Hmm. Mysterious. Anyway, we may be hearing more about CNS Response soon, so watch this space.

(*) - Technically, some of them had failed an SSRI and some had failed "2 or more classes of antidepressants", but one of those classes will almost certainly have been an SSRI, because they're the first-line treatment.

DeBattista, C., Kinrys, G., Hoffman, D., Goldstein, C., Zajecka, J., Kocsis, J., Teicher, M., Potkin, S., Preda, A., & Multani, G. (2010). The use of referenced-EEG (rEEG) in assisting medication selection for the treatment of depression Journal of Psychiatric Research DOI: 10.1016/j.jpsychires.2010.05.009