The Brain's High School Spot

It's been known for a long time that electrical stimulation of the brain's temporal lobe can sometimes evoke vivid memories.

The famous neurosurgeon Wilder Penfield first noticed this effect as part of his pioneering stimulation experiments, but he believed that it was both uncommon and haphazard with any given stimulation able to evoke any memory, more or less at random.

A new paper, however, says different. Philadelphia's Joshua Jacobs et al report that they found a spot in the left temporal lobe of a male patient, stimulation of which evoked memories of the man's time at high school. The guy was in his 30s at the time, so these are quite distant memories.

When it first happened, he is reported to have said:

Iʼm, like, remembering stuff from, like, high school…. Why is this suddenly popping in my head?

Repeated stimulation of the same electrode - but not nearby electrodes - caused other high school memories to emerge.

Even more interestingly, when the same stimulating electrode was used to record activity during memory retrieval, the "high school spot" was found to be significantly less active when high school was being remembered, compared to when various other kinds of memories were being accessed.

This graph shows that all kinds of memories evoked high-frequency activity in the high-school zone, but high-school memories did so less:

No other electrode location caused the same effects (or indeed, any detectable memory effects), although as you can see on the image at the top, the electrode coverage was not huge.

A little background: the guy had these electrodes in place because he suffered from epilepsy, resistant to medication, which was believed to originate in the temporal lobe. Temporal lobe epilepsy can cause memory phenomena rather like this, but this patient had never experienced that, and the electrically-evoked memories were experienced as entirely novel.

It's a nice case report and it raises many questions. Why is the high-school spot less active during memory retrieval? That seems the wrong way around (I did a double-take to make sure I was reading it properly).

And what would happen if you somehow disabled (or overactivated) this area, and asked him to remember a particular school memory? Would he draw a blank, or would he remember it but without the "high-school-ness"? What would that feel like?

Either way, this case suggests that memories are stored in the brain "by topic", in the sense that "similar" memories are associated with nearby areas of the brain. At least sometimes. But then, why didn't nearby electrodes evoke other memories? If there's a high-school spot, why not a kindergarten spot, a my-first-job spot?

Maybe those spots lay in areas with no electrode coverage... but the fact that many temporal electrodes didn't bring back any memories suggests that there's lots of cortex which isn't part of a "spot". Perhaps those areas are "spare", waiting to be used up? Clearly, he wasn't born with a high school spot. It must have emerged during high school. But in that case there had to be a "blank" area first.


Jacobs J, Lega B, and Anderson C (2011). Explaining How Brain Stimulation Can Evoke Memories. Journal of cognitive neuroscience PMID: 22098266

Scientific Databases - or Filters?

A new online database called AutismKB offers a quick way to find the evidence linking genes to autism.

You can read up on it in a paper describing the project.

You can browse by chromosome or gene name, it includes data on all kinds of genetic variants from SNPs to CNVs and it gives each variant a score according to the strength of the evidence. I haven't had a chance to really tell how useful these scores are, but there's an option to create your own score based on how much weight you give different kinds of evidence. The dataset is huge although it doesn't seem to have been updated for a few months.

Overall, it's a new tool and there's sure to be bugs to iron out, but it seems like it could be very useful. I do worry though that this kind of database encourages misleading ways of thinking about autism genetics.

There are numerous genetic variants which have been strongly linked to autism, although none of them account for more a small proportion of cases because these variants are rare. But many (most, actually, is my impression) of them have also been observed in people with other symptoms ranging from ADHD to epilepsy to schizophrenia.

So searching a database of "autism genes" could encourage you to think that these were only autism genes, which is far from true. Genetics, it is becoming increasingly clear, doesn't respect our current concepts of psychiatric illness or our academic specialities. There are few (if any) parts of the genome that can be neatly fenced off and declared exclusive to ADHD experts, schizophrenia researchers or whatever.

But disease-specific databases encourage the illusion that they do exist. It's the same old problem of the filter bubble which many people have warned about in the context of general purpose search engines. Scientists have filter bubbles too.

This is not of course a criticism of AutismKB in particular - the same goes for any similar "disease-gene" database. And to be fair AutismKB does provide links to a schizophrenia database, and a couple of others but you have to dig quite deep to get there. The "main page" of results for any given variant is pure autism.

That's the whole problem with filter bubbles - they make it too easy to hear what you want to hear, compared to getting a new perspective, so you don't even think to look outside the filter.


Xu LM, Li JR, Huang Y, Zhao M, Tang X, and Wei L (2011). AutismKB: an evidence-based knowledgebase of autism genetics. Nucleic acids research PMID: 22139918

The Network of Mental Illness

A provocative but problematic paper just out offers a new perspective on psychiatric symptoms.

The basic idea is that rather than psychiatric disorders being entities, they are just bundles of symptoms which cause each other:

...symptoms are unlikely to be merely passive psychometric indicators of latent conditions; rather, they indicate properties with autonomous causal relevance. That is, when symptoms arise, they can cause other symptoms on their own. For instance, among the symptoms of MDE we find sleep deprivation and concentration problems, while GAD (generalized anxiety disorder) comprises irritability and fatigue. It is feasible that comorbidity between MDE and GAD arises from causal chains of directly related symptoms; e.g., sleep deprivation (MDE)→fatigue (MDE)→concentration problems (GAD)→irritability (GAD).

The authors seem to have mixed up their labels in the middle there, but you see the drift.

This symptom-based approach stands in contrast to the idea that psychiatric illnesses are underlying things which lead to some symptoms. So it's a challenge to the notion of underlying biological dysfunction (except maybe for specific symptoms) but it's equally incompatible with any theory of underlying psychological causes - there's no room for Freudian unconscious "complexes" here.

So there's something very straightforward and un-mysterious about this model, which will either make it attractive or suspect, depending on whether you think human life is mysterious or not.

What's the evidence? First, the authors do an analysis of the DSM-IV diagnostic manual in terms of symptoms. They take every symptom which is mentioned in at least one diagnosis. They found 439 symptoms in total, over 201 disorders, with many symptoms, such as insomnia, shared between lots of different "disorders".

They then used network analysis to create a kind of graph where the "distance" between the nodes (symptoms) is based on the number of shared diagnoses. They found that while some symptoms are unique to just one disorder, there's a core of highly shared symptoms which form a "giant component"

It's a very clever approach but I wonder what it really tells us. The DSM-IV is not data about mental illness. It's data about what we think about mental illness. Actually, it's not even that: it's data about what a particular set of people, at a particular time, were able to agree upon.

DSM-V is coming soon, and before that we had DSM's I, II and III. What about them? Do they have a different network structure? I'd have thought they would, but we don't know.

We've already seen the kinds of politics that lie behind the decision to include or exclude a diagnosis in the DSM. In the upcoming DSM-V they're seriously proposing to add a new diagnosis ("TDDD"), purely in order to stop people getting another diagnosis (childhood "bipolar").

There is a lot of symptom overlap between TDDD and bipolar disorder. Because one was designed for the purpose of diverting patients from the other. But that doesn't tell us anything about real people with real symptoms. This is an extreme example and to be fair to the authors they do acknowledge some of these problems with the DSM, but still.

The authors then show that the symptomatic closeness between DSM-IV disorders predicts the rates of comorbidity between those disorders, as measured in the American population survey the NCS-R. This is true even of disorders which don't share a common symptom but which are connected indirectly by a mutual friendship, as it were.

Finally they show that a statistical model based on interacting symptoms can predict the prevalence of depression (10% per year according to the NCS-R survey) and GAD (3% per year). It does so much better than a random model in which symptoms randomly interact.

However, I'm not convinced that all these show us that the symptom-network approach is the best model to explain the occurence of these disorders. It only shows us that it's a model that works better than a crazy random model. I'm also not sure that being able to model the NCS-R data is even a good thing, since these data are themselves of questionable validity.

But it's a genuinely interesting approach and well worth following up.

Borsboom D, Cramer AO, Schmittmann VD, Epskamp S, and Waldorp LJ (2011). The small world of psychopathology. PloS one, 6 (11) PMID: 22114671

A Psychedelic Tale of Two Neurotransmitters

An unexpected interaction between neurotransmitter systems may explain psychosis and hallucinations, according to a fascinating new paper.

Serotonin (5HT) and glutamate are two neurotransmitters. Up until now, it was thought that they acted independently. A given neuron might have receptors for both serotonin and glutamate, but they didn't interact: serotonin would never affect the glutamate receptors, and vice versa.

The new research overturns that view. Authors Miguel Fribourg and colleagues of Mount Sinai School of Medicine show, in a series of elegant experiments in mice, that different receptors can cluster together, forming a complex. The two receptors, serotonin's 5HT2A and glutamate's mGluR2, can talk to each other.

However, this doesn't seem to happen under normal conditions. Serotonin and glutamate don't seem to trigger the receptor interaction, or at least not very much. Only certain drugs can do it. And this is where it gets really interesting.

Psychedelic drugs, like LSD, have long been thought of as 5HT2A agonists, binding to the receptor and activating it. It turns out that this was only half right. They also inhibit mGluR2 transmission via the receptor complex. Serotonin itself is a 5HT2A agonist, but it doesn't do that. So psychedelics seem to be a kind of (for want of a better word) "superagonist".

It also works in reverse. The antipsychotic drugs clozapine and risperidone are known as 5HT2A antagonists. But Fribourg et al show that they also activate the mGluR2 receptor.

And the cross-talk can go in the other direction. Certain molecules that act on mGluR2 can either inhibit or promote 5HT2A. Unlike psychedelics and antipsychotics, these mGluR2 drugs have not been tested in humans yet. But these data predict that they will have psychedelic-like or antipsychotic-like effects, depending which way they work.

The interaction turns out to be all about G proteins, which are part of the chain of transmitter substances that convey signals within the cell, in response to neurotransmitters outside it. Here's a chart showing the effects of various drugs on the balance between different G proteins: the LSD-like psychedelic DOI has the opposite effect from the antipsychotics clozapine and risperidone.

This paper builds on a previous one from the same team showing that psychedelic 5HT2A "agonists" (like LSD and DOI) have different effects on G proteins from other, non-psychedelic agonists. That was interesting in itself but by adding glutamate to the picture, this new paper is really ground-breaking.

This goes a long way to explaining one of the mysteries of serotonin which is this:  if 5HT2A agonists like LSD are psychedelic, why aren't antidepressants the same? Almost all antidepressants work by increasing extracellular 5HT levels. That ought to mean that they activate 5HT2A receptors (indirectly). This explains why not - 5HT alone doesn't promote the crucial 5HT2A-mGluR2 interaction.

Taken together, these interesting results show clearly that 5HT2A and mGluR2 are hooking up and doing something exciting. Certainly in terms of how hallucinogens work.

I'm less convinced that this can directly explain antipsychotic effects though. The problem is that while newer "atypical" antipsychotics act on 5HT2A, the older antipsychotics don't, and atypicals are at best only slightly more effective on average.

What we don't yet know is whether this kind of complex receptor interactions can happen with other receptors. I'd have thought it unlikely that these two receptors were the only ones that could ever do it. The synapse looks like it's more complex than we could have imagined.

Fribourg M, et al. (2011). Decoding the Signaling of a GPCR Heteromeric Complex Reveals a Unifying Mechanism of Action of Antipsychotic Drugs. Cell, 147 (5), 1011-23 PMID: 22118459

Beware Good Theories

The ancient Greeks had a lovely theory. Certain places on the earth (caves, mostly) were, they thought, gateways to the underworld. Plants growing near these places could absorb the deadly essence of Hades and became poisonous.

Snakes and other venemous creatures got their poison by consuming these plants. And stinging insects got their little doses of poison by feeding off dead snakes.

Isn't that a great narrative? It explains everything, in a nice logical progression. OK, it presupposes what we would call a "supernatural" force as the ultimate origin of poison, but other than that, it's an entirely "scientific" account. In accordance with Occam's Razor, it proposes a single unified process underlying diverse phenomena.

It is, in other words, a perfect scientific theory. It's completely wrong, on every point, but we only know that because we now understand atoms, molecules, chemistry and biochemistry, which the Greeks had no way of knowing. At the time, the Hades theory was surely the best possible theory about where poison came from.

The moral of this story is, beware nice theories based on incomplete data.


Reference: Greek Fire, Poison Arrows and Scorpion Bombs, which I'm currently reading, all about chemical and biological weapons.