Bacteria treat pain?

Abdominal pain is common in the general population and, in patients with irritable bowel syndrome, is attributed to visceral hypersensitivity. We found that oral administration of specific Lactobacillus strains induced the expression of mu-opioid and cannabinoid receptors in intestinal epithelial cells, and mediated analgesic functions in the gut—similar to the effects of morphine. These results suggest that the microbiology of the intestinal tract influences our visceral perception, and suggest new approaches for the treament of abdominal pain and irritable bowel syndrome

So Chris at DevIntel had a post a few days ago about a Barbara Finlay paper from 2001 that examined the ordering and relative length of phases of neurogenesis in mammals. I haven’t got a copy of the paper, but it appears that she’s arguing that the pattern of brain development is highly constrained and that changes through evolution will be quantitative rather than qualitative. This is evidence for a domain-general view of human evolution wherein first we get extra tissue and (i’m not sure of my usage here) we exapt it into human-specific brain parts.

I remembered a study from a while back suggesting that humans had a disproportionate amount of white matter in the prefrontal cortex. The author of that study (Schoenemann) has a thick 2006 review (pdf) covering many areas of human brain evolution available on his website. There are sections on cranial capacity, the fossil record, and behavioral evolution, but the bulk of the most interesting data are in the comparative internal allometry section and the genetic correlations between brain size and behavior. Neither are my specialty, but I’m really out of my league in the genetic correlations area, so I’ll give you the brain size business and you can study the other part on your own.

Brain size scales with body size in a log-log relationship. You can determine the normal parameters of this relationship by sampling brain and body sizes across primates, for instance. You can get an idea of the relative increase in brain size controlling for body size by taking the ratio of observed brain size to that expected from this line of best fit. Compared to the rest of the primates, human brains are 3.1 times too big.

Brain regions evolve at different rates. For instance, in the boring case, the motor and somatosensory cortices could grow to accommodate larger bodies leaving other regions behind. We can compare the relative region sizes across primates and control for brain size, so we know how big the region should be “for a primate brain of our size”. I like this measure more than the body size comparison because it seems to show how the brain has specialized. Thus, the human olfactory bulb, visual cortex, primary motor cortex, and premotor cortex are smaller than expected. As an aside, Michael Graziano is scrambling all of our distinctions about primary and pre- motor areas and moving away from the homunculus model that you see in your intro to neuroscience books. All these regions scale with body size reasonably, and we know we can see and move pretty well. Not only that, but the frontal lobe (which contains the motor cortices) scales properly while the motor parts lag. What is making our brains so big and raising the expectations for all these poor workhorse regions? The prefrontal cortex is what.

It turns out that measuring the prefrontal cortex (PFC) is messy because there aren’t clear markers for the boundaries. Some MRI studies have used the area in front of the corpus callosum. This underestimates the size, but does so more for humans than for other primates. Using measures such as this, we find that the human PFC is larger than expected compared to brain and body size. There are some more detailed techniques outlined in the review. Three studies in 2005 morphed common chimp, bonobo, and macaque brains into human brains and came to the conclusion that human PFCs were expanded. Also, based on traditional cytoarchitectural markers of PFC areas, specific subregions within the PFC scale at different rates. He didn’t mention any area that lags behind though, so it can’t really help us focus yet. One interesting point that runs through the analysis is that you shouldn’t write off a change in absolute size just because you can account for it using these scaling relationships. We get two examples (abstract rule learning and object-discrimination) that are better explained by absolute brain size than any relative measure.

In a semi-related note, Buzsaki suggested that a constraint on overall brain size may be axonal conduction delays. Certain cognitive feats may require synchronized oscillations in different cortical areas. While the networks can adjust to some out-of-phase inputs, there must be a certain degree of incoherence that they just can’t handle. The idea is that Neandertal brains could possibly’ve gotten too big for their bridges. If this interests you, look into gamma oscillations and binding. I don’t understand it yet well enough to explain it.

Update:Mindblog discussed a paper about long-range synchrony last week.

Aaron Haspel gives away the recipe for a productive* career in the social sciences.

* Measured the same way Alexandre Dumas got paid.

I received my latest APS Observer in the mail, and one of the main articles reports that 3 psychologists have been placed on the National Science Board, one of whom is Camilla Benbow.

This is significant for multiple reasons. While Dr. Benbow’s academic record is exemplary (here are some pdfs), her record of research on sex differences and mathematics (along with Stanley and Lubinski) ranks her among the few in this area who do not fall into the “there are no differences” camp (a la Hyde; pdf). Moreover, her writings on the cogency of cognitive ability and its influence in educational and life outcomes (no doubt stemming from her many years working with precocious youth) is very much in line with the general London School mindset. (must read: Benbow, C. P., & Stanley, J. C. (1996). Inequity in equity: How current educational equity policies place able students at risk. Psychology, Public Policy, and Law, 2, 249-293.). Consequently, I think this is the first time in the NSB’s History an Individual Differences researcher is on board. I am not sure what, if any, changes are in store at the NSF, but this a big step for the field of differential psychology and (hopefully) a sign of things to come.

Three cheers for Dr. Benbow!

At Steve Sailer’s blog, there’s an interesting discussion on height in music stars, with some evidence that country singers are taller on average than rock musicians. The mean for rock stars is ~5’10”, although personal observations in the comments suggest exaggerated heights among the shorter rock stars like Mick Jagger. I looked through the CelebHeights website for height data on “pretty boys” (e.g., Johnny Depp), and they too appear to be at or below the male population average of 5’10” (see list at the end of this post). If the apparent trend is real, it would be a nice illustration of why all males aren’t the same ideal height: there may be some ideal height, but those falling on either side of ideal will still have some niche to fill. Thus, selection is likely more of the balancing type — it keeps heights within a tolerable range, in this case normally distributed.

Just because you’re within 1 SD of the mean on the below-average side doesn’t mean you’re doomed — you can excel in areas where being short is more advantageous, such as bouncing around on stage as a musician, generating pretty boy / heartthrob appeal, or honing your skills as a dancer (which becomes more difficult as your center-of-gravity increases and your limbs become longer). This assumes the below-average individual possesses independent other appealing traits, which is why the height distribution isn’t uniform — guys who are 5’7 and otherwise unappealing will be selected against, so 5’7 males will be less frequent than 5’10 males, but enough of the former can rely on other qualities to find mates that their frequency won’t be close to zero.

Now, it may sound strange to lump being a rockstar and being a good dancer into the same category, but that just proves the point: just one generation ago during the disco era, dancing skills were highly valued in males. Now, not really. Stochastic environments tend to result in a more diverse range of phenotypes — unlike, say, the constant environment of oxygen in the air, which will weed out human lungs designed to process anything other than oxygen. So, it seems that predicting fitness based on a guy’s height is chancy enough that non-ideal phenotypes aren’t mercilessly purged from the genepool.

This scenario predicts that human height will show moderate-high heritability, since directional selection isn’t at work and so doesn’t exhaust genetic variance in the trait, and since height is not so fitness-neutral that there is nearly unconstrained variance among individuals. Sure enough, h^2 = 0.65 [see Note1]. All this said, I’m no expert on life history theory, so there are surely some subtleties that I’m missing.

As a final thought, complex modern societies open up many more niches to be exploited by yesteryear’s outcasts (asocial introverts for one), and the accelerated pace at which aspects of social life change in such societies — especially due to technological changes — introduces greater environmental stochasticity. Aside from the disco example, consider the present-day greater fitness of lesser-IQ individuals compared to higher-individuals: in the mid-19th C., who could’ve rationally predicted that the less intelligent would turn the Darwinian tables on the more brainy? If we ended welfare state policies that support large families among lower-IQ individuals, the trend could snap back to the way it was in 1850. This greater unpredictability of life compared to that of hunter-gatherer societies tells us that phenotypic variance should have exploded not long after the transition to agriculture roughly 10,000 years ago. Concluding where we began with height, Greg Cochran coined a nice mneumonic for remembering the take-home lesson here: “The bow begat the Bushmen.”

Pretty Boys

Gael Garcia Bernal 5’6.5
Tom Cruise 5’7
Wilmer Valderrama 5’7
Scott Wolf 5’7
Johnny Depp 5’8
Ryan Phillippe 5’8
Jon Bon Jovi 5’9
Jared Leto 5’9
Dave Navarro 5’9
Scott Baio 5’10
Orlando Bloom 5’10
Leonardo DiCaprio 5’10
Matt Damon 5’10
Colin Farrell 5’10
Jude Law 5’11
Brad Pitt 5’11
Mark McGrath 5’11
Jake Gyllenhaal 6′
Freddie Prinze Jr. 6’1
Gavin Rossdale 6’1
Josh Hartnett 6’3

Median = 5’10. Sex appeal doesn’t tail off as height decreases in this sample: look who’s 5’9 or shorter. I’m sure there are other data points, but I’m only going to tolerate looking up so much data on pretty boys in the interests of science. I randomly thought of as many as I could, then Googled websites showcasing pretty boys, so if anyone is going to add more data, try to make it random rather than only looking for confirming or disconfirming data points. I think I covered the real heartthrobs, though, which are the most important data. I invite those more inclined to study this — such as our legions of teenage girl readers — to pick up where I’m leaving off.

Note1: Falconer & Mackay give two references for heritability of human height, one of which is here, and the other of which is:

Huntley (1966). Heritability of intelligence. pp. 201-18 in Meade & Parkes (eds.), Genetic and Environmental Factors in Human Ability. Oliver and Boyd: Edinburgh.

Different populations have different traits– the distributions of hair color, skin color, behavior, etc., all vary between groups, and some of this variation is certainly genetic in origin. This much is clear. But how does genetics cause these population-level differences?

A new paper in Nature Genetics (see the news story here) is a start towards answering this question– the authors find a huge percentage of genes have different levels of expression in Europeans and Asians, and that these expression differences are due to common genetic variation. In addition, clustering by expression profile led to almost perfect clusters according to ethnicity (those are the two clusters–Europeans and Asians–in the picture) Here’s the abstract:

Variation in DNA sequence contributes to individual differences in quantitative traits, but in humans the specific sequence variants are known for very few traits. We characterized variation in gene expression in cells from individuals belonging to three major population groups. This quantitative phenotype differs significantly between European-derived and Asian-derived populations for 1,097 of 4,197 genes tested. For the phenotypes with the strongest evidence of cis determinants, most of the variation is due to allele frequency differences at cis-linked regulators. The results show that specific genetic variation among populations contributes appreciably to differences in gene expression phenotypes. Populations differ in prevalence of many complex genetic diseases, such as diabetes and cardiovascular disease. As some of these are probably influenced by the level of gene expression, our results suggest that allele frequency differences at regulatory polymorphisms also account for some population differences in prevalence of complex diseases.

1. This provides a neat mechanism for ethic differences– a number differentially expressed genes act in a network to give various phenotypes– be they diseases, skin colors, behaviors, or anything else with a genetic component.

2. It’s also possible that different regulatory networks have evolved in the two populations:

In addition to the variation analyzed above, some variation in expression phenotypes between populations can probably be attributed to different regulatory mechanisms. For four phenotypes, we found significant cis association in the CHB+JPT [Asian] sample but not in the CEU [European] sample.

3. The elephant in the room: The authors used cell lines from the HapMap for these studies. Besides the European and Asian samples, there’s another population in the HapMap which was not included in this paper– that of an African population from Nigeria. If a full quarter of genes have different expression profiles in Europeans and Asians, then this African population is likely to be even more different. The authors of this study certainly have the African cell lines and have probably done the expression analysis. So where’s the data?

Brainy Caltech gets first NCAA victory since 1996:

Coach Roy Dow and his squad of brainy — as opposed to brawny — Beavers beat Bard College of New York 81-52 on Saturday night, ending a mathematically improbable run of 207 consecutive NCAA Division III losses.

So the internets are abuzz about Richard Dawkins’s op-ed lamenting Saddam Hussein’s death from a scientific standpoint. There’s a lot of outrage out there, for myriad reasons. Some seem to think Dawkins is advocating experimental manipulation of Saddam’s brain or some crazy shit like that, but I think anyone calmly reading the article would come to the conclusion that he’s talking about doing interviews and maybe drawing some blood. “Psychological research” might have negative connotations for some, but observation is also research.

John Hawks and Chris at Mixing Memory have more reasonable objections related to the potential scientific utility of having Saddam around and/or the issue of informed consent. There are presumably ethical guidelines in place for research on prisoners, so I’m going to simply skip over that (Dawkins isn’t writing this for an IRB, but rather the LA Times, so give him a break). It is true, however, that it’s not immediately obvious what Hussein’s actual scientific worth would be, at least to me, a geneticist. But I imagine historians would love to ask him about his regime (sure, he might not be entirely truthful, but when is any primary source perfect?) and psychologists would love to add another well researched test case of crazy-ass dictator syndrome to the literature. And in any case, whenever there’s data available, someone will be clever enough to ask an interesting question of it– it’s not likely to be John, Chris, or I, but people are constantly researching things I’d never thought of, and I’m not bold enough to ever argue against collecting data because I can’t think of any use for it.

John Hawks’s final point is perhaps the most relevant:

I guess the reason why I am so revulsed is that Dawkins explicitly sets his interest in scientific inquiry above the cause of justice…I’d say that far more important to our future is the value of justice over science. Certainly, many people believe that Saddam’s execution did not serve justice. But scientific value should not be part of that calculation

That’s a valid objection, but I’m not sure I entirely agree. The problem is that justice can be served in a number of ways. Imgaine a less incendiary example: there are 1000 people convicted of drug related crimes who, according to the law, must be punished. Now there are a couple ways the punishment can be meted out– a certain amount of time in prison, for example, or treatment for drug abuse in some clinic. There’s a scientfic question to be asked there: which punishment has the best outcome, i.e. which reduces the future probability of being arrested the most. The experiment is obvious– assign 500 people to each punishment and follow them for X number of years, but it implies that scientific questions are considered in the selection of the punishment.

Now, this is not exactly analogous to Saddam’s case, but still, I’m not so quick to discard scientific value in the calculation of a punishment. If you’ve of the opinion that death was the only just punishment for Saddam’s crimes, then this argument isn’t for you. If, on the other hand, you think there are multiple ways justice could have been served, then I think scientific value could have been one criteria for making that choice.

PLoS Genetics has an interview with Sir John Sulston, otherwise known as the guy who mapped all the cell lineages of C. elegans using only a microscope, some pens, and a lot of paper. A representative sheet of his notes is on the right.