Anthropology on BBC4

People with access to the UK digital TV channel BBC4 should note that the channel has been showing a really outstanding series of programmes on anthropology. So far there have been four, on:

– Margaret Mead

– Bronislaw Malinowski

– Desmond Morris

– Tom Harrisson.

I missed the one on Margaret Mead, but I’ve seen the others, and they were all excellent. For me the most fascinating was the one on Tom Harrisson – titled The Barefoot Anthropologist – who was evidently a remarkable individual, though I’m ashamed to say I had never heard of him. The one on Desmond Morris was another matter: I had always vaguely dismissed him (without actually reading his books) as a pop lightweight, but Armand Leroi argued persuasively in the programme that Morris’s speculations ought to be revisited in the light of more recent theories and data. As for Malinowksi, I already knew a fair amount about him, but still learned quite a lot.

I don’t know if there will be any more programmes in the series, but they are likely to be repeated either on BBC4 or BBC2. [Added: There will be one on Carlos Castaneda next week.]

I don’t know what the prospects are outside the UK: I suspect the programmes are too serious for Discovery Channel, but you never know.

Blondes are not sexier: What the theory predicts and the data say

Steve has an interesting post on assortative mating in which he purports, in passing, that blondes have greater sex appeal, citing Peter Frost’s hypothesis that blonde hair was sexually selected in Northern Europeans (I’ll post on the assortative theme later). A danger in discussing which traits might be sexually selected is that the ponderer will likely go with what they personally find sexy and ask why such things might be sexually selected, rather than work from an independent angle. For example, I am very picky about the upper eyelids — if they have that half-moon shape, that really does it for me. I’ve heard Michael say once that he likes this feature too — but then, we’re probably weirdos, or at least that’s the conclusion until someone can show that a large fraction of guys prefer this feature, and that there’s good reason to think it was sexually selected. Unlike half-moon eyes, blonde hair color receives lots of attention as a potentially sexually selected trait, but is a key prediction met — are blondes sexier?

Below the fold, I briefly review some theory but mostly present data from all winners in three beauty contests, which indicate no overrepresentation of blondes. I conclude that hair color is of weak importance at best in accounting for sexiness, that the role of sexual selection in accounting for hair color variation is also weak at best, and that the perception that men are more likely to find blondes sexy is due to a passing fad for blondes during the decade from the mid-1970s to the mid-1980s.

First, Steve notes:

One of the most common storylines in movies is this: the blonde debutante gets engaged to the blonde fraternity president, but then she falls hard for the tall, dark, and handsome boy from the wrong side of the tracks.

The idea again is that blonde hair is sexy in females, not males. But just as common as the above scenario is the guy whose feelings for his fair-haired maiden waver once he becomes enchanted by a woman with coal eyes and raven tresses. For instance, in The Hunchback of Notre Dame (see here starting at line 57), the once pure priest Frollo describes how, after watching the gypsy Esmeralda dance and sing, he became so bewitched that he could not stem the tide of lust rising within him and fell madly in love with her. Shakespeare’s “Sonnet 147” expresses a similar predicament: the speaker’s got it bad for a bad girl! Not the first, nor the last. Interesting though literature and film may be, let’s get to the theory and data.

Starting with the predictions from theory, the hypothesis that icy climes select for greater sex appeal is probably wrong. Gangestad & Buss (1993) showed that people in more pathogen-wracked areas emphasize “good looks” more strongly, and these are generally not icy areas. Think about the rest of the animal kingdom: where are the sexy, showy specimens with the most ornate song patterns? Same answer: mostly pathogen-infested areas, the tropics, etc. Consider the quintessential animal with exaggerated sexually selected traits — the peacock — whose rarer variant is native to Southeast Asia, and whose more common variant is native to the world’s germ-cauldron (South Asia). Hamilton & Zuk’s (1982) explanation was that these traits signaled better health to mates, no small feat in such areas. So, the prediction is that sexual selection will be very weak in Northern Europe (defined as the non-Mediterranean countries), where blondeness reaches substantial frequencies.

But even if sexual selection were a strong pressure there, what independently motivated evidence is there that blondeness is sexy, so that males who are sexually selecting would choose it over brunette hair? Again, the only good guess people have made is that sexually selected traits signal lack of being parasitized. For hair, though, this has mostly to do with the texture, lustruousness, and so on, not color — although I’m willing to be corrected if someone knows of studies showing that blonde hair is more likely than dark hair to thwart the entry of pathogens into the scalp area. In any event, the main problem remains: in general, pathogen pressure is relatively very low in areas where blondeness is prevalent.

Turning now to the data, I recently posted about the list of who Maxim magazine ranked the hottest women for 2006, and there was no evidence of overrepresentation of blondes. The same is true for the other “lad mags” that you see in drug stores. Now I look at two other datasets that are probably more informative than who Maxim thought was hot in 2006: the winners of the Miss Universe and Miss USA beauty pageants. (The Miss America competition is not primarily a beauty pageant, as looks account for just 35% of the score). Such lists are preferable for testing the “sexy blonde” hypothesis since the individuals represent a very elite level of eminence. I looked up galleries of the winners, and if a girl’s hair color wasn’t clear from that, I did a Google image search for her. I judged overrepresentation based on the frequency of light hair according to Peter Frost’s map at the Wikipedia entry for hair color.

For Miss Universe (gallery), there are 56 data points: 12 (21.4%) have light hair, 43 (76.8%) have dark hair, and 1 (1.8%) is pretty in-between. Now, 21.4% is surely a greater fraction of blondes than there are worldwide, but remember that Miss Universe doesn’t represent the entire world — it’s mostly Europe and its offshoots, plus the white and mestizo populations of Latin America, and a tiny handful of East Asian countries (not China). For the non-Mediterranean areas of Europe, 21.4% is on the low-end of normal, but on the high end of normal for the Mediterranean (and so, for the mostly Mediterranean-looking Latin Americans who compete). I interpret this as supporting the null hypothesis of no effect of hair color on sexiness.

As for Miss USA (gallery), there are 60 data points: 17 (28.3%) have light hair, 38 (63.3%) have dark hair, and 5 (8.4%) have borderline hair. Although the fraction is larger here, remember the US is much blonder than the Mediterranean and Latin American countries who are also big contenders in the Miss Universe competition. Because the vast majority of the US population has been Northern European since the pageant began in 1952, we should determine overrepresentation based on the Northern European areas of Peter Frost’s map. Doing so, we see that 28.3% is easily at expectation, and if anything is a bit on the low-end of normal for a predominantly Northern European population. Again, this result supports the null hypothesis.

In sum, we note that when put to a stringent test, blondes appear no sexier or uglier when compared to brunettes. Datasets such as Miss Universe and Miss USA are particularly instructive since the bar is set rather high. Then whence the perception that men find blonde
s sexier? There is an interesting temporal wrinkle in the data — blonde winners are not evenly distributed in either dataset. For Miss Universe, from 1952 – 1974, 17.4% of the 23 winners are blonde; from 1975 – 1984, 60% of the 10 winners are blonde; and from 1985 – Present, either 8.7% or 13.0% of the 23 winners are blonde (depending on whether you are generous and code the 1 borderline girl as blonde). There thus appears to be a general lack of interest in blondes (and if anything, a dispreference for them), punctuated by a decade where blondes were very fashionable. Does the same pattern show up in the Miss USA dataset? Pretty much. From 1952 – 1973, 25% of the 24 winners were blonde; from 1974 – 1986, 50% of the 14 winners were blonde; and from 1986 – Present, 18.2% of the 22 winners were blonde. We note again the spike in blonde fashionableness from the mid-1970s to the mid-1980s.

I suggest that those who came of age during this Blonde Decade — those who were born between roughly 1955 and 1970 — may have unwittingly projected their perception of the sexiness of blondes onto time periods for which the view is not true. Combine this with the theoretical problems noted earlier, and it seems likely that sexual selection’s role in increasing the frequency of blondeness is weak at best. That still doesn’t answer the question of why blondeness evolved — though I’ll leave that for another post (or someone else can take it up). The explanation that I (and others) find most convincing for now is based on Jerome Kagan’s work, starting in the mid-1980s, which has showed that light irises correlate with behavioral inhibition, suggesting that in Northern Europeans there was selection for different values of certain personality traits, which happened to also affect their eye & hair color.

Appendix: Hair color data for Miss Universe and Miss USA winners

Miss Universe (L = light, D = dark, M = borderline)

L 1952-Armi Helena Kuusela Kovo-Finland
D 1953-Christiane Magnani (Martel)-France
D 1954-Miriam Jacqueline Stevenson-USA
L 1955-Hillevi Rombin-Sweden
D 1956-Carol Laverne Morris-USA
D 1957-Gladys Zender Urbina-Peru
D 1958-Luz Marina Zuluaga-Colombia
D 1959-Akiko Kojima-Japan
D 1960-Linda Jeanne Bement-USA
L 1961-Marlene Schmidt-Germany
D 1962-Norma Beatriz Nolan-Argentina
D 1963-Ieda Maria Britto Vargas-Brazil
D 1964-Kiriaki “Corinna” Tsopei-Greece
D 1965-Apasra Hongsakula-Thailand
L 1966-Margareta Arb Arvidsson-Sweden
D 1967-Sylvia Louise Hitchcock-USA
D 1968-Martha Maria Cordeiro Vasconcellos-Brazil
D 1969-Gloria Maria Diaz Aspillera-Philippines
D 1970-Marisol Malaret Contreras-Puerto Rico
D 1971-Georgina Rizk-Lebanon
D 1972-Kerry Anne Wells-Australia
D 1973-Maria Margareta Moran Roxas-Philippines
D 1974-Amparo Muñoz Quesada-Spain
L 1975-Anne Marie Pohtamo-Finland
D 1976-Rina Messinger-Israel
D 1977-Janelle “Penny” Commissiong-Trinidad/Tobago
L 1978-Margaret Gardiner-South Africa
D 1979-Maritza Sayalero Fernández-Venezuela
L 1980-Shawn Nichols Weatherly-USA
L 1981-Irene Lailin Sáez Conde-Venezuela
D 1982-Karen Dianne Baldwin-Canada
L 1983-Lorraine Elizabeth Downes-New Zealand
L 1984-Yvonne Ryding-Sweden
D 1985-Deborah Carthy-Deu-Puerto Rico
D 1986-Bárbara Palacios Teyde-Venezuela
D 1987-Cecilia Carolina Bolocco Fonck-Chile
D 1988-Porntip Nakhirunkanok-Thailand
L 1989-Angela Visser-Holland
D 1990-Mona Grudt-Norway
D 1991-María Guadalupe “Lupita” Jones Garay-Mexico
D 1992-Michelle McLean-Namibia
D 1993-Dayanara Torres Delgado-Puerto Rico
D 1994-Sushmita Sen-India
D 1995-Chelsi Pearl Smith-USA
M 1996-Yoseph Alicia Machado Fajardo-Venezuela
D 1997-Brook Antoinette Mahealani Lee-USA
D 1998-Wendy Rachelle Fitzwilliam-Trinidad/Tobago
D 1999-Mpule Keneilwe Kwelagobe-Botswana
D 2000-Lara Dutta-India
D 2001-Denise Marie Quiñones August-Puerto Rico
D 2002-Oksana Fyodorova (Oxana Fedorova)-Russia (dethroned)
D —Justine Lissette Pasek Patiño-Panama
D 2003: Amelia Vega Polanco-Dominican Republic
L 2004: Jennifer Hawkins-Australia
D 2005: Natalie Glebova-Canada
D 2006: Zuleyka Jerris Rivera Mendoza-Puerto Rico

Miss USA

D Jackie Loughery 1952
D Myrna Hansen 1953
D Miriam Stevenson 1954
L Carlene King Johnson 1955
D Carol Morris 1956
D Leona Cage 1957
L Charlotte Sheffield 1957
M Eurlyne Howell 1958
D Terry Lynn Huntingdon 1959
D Linda Bement 1960
D Sharon Brown 1961
D Macel Wilson 1962
L Marite Ozers 1963
L Bobbie Johnson 1964
L Sue Downey 1965
D Maria Remenyi 1966
D Sylvia Hitchcock 1967
D Cheryl Ann Patton 1967
D Dorothy Anstett 1968
L Wendy Dascomb 1969
D Debbie Shelton 1970
D Michele McDonald 1971
M Tanya Wilson 1972
D Amanda Jones 1973
L Karen Morrison 1974
D Summer Bartholomew 1975
D Barbara Peterson 1976
L Kimberly Tomes 1977
L Judi Andersen 1978
M Mary Therese Friel 1979
L Shawn Weatherly 1980
L Jineane Ford 1980
L Kim Seelbrede 1981
D Terri Utley 1982
D Julie Hayek 1983
D Mai Shanley 1984
D Laura Martinez-Herring 1985
L Christy Fichtner 1986
D Michelle Royer 1987
D Courtney Gibbs 1988
D Gretchen Polhemus 1989
D Carole Gist 1990
M Kelli McCarty 1991
L Shannon Marketic 1992
D Kenya Moore 1993
D Lu Parker 1994
D Chelsi Smith 1995
D Shanna Lynn Moakler 1995
D Ali Landry 1996
D Brook Lee 1997
D Brandi Sherwood 1997
M Shawnae Jebbia 1998
D Kimberly Ann Pressler 1999
D Lynnette Cole 2000
L Kandace Krueger 2001
D Shauntay Hinton 2002
D Susie Castillo 2003
L Shandi Finnessey 2004
D Chelsea Cooley 2005
L Tara Elizabeth Conner 2006

I say inbreeding depression, you say heterosis

We’ve talked a lot about inbreeding and the its health consequences many many times before ’round these parts. Most people think of the consequences in terms of unmasking recessive disorders like rare bith defects or the inability to feel pain. But the consequences are also apparent in complex traits–a new article shows a negative correlation between heterozygosity in the genome (inbreeding causes decreased heterozygosity) and both blood pressure and cholesterol levels.

These findings, if replicated, suggest that hR [heterozygosity] be considered as a genetic risk factor in genetic epidemiological studies on common disease traits. They are consistent with the well-known effects of heterosis (hybrid vigour) described when outcrossing animals and plants. Outbreeding resulting from urbanization and migration from traditional population subgroups may be leading to increasing hR and may have beneficial effects on a range of traits associated with human health and disease. Other traits, such as age at menarche, IQ and lifespan, which have been changing during the decades of urbanization, may also have been influenced by demographic factors.


A fascinating new article in PLoS One follows up on a previous paper documenting a possible evolutionary response to sperm competition— sperm cooperation.

The idea here is simple– if a number of males mate with a female, there are a huge number of sperm competing to be the lucky one who ends up fertilizing the egg. Selection on swimming speed and efficiency must be intense– individuals with slow sperm just don’t have any offspring. However, many of those single sperm are actually from the same individual, and are thus related; if those related sperm could somehow work together to outcompete the sperm from other individuals, they might increase their fitness. The logic here is an application of Hamilton’s rule (altruism can evolve if r*B>C, where r is relatendess between two organisms, B is the benefit to cooperation, and C is the cost), except here we’re talking about haploid germ cells, not diploid organisms.

Two individual sperm share, on average, 50% of their genome, giving them an r of 0.5. So altrism can evolve if the benefit of cooperation to any individual sperm is more than half the cost; if sperm competition is strong, this might not be a bad proposition. And indeed, sperm in some rodent species band together in “trains”. The video they include is pretty sweet:

The puzzling thing for me about this is that, in some species, there can be 50-100 sperm in these “trains”, while only those sperm at the head of the train have the opportunity to fertilize the egg. This seems like a lot, and certainly suggests a very strong benefit to forming these trains, as the cost to each sperm is likely proportional to N, the number of sperm in the train.

Another possibility is suggested by noting that the relatedness of two sperm has an expectation of 0.5; some sperm will be more or less related to each other. If there were some mechanism by which more closely-related sperm could preferentially group together, the necessary benefit for Hamilton’s rule to apply would be greatly decreased, and the number of sperm willing to act altruistically greatly increased.

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Imagination and memory

A recent paper in PNAS is getting some press. Patients with hippocampal damage and amnesia (the normal symptom) are also impaired in imagining future scenarios. The authors contend that this fits with a view of the hippocampus as necessary for creating the context in which we have rich inner experiences. The data hinge on how well you think the questions asked by the researchers reflect “imagining”. The patients were given a general scenario and asked to imagine an experience there. They were usually short on descriptive richness and “spatial coherence”. But they were also generally more brief, and I’m not sure this was controlled for. Some schizophrenia patients suffer from alogia (poverty of speech). They need something like a richness/detail measure.

If the hippocampus is important for vivid, rich recollection of past experience and for making up future experiences, it seems more like a setting for memories to play out in rather than a memory storage structure per se. This doesn’t really sit with the systems consolidation or the multiple memory trace as far as I can see, but Nadel and Moscovitch have jumped on it as a challenge to systems consolidation. (Refresher: Systems consolidation = over time memories become less and less dependent on the hippocampus; multiple memory trace = the reduced effect of hippocampal lesions over time is due to propagation of memory traces within the hippocampus). I think it’s interesting that imagination and memory recollection might have the same substrate. In efforts to eschew confabulation I often demure when asked to recollect particular details of an experience, while I have seen others in the process of storytelling give very rich, but erroneous details.

This passage from a patient’s attempt to imagine himself in a museum struck me as sort of tragic. I wonder if the patient becomes as frustrated and depressed as I would failing at this task:

[pause] There’s not a lot as it happens. So what does it look like in your imagined scene? Well, there’s big doors. The openings would be high, so the doors would be very big with brass handles, the ceiling would be made of glass, so there’s plenty of light coming through. Huge room, exit on either side of the room, there’s a pathway and map through the centre and on either side there’d be the exhibits [pause] I don’t know what they are [pause]…there’d be people. [pause] To be honest there’s not a lot coming. Do you hear anything or smell anything? No, it’s not very real. It’s just not happening. My imagination isn’t… well, I’m not imagining it, let’s put it that way. Normally you can picture it can’t you? I’m not picturing anything at the moment. So are you seeing anything at all? No.

Basic concepts – linkage disequilibrium

Thinking about it today, I realized there is a “Basic Concept” that I think I should touch upon, and that is linkage disequilibrium (LD). Notice the wiki link? I do that whenever I mention LD because it is such an essential concept for some of the evolutionary ideas which I am interested in, but often not necessarily a transparent or clear one to the lay person.
chrom1.jpgIts lack of obviousness isn’t due to complexity, LD is pretty simple, rather there are particular background ideas which one needs to firmly have in mind before one can easily grasp it. For this reason I’ve placed an image of a chromosome to the left. LD is not a purely intrachromosomal concept, but, I believe a biophysical model is important in understanding it, so I will use this image for illustrative purposes in the following post. So, you know that the human genome is divided physically into chromosomes, and each chromosome consists of two sister strands of DNA, chromatids. As you see to the left diploid organisms have two copies of a gene, alleles, at each “locus.” A locus is obviously an abstract concept, it is basically a synonym for a gene. Assuming we have “gene” under our belts we can now conceive of a strand of DNA which is saturated with various genomic regions, introns, exons, intra and intergenic regions, etc. The details aren’t particularly relevant to LD, just remember that locus 1 and locus 2 on the same chromosomal strand are a particular physical distance apart.

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Hippocampal subfield differentiation

There has been a lot written in recent years about interneuron diversity. Excitatory interneurons exist, but more often than not interneurons produce and release the major inhibitory neurotransmitter, GABA. Interneurons are locally connected, and they can control local circuit oscillations and excitability. There are about a zillion different types of GABAergic interneuron based in morphology, physiology, and molecular content. All this interneuron diversity has got me wondering about the diversity of another major neuron class, the excitatory pyramidal neuron. Look, here comes one now:

They are called pyramidal because that’s how you can loosely describe the shape of their cell body. They usually have an apical dendrite that comes out of the top. The one pictured is bifurcating where the arrow is pointing. They have basilar dendrites that come out the sides near the bottom, and they have an axon that comes straight out the bottom (indicated by an arrowhead in this picture). This particular model is a CA3 pyramidal neuron, found in the CA3 subfield of the hippocampus. The hippocampus is made up of the dentate gyrus (DG) and the Ammon’s horn (cornu ammonis, CA). These are two curving rows of cell bodies all lined up so their dendrites and axons are pointing the same directions. The DG curves rather sharply and makes something like a V or a crest. The CA fields together form a milder curve that still comes out something like a C. The bottom portion of the CA “C” interlocks with the DG, so you could draw something like a S to get both subregions of the hippocampus. Here’s a link to a picture if my description is confusing. The CA1 field covers mostly the top arc or the “C”, while the CA3 field is from more like 6 to 10 on the C clockface.

If you just look at a picture of the hippocampus, the division seems completely arbitary. CA1? CA3? And what happened to CA2? There actually are meaningful differences between the subfields though and it’s not a smooth gradient. Functionally, one important distinction is connectivity. The CA3 pyramidal neurons are much more highly interconnected than CA1 pyramidal neurons. This allows them to chatter with each other and do computations locally. Some have suggested this ‘recurrent network’ property of CA3 places it in a role as a pattern completion computer. Morphologically, CA3 cells are bigger than CA1 cells. And this is where my knowledge sort of runs out and I don’t know where to look. I’d like to know the rest of the differences between CA3 and CA1 cells. I would like to know whether one of the two is more like some class of neocortical pyramidal cell. I have one last place to check, my Hippocampus book, but I don’t have it with me right now.

I did find this paper though, by Tole et al., that shows that the CA fields are specified early in development (~ embryonic day 15 in mice), and that they don’t need extrinisic cues to develop properly. These brave folks managed to dissect out embryonic hippocampi (which are tiny already) and then subdivide them into even smaller “presumptive CA fields” and grow them up. The CA1 and CA3 fields still gain the proper cell morphology and cell-type markers without any help from outside sources. They also found that the differentiation of these cell-types starts at the ends of the CA layer and works its way in, so eventually there is a hole of undifferentiation in between the CA1 and CA3 specified cells. The two finally meet at about embryonic (post-conception) day 19.5 just around the date of birth. This explains CA2 as well. CA2 is where the two differentiation signals intermingle and produce some CA3-type and some CA1-type cells. The markers used in this paper are not terribly informative about function, but could perhaps be used to derive a line of mice with different colored CA3 and CA1 cells that we could grab and do genomics on. Having good specific markers for these cell-types would, in general, assist in the development of transgenic technologies to piece apart subregion contributions to hippocampal funciton. I wonder if CA3 and CA1 pyramidal cell-types can be any further subdivided or if we already understood the full-range of hippocampal excitatory diversity.

Update:The Spruston and McBain chapter in The Hippocampus Book is a treasure trove for this kind of stuff. It’s going to require a whole new post. Also, Tole and Grove didn’t stop publishing in 1997, so I will have to look into their more recent work.