Pity the poor blogger’s lot: there are more interesting papers being published every week than any essayist, however diligent, can possibly cope with. And there will be more, as the vast genetic databases give up their secrets. No sooner does one team scoop the others with a savage novelty than their rivals counter-attack with their own surprising findings. If you are curious about mankind, it is the best time to be alive. We are likely to learn more about ourselves in the next few decades than was possible in the last few centuries.

So back we go to an old theme, but with a new twist: how do women’s brains work?

To sort out this mildly contentious issue, Stuart Ritchie, up and coming member of the Edinburgh crew and its international affiliates, has provided intrigued men with a map of women’s brains. Smaller, of course, as many a man has surmised in the midst of an unexpectedly heated domestic discussion, but apparently able to function as well, or almost as well, as the male variety. Let us dig deeper into these mysteries, in the calm and measured way which befits this distinguished audience.

Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

Stuart J Ritchie, Simon R Cox, Xueyi Shen, Michael V Lombardo, Lianne M Reus, Clara Alloza, Mathew A Harris, Helen L Alderson, Stuart Hunter, Emma Neilson, David C M Liewald, Bonnie Auyeung, Heather C Whalley, Stephen M Lawrie ,Catharine R Gale, Mark E Bastin, Andrew M McIntoshIan, J Deary.

Cerebral Cortex, bhy109, https://doi.org/10.1093/cercor/bhy109

Published: 16 May 2018

https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhy109/4996558

The authors say:

Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function.

There is much to discuss here, but my attention was drawn by two phrases “considerable distributional overlap” (which in my experience means that one group is pretty different from another) and “generally greater male variance” (which agrees with most of the observations on sex differences indicating that men are leptokurtic (more variable), women more platykurtic (less variable).

Women are more at risk of dementia, depression, schizophrenia and dyslexia. Men are better than women at mental rotation tasks, and are more physically aggressive; women are more interested in people than in things, are more neurotic and more agreeable.

One of the most interesting sex differences is intelligence. Here is their introduction to the topic:

There is more to sex differences than averages: there are physical and psychological traits that tend to be more variable in males than females. The best-studied human phenotype in this context has been cognitive ability: almost universally, studies have found that males show greater variance in this trait (Deary et al. 2007a; Johnson et al. 2008; Lakin 2013; though see Iliescu et al. 2016). This has also been found for academic achievement test results (themselves a potential consequence of cognitive differences, which are known to predict later educational achievement; Deary et al. 2007b; Machin and Pekkarinen 2008; Lehre et al. 2009a, 2009b), other psychological characteristics such as personality (Borkenau et al. 2013), and a range of physical traits such as athletic performance (Olds et al. 2006), and both birth and adult weight (Lehre et al. 2009a). To our knowledge, only two prior studies have explicitly examined sex differences in the variability of brain structure (Wierenga et al. 2017; Lange et al. 1997), and no studies have done so in individuals older than 20 years. Here, we addressed this gap in the literature by testing the “greater male variability” hypothesis in the adult brain.

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We tested male–female differences (in mean and variance) in overall and subcortical brain volumes, mapped the magnitude of sex differences across the cortex with multiple measures (volume, surface area, and cortical thickness), and also examined sex differences in white matter microstructure derived from DT-MRI and NODDI. We tested the extent to which these differences were regionally-specific or brain-general, by adjusting them for the total brain size (or other relevant overall measurement; for instance, adjusting volume differences for total brain volume and cortical thickness differences for mean cortical thickness), and examining whether the differences found in the raw analyses were still present. We tested the extent to which these structural differences (in broad, regional, and white matter measures) mediated sex variation in scores on two cognitive tests, one tapping a mixture of fluid and crystallized reasoning skills (skills previously found to be linked to brain volumes; Pietschnig et al. 2015) and one testing processing speed (previously found to be linked to white matter microstructural differences; see Penke et al. 2012). At the functional level, we also examined large-scale organization of functional networks in the brain using resting-state fMRI functional connectivity data and data-driven network-based analyses.

The study compared 2750 females (mean age = 61.12 years, SD = 7.42, range = 44.64–77.12) and 2466 males (mean age = 62.39 years, SD = 7.56, range = 44.23–76.99). These are extremely large samples, two orders of magnitude larger than the early studies in the 1980s, and way larger than many of the studies that the Press report so frequently. Consider them “Foxtrot Oscar” samples.

The first result is startling: male brains are very much bigger, a colossal 1.4 effect size. 92% of men will be above the mean for women. On average men have 117.8 cm3 more brain than women. All this extra brain must be doing something for men, you might surmise, other than just helping them perpetually contemplate the relative advantages of the more complicated positions adopted during sexual intercourse. Perhaps not. Broadly the same effect of male advantage can be found in all the brain region sub-comparisons. Male brains are both larger, and also vary more in size. Greater male variability seems a fact of nature. If there were a direct relationship between brain size and cognitive ability, there would be many, many more bright men than bright women.

The cognitive test was limited to a 13-item verbal-numerical test to be completed in 2 minutes, which ought to be enough to grade the general population. The mere notion of such a test will discomfort those citizens who regard their own intellects as more wide-ranging and multi-faceted than could ever be measured by mere earthly means, and who rank their brainpower of greater value to Western Civilization in ways that could not possibly be assayed in 120 seconds. Personally, I quail at the thought of having to subject myself to such a harsh evaluation. I mean, 13 into 120 is, let me see, well, not very long at all to solve each item. On reflection, 9 seconds to pass each question. Can such people exist?

The test might be a little crude if the purpose is to detect sex differences across the broad range of different cognitive tasks, and also a bit limited if the volunteers are, as one might expect of this database, somewhat brighter volunteers interested in contributing to science. However, these are minor quibbles. All intellects can be evaluated in 2 minutes. I like it. Here are the details:

Verbal-numerical reasoning. This test (UK Biobank data field 20016) consisted of thirteen multiple-choice items, six verbal and seven numerical. Participants responded to the items on a touch-screen computer. One of the verbal items was: “Stop means the same as: Pause/Close/Cease/Break/Rest/Do not know/Prefer not to answer”. One of the numerical items was: “If sixty is more than half of seventy-five, multiply twenty-three by three. If not subtract 15 from eighty-five. Is the answer: 68/69/70/71/72/Do not know/Prefer not to answer”. Participants had a two-minute time limit to answer the thirteen questions. The “prefer not to answer” option was considered as missing data for the purposes of the present analyses. The scores from the test formed a normal distribution. Reaction Time. This test (UK Biobank data field 100032), which followed immediately after the verbal-numerical reasoning test, was modelled on the game of ‘snap’: participants responded by pressing a button on a button box as quickly as possible with their dominant hand whenever the symbols on two ‘cards’ displayed to them on the computer screen matched. The test had twelve rounds; the first four rounds were considered ‘training’ (or practice) rounds so were not included in the calculation of the final score, and four of the remaining rounds did not include matching symbols. Thus, the final score was calculated on the basis of the four rounds with matching symbols (the mean time in ms to press the button across these four trials was the score variable). We excluded the scores of 8 participants who had Reaction Times of 1100ms or longer. After this exclusion, the Reaction Times formed an approximately normal distribution. Note that, for analyses, we reflected the raw scores so that higher scores meant better performance (this meant that the two cognitive tests correlated positively with each other).

The choice reaction time task should be a good measure of mental alertness, though 4 out of 8 trials is on the short side. However, there is a case for saying that all reaction time tests should have only one trial. If the person responds very slowly, in real life he would be dead. That is what reaction times are for. Here are the results for the two cognitive tests:

The insert above shows: female mean, male mean, t-test, probability, d (effect size), and finally the Bayes Factor showing the probability there is a sex difference. The full results for Table 2 are in the paper.

Sure enough, Table 2 shows that the cognitive tests are only an effect size of about 0.2 in favour of men. Where did all the male brain size advantage go? 0.2 of a standard deviation works out to 3 IQ points. Nothing much, you may say, considering that the test-retest reliability of the Wechsler is 4 IQ points, but if this is a true representation of male-female differences, then we can calculate what it would mean for the male/female balance at the higher levels of ability. As you may have seen in previous posts, if men are really 3 points brighter than women, and women’s standard deviation is narrower than men, say 14 rather than 15 points, then this makes a big difference at the higher reaches of intelligence.

Here are the estimates, if one assumes men have an IQ of 102, (sd 15) and women an IQ of 99, (sd 14).

At IQ 130: 69.8% men

At IQ 145: 80.3% men

The authors correctly point out that the sample, though the biggest collected for scanning, may not be a perfect representation of the population at large (though I doubt this directly affects sex differences).

This is a very substantial paper. It shows a massive sex difference in brain size of 1.4 d, and when one factors in that brain size relates to intelligence at a correlation of about 0.28, then the predicted intelligence difference will be a large 0.39 d, but the observed difference is only half that. Paradoxical. One implication is that there are sex-linked differences in brain structure and dendritic arborization which overcome pure size differences. If so, how is this balancing act achieved? Why don’t all people have the smaller, more craftily wired version of the human brain, which presumably requires a smaller blood supply. On the other hand, it might be that the cognitive testing has not been wide enough, and has ignored tasks in which males have an advantage. By the way, if one sex has an advantage in one skill, this is not an error of testing, it is a triumph of testing that a real difference has been revealed.

It is possible that, in a rush to ensure that men and women’s mental ability scores can be presented as equal, in general men’s stronger subject areas have been under-sampled. Test producers are under pressure to minimize sexual and racial differences. This may have suppressed the size of real differences. In defence of any group who think that their specialist strong points have been ignored, we should set the sampling frame for cognitive tests as wide as possible. These points do not invalidate the findings of this fine paper on brains, but they leave open the possibility that there is a small but real male advantage in intelligence which a broader scope of tests would reveal.

And now I must leave you. The opportunity to sit quietly in a room, mentally rotating three-dimensional objects, is too good to be missed.

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