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Evidence for Natural Selection in Humans: East Asians Have Higher Frequency of CASC5 Brain Size Regulating Gene
Brain size is one physical difference that the races differ on. East Asians have bigger brains than Europeans who have bigger brains than Africans (Beals et al, 1984; Rushton, 1997). What caused these average differences and the ultimate causes for them have been subject to huge debate. Is it drift? Natural/sexual selection? Mutation? Gene flow? Epigenetic? One reason why brains would need to be large in colder climates is due to heat retention, while in tropical climates heads need to be smaller to dissipate heat. One of the biggest criticisms of HBD is that there is no/little evidence of recent natural selection between human races. Well, that has changed.
CASC5 “performs two crucial functions during mitosis, being required for correct attachment of chromosome centromeres to the microtubule apparatus, and also essential for spindle-assembly checkpoint (SAC) signaling” (Shi et al, 2016). The gene has been found to be important in recent human evolution along with neurogenesis.
Shi et al (2016) genotyped 278 Han Chinese (174 females and 104 males with a mean age of 36) who were free of maladies or genetic defects. They had the coding sequences of CASC5 for humans, chimpanzees, gorillas, baboons, gibbons, orangutans, tarsiers, Denisovans, and Neanderthals. They downloaded genotypes from the Human Genome Project for their analysis.
They compared CASC5 among three human species: humans, Neanderthals, and Denisovans. Using chimpanzees as an outgroup, they discovered 45 human-specific mutations, 48 Neanderthal-specific mutations, and 41 Neanderthal-specific mutations. Further, when one exon region was aligned among modern humans, non-human primates and other mammalian species, 12 amino acid sites showed divergence between modern humans, Neanderthals, and Denisovans with 8 occurring in modern humans. Of the 8 sites in humans, 6 are preserved which implies that they were important in our evolutionary history.
Shi et al (2016) write:
At the population level, among the 8 modern human amino acid changes, two (H159R and G1086S) are fixed in current human populations, and the other six are polymorphic Fig. 1). Surprisingly, 5 of the 6 amino acid polymorphic sites showed deep between-population divergence in allele frequencies. East Asians possess much higher frequencies of the derived alleles at four sites (T43R-rs7177192, A113T-rs12911738, S486A-rs2412541 and G936R-rs8040502) as compared to either Europeans or Africans (Fig. 1), while E1285K-rs17747633 is relatively enriched in Europeans (46%), and rare in East Asians (10%) and Africans (3%). No between-population divergence was observed for T598 M-rs11858113 (Fig. 1).
So East Asians have a much higher frequency of this derived trait. This is direct evidence for natural selection in recent human evolution in regards to the physical structure of the brain.
Since most of the amino acid polymorphic sites showed between-population divergence, they decided to analyze the three classical races using 1000 genomes. The variation between the races could be due to either genetic drift or natural selection. When they analyzed certain gene regions, they observed a signal of positive selection for East Asians but not Europeans or Africans. They further tested this selection signal using “the standardized integrated haplotype score (iHS) which is used for detecting recent positive selection with incomplete sweep (i.e. the selected allele is not yet fixed)” (Shi et al, 2016). Using this method, they discovered a few SNPs with large iHS values in Europeans (7 SNPs at 4.2 percent) and none in Africans.
They also conducted a genome-wide scan of Fst, iHS, and “XPCLR (searching for highly differentiated genomimc regions as targets of selective sweeps)” (Shi et al, 2016). Several SNPs had high Fst, iHS and XPCLR scores, which indicate that these alleles have been under positive selection in East Asians. Among the fixed amino acid sites in human populations, East Asians showed 5, Europeans showed 1, and Africans showed 0 which, the authors write, “[imply] that these amino acid changes may have functional effects” (Shi et al, 2016). Furthermore, using the HDGP, they obtained the frequency of the 6 amino acid sites in 53 populations. This analysis showed that 4 of the 6 amino acid sites are “regionally enriched in East Asia .. in line with the suggested signal of population-specific selection in this area” (Shi et al, 2016).
Then, since CASC5 is a brain size regulating gene, they looked for phenotypic effects. They recruited 167 Han Chinese (89 men, 178 women) who were free of maladies. They genotyped 11 SNPs and all of the frequencies followed Harvey-Weinberg Equilibrium (which states that allele and genotype frequencies will remain constant in a population from generation to generation in the absence of evolutionary pressures; Andrews, 2010). In the female sample, 5 regions were related to gray matter volume and four were on the amino acid polymorphic sites. Interestingly, the four alleles which showed such a stark difference between East Asians and Europeans and Africans showed more significant associations in Han Chinese females than males. Those carrying the derived alleles had larger brain volumes in comparison with those who had the ancestral alleles, implying recent natural selection in East Asia for brain size.
Shi et al (2015) also attempted two replications on this allele writing:
We further conducted a replication analysis of the five significant CAC5 SNPs in two other independent Han Chinese samples (Li et al. 2015; Xu et al. 2015). The results showed that three SNPs (rs 7177192, rs11858113 and rs8040502) remained significant in Replication-1 for total brain volume and gray matter volume (Xu et al. 2015), but no association was detected in Replication-2 (Li et al. 2015) (Table S4).
It is very plausible that the genes that have regulated brain growth in our species further aid differences in brain morphology within and between races. This effect is seen mostly in Han Chinese girls. Shi et al (2016) write in the Discussion:
If this finding is accurate and can be further verified, it suggests that that [sic] after modern humans migrated out of Africa less than 100,000 years ago, the brain size may still be subject to selection.
I do believe it is accurate. Of course, the brain size could still be subject to selection; there is no magic field shielding the brain against selection pressure. Evolution does not stop at the neck.
So Shi et al (2016) showed that there were brain genes under recent selection in East Asians. What could the cause be? There are a few:
- Climate: In colder climates you need a smaller body size and big brain to survive the cold to better thermoregulate. A smaller body means there is less surface area to cover, while a larger head retains heat. It, obviously, would have been advantageous for these populations to have large brains and thus get selected for them—whether by natural or sexual selection. This could also have to do with the fact that one needs bigger eyes in colder environments, which would cause an increase in the size of the brain for the larger eyes, as well as being sharper visio-spatially.
- Intelligence: East Asians in this study showed that they had high levels of gray matter in the skull. Further, large brains are favored by an intermediately challenging environment (Gonzalez-Forero, Faulwasser, and Lehmann, 2017).
- Expertise: I used Skoyle’s (1999) theory on expertise and human evolution and applied it to racial differences in brain size and relating it to the number of tools they had to use which differed based on climate. Now, of course, if one group uses more tools then, by effect, they would need more expertise with which to learn how to make those tools so large brains would be selected for expertise—especially in novel areas.
- Vision: Large brains mean large eyes, and people from cold climates have large eyes and large brains (Pearce and Dunbar, 2011). Decreasing light levels select for larger eye size and visual cortex size in order to “increase sensitivity and maintain acuity“. Large eyeballs mean enlarged visual cortices. Therefore, in low light, large brains and eyes get selected for so one can see better in a low light environment.
Of course, all four of the examples below could (and probably do) work in tandem. However, before jumping to conclusions I want to see more data on this and how the whole of the system interacts with these alleles and these amino acid polymorphic sites.
In sum, there is now evidence for natural selection on East Asians (and not Africans or Europeans) that favored large brains, particularly gray matter, in East Asians with considerable sexual dimorphism favoring women. Four of the genes tested (MCPH1, ASPM, CDK5RAP2, and WDR62) are regulated by estradiol and contribute to sexual dimorphism in human and non-human primates (Shi et al, 2016). Though it still needs to be tested if this holds true for CASC5.
This is some of the first evidence that I have come across for natural selection on genes that are implicated in brain evolution/structural development between and within populations. It does show the old “Rushton’s Rule of Three“, that is, Mongoloids on top, Caucasians in the middle, and Negroids on bottom, though Caucasians were significantly closer to Africans than Mongoloids in the frequency of these derived alleles. I can see a HBDer going “They must be related to IQ”, I doubt it. They don’t ‘have’ to be related to IQ. It just infers a survival advantage in low light, cold environments and therefore it gets selected for until it reaches a high frequency in that population due to its adaptive value—whether spreading by natural or sexual selection.
The notion that there is any ‘progress’ to evolution is something that I have rebutted countless times on this blog. My most recent entry being Marching Up the ‘Evolutionary Tree’? which was a response to Pumpkin Person’s article Marching up the evolutionary tree. Of course, people never ever change their views in a discussion (I have seen it, albeit it is rare) due, mainly to, in my opinion, ideology. People have so much time invested in their little pet theories that they cannot possibly fathom at the thought of being wrong or being led astray by shoddy hypotheses/theories that confirm their pre-existing beliefs. I will quote a few comments from Pumpkin Person’s blog where he just spews his ‘correlations with brain size and ‘splits’ on the ‘evolutionary tree” that ‘proves that evolution is progressive’, then I will touch on two papers (I will cover both in great depth in the future) that directly rebut his idiotic notion that so-called brain size increases across our evolutionary history (and even before we became humans) are due to ‘progress in evolution’
I think you mistyped that, but i see your point. Problem, however, most of your used phylogenies were unbalanced.
Based on the definition you provided, but not based on any meaningful definition. To me, an unbalanced tree is . . .
This is literally meaningless. Keep showing that you’ve never taken a biology class in your life, it really shows.
All it is is ignorance to basic biological thinking, along with an ideology to prove his ridiculous Rushtonian notion that ‘brain size increases prove that evolution is progressive’.
You have yet to present ANY scientific logic, and my argument about taxonomic specificity is clearly beyond you.
Scientific logic?! Scientific logic?! Please. Berkely has a whole page on misconceptions on evolution that directly rebut his idiotic, uneducated views on evolution. It doesn’t help that his evolution education most likely comes from psychologists. Nevertheless, PP’s ‘argument’ is straight garbage. Taxonomic specificity’ is meaningless when you don’t have an understanding of basic biological concepts and evolution. (I will have much more to say on his ‘taxonomic specificity’ below.)
Was every tree perfect? No, but most were pretty close, and keep in mind that any flawed trees would have the effect of REDUCING the correlation between brain size/encephalization and branching, because random error is a source of statistical noise which obscures any underlying relationship. So the fact that I repeatedly found such robust correlation in spite of alleged problems with my trees, makes my conclusions stronger, not weaker.
The fact that you ‘repeatedly’ found ‘correlations’ in spite of the ‘problems’ with your trees makes your ‘conclusions’ weaker. Comparing organisms over evolutionary time and you notice a ‘trend’ in brain size. Must mean that evolution is progressive and brain size is its calling card!!
I’m right and all the skeptics you cite are wrong.
Said like a true idealogue.
It’s not how many splits they have that I’ve been measuring, it’s how many splits occur on the tree before they branch off. Here’s a source from 2017:
Eukaryotes represent a domain of life, but within this domain there are multiple kingdoms. The most common classification creates four kingdoms in this domain: Protista, Fungi, Plantae, and Animalia.
So you needed ‘a source from 2017’ to tell you something that is literally taught on the first day of biology 101? Keep showing how uneducated you are here.
Nothing fallacious about a correlation between number of splits and brain size/encephalization.
Post hoc, ergo propter hoc is a Latin phrase for “after this, therefore, because of this.” The term refers to a logical fallacy that because two events occurred in succession, the former event caused the latter event.
Magical thinking is a form of post hoc, ergo propter hoc fallacy, in which superstitions are formed based on seeing patterns in a series of coincidences. For example, “these are my lucky trousers. Sometimes good things happen to me when I wear them.”
P1: X happened before Y.
P2: (unstated) Y was caused by something (that happened before Y).
C1: Therefore, X caused Y.
Here is PP’s (fallacious) logic:
P1: splits (X) happened before Y (brain size increase)
P2: (unstated) brain size increase was caused by something (that happened before brain size increaes [splits on the tree])
C1: therefore, splits caused brain size increase
Now, I know that PP will argue that ‘splits on the evolutionary tree’ denote speciation which, in turn, denotes environmental change. This is meaningless. You’re still stating that Y was caused by something (that happened before Y) and therefore inferring that X caused Y. That is the fallacy (which a lot of HBD theories rest on).
You don’t get it. Even statistically insignificant correlations become significant when you get them FIVE TIMES IN A ROW. If you want to believe it was all a coincidence, then fine.
Phylogenies are created from shared derived factors. Berkely is the go-to authority here on this matter. (No that’s not appeal to authority.) Biologists collect information about a given animal and then infer the evolutionary relationship. Furthermore, PP’s logic is, again, fallacious. Berkely also has tips for tree reading, which they write:
Trees depict evolutionary relationships, not evolutionary progress. It’s easy to think that taxa that appear near one side of a phylogenetic tree are more advanced than other organisms on the tree, but this is simply not the case. First, the idea of evolutionary “advancement” is not a particularly scientific idea. There is no unbiased, universal scale for “advancement.” Second, taxa with extreme versions of traits (which might be perceived as more “advanced”) may occur on any terminal branch. The position of a terminal taxon is not an indication of how adaptive, specialized, or extreme its traits are.
He may emphatically argue (as I know he will) that he’s not doing this. But, as can be seen from his article, X is ‘less advanced’ than Y, therefore splits, brain size, correlation=progress. This is dumb.
For anyone who wants to know how (and how not to) read phylogenies, read Gregory (2008). These idotic notions that PP espouses are what Freshman in college believe due to ‘intuitiveness’ about evolution. It’s so rampant that biologists have writen numerous papers on the matter. But some guy with a blog and no science background (and an ideology to hammer) must know more than people who do this for a living (educate people on phylogenies).
On Phil’s response to see the Deacon paper that I will discuss below, PP writes:
That’s not a rebuttal.
Yes it is, as I will show shortly.
The first paper I will discuss is Deacon’s (1990) paper Fallacies of Progression in Theories of Brain-Size Evolution. This is a meaty paper with a ton of great ideas about phylogenies, along with numerous fallacies that people go to when reading trees (my favorite being the Numerology fallacy, which PP uses, see below).
Deacon argues that since people fail to analyze allometry, this anatomists have mistaken artifacts for evolutionary trends. He also argues that many structural’brain size increases’ from ‘primitive to advanced forms’ (take note here, because this is what PP did and this is what discredits his idiotic ideology) are the result of allometric processes.
Source: Evolution of consciousness: Phylogeny, ontogeny, and emergence from general anesthesia Mashour and Alkire (2013)
This paper (and picture) show it all. This notion of scala naturae (which Rushton (2004) attempted to revive with r/K selection theory has been rebutted by me) was first proposed by Aristotle. We now know how the brain structure evolved, so the old ‘simple scala naturae‘ is, obviously, out of date in the study of brain evolution.
This paper is pretty long and I don’t have time to discuss all of it so I will just provide one quote that disproves PP’s ‘study’:
Whenever a method is discovered for simplifying the representation of a complex or apparently nonsystematic numerical relationship, the method of simplification itself provides new insight into the phenomenon under study. But reduction of a complex relationship to a simple statistic makes it far easier to find spurious relationships with other simple statistics. Numerology fallacies are apparent correlations that turn out to be artifacts of numerical oversimplification. Numerology fallacies in science, like their mystical counterparts, are likely to be committed when meaning is ascribed to some statistic merely by virtue of its numeric similarity to some other statistic, without supportive evidence from the empirical system that is being described.
Deacon also writes in another 1990 article titled Commentary on Ilya I. Glezer, Myron So Jacobs, and Peter J Morgane (1988) Implications of the “initial brain’9 concept for brain evolution in Cetacea:
The study of brain evolution is one of the last refuges for theories of progressive evolution in biology, but in this field its influence is still pervasive. To a great extent the apparent “progress” of mammalian brain evolution vanishes when the effects of brain size and functional specialization are taken into account.
(It’s worth noting that in the author’s response to Deacon, he did not have any qualms about ‘progressive brain-size’.)
In regards to PP’s final ‘correlation’ on human races and brain-size, this is a perfect quote from McShea (1994: 1761):
If such a trend [increase in brain size leading to ‘intelligence’] in primates exists and it is driven, that is, if the trend is a direct result of concerted forces acting on most lineages across the intelligence spectrum, then the inference is justified. But if it is passive, that is, forces act only on lineages at the low-intelligence end, then most lineages will have no increasing tendency. In that case, most primate species—especially those out on the right tail of the distribution like ours—would be just as likely to lose intelligence as to gain it in subsequent evolution (if they change at all).
The ‘trend’ is passive. Homo floresiensis is the best example. We are just as likely to lose our ‘intellect’ and our ‘big brains’ as we are to ‘get more intelligent’ and ‘smaller brains’. The fact of the matter is this: environment dictates brain size/whatever other traits an organism has. Imagine a future environment that is a barren wasteland. Kilocalories are scarce; do you think that humans would keep their big brains—which are two percent of their body weight accounting for a whopping 25 percent of total daily energy needs—without enough high-quality energy? When brain size supposedly began to increase in our taxa is when erectus learned to control fire and cook meat (Hlublik et al, 2017).
All in all, there is no ‘progress’ to evolution and, as Deacon argues, so-called brain-size increases across evolutionary time disappear after adjustments for body size and functional specialties are taken into account. However, for the idealogue who looks for everything they can to push their ideology/worldview, things like this are never enough. “No, that wasn’t a rebuttal! YOU’RE WRONG!!” Those are not scientific arguments. If one believes in ‘evolutionary progress’ and that brain-size increases are the proof in the pudding that evolution is ‘progressive’ (re has a ‘direction’), then they must rebut Deacon’s arguments on allometry and his fallacies in his 1990 paper. Stop equating evolution with ‘progress’. Though, I can’t fault laymen for believing that. I can, however, fault someone who supposedly enjoys the study of evolution. You’re wrong. The people you cite (who are out of their field of expertise) are wrong.
Evolution is an amazing process. To equate it with ‘progress’ does not allow one to appreciate the beauty of the process. Evolution does carry baggage with it, and if I weren’t so used to the term I would use Descent by Modification (DbM, which is what Darwin used). Nevertheless, progressionists will hide out in whatever safehold they can to attempt to push their idealogy that is not based on science.
(Also read Rethinking Mammalian Brain Evolution by Terrence Deacon. I go more in depth on these three articles in the future.)
Would dinosaurs have reached human-like intellect had the K-T extinction (an asteroid impact near the Yucatan peninsula) not occurred? One researcher believes so, and he believes that a dinosaur called the troodon would have evolved into a bipedal, human-like being. This is, of course, the old progressive evolution shtick. This assumes that a man-like being is an inevitability, and that sentience is a forgone conclusion.
This belief largely comes from Rushton’s citation of one Dale Russel, the discoverer of the dinosaur the troodon:
Paleontologist Dale Russell (1983,1989) quantified increasing neurological complexity through 700 million years of Earth history in invertebrates and vertebrates alike. The trend was increasing encephalization among the dinosaurs that existed for 140 million years and vanished 65 million years ago. Russell (1989) proposed that if they had not gone extinct, dinosaurs would have progressed to a large-brained, bipedal descendent. For living mammals he set the mean encephalization, the ratio of brain size to body size, at 1.00, and calculated that 65 million years ago it was only about 0.30. Encephalization quotients for living molluscs vary between 0.043 and 0.31, and for living insects between 0.008 and 0.045 but in these groups the less encephalized living species resemble forms that appeared relatively early in the geologic record, and the more encephalized species resemble those that appeared later. (Rushton, 1997: 294)
This argument is simple to rebut. What is being described is complexity. The simplest possible organism are bacteria, which reside at the left wall of complexity. The left wall “induces right-skewed distributions”, whereas the right wall induces “left-skewed distributions” (Gould, 1996: 55). Knowing this, biological complexity is a forgone conclusion, which exists at the extreme end of the right tail curve. I’ve covered this in my article Complexity, Walls, 0.400 Hitting and Evolutionary “Progress”
Talking about what Troodons may have looked like (highly, highly, doubtful. The anthropometric bias was pretty strong) is a waste of time. I’ve stated this a few times and I’ll state it yet again: without our primate body plan, our brains are pretty much useless. Our body needs our brain; our brain needs our body. Troodons would have stayed quadrupedal; they wouldn’t have gone bipedal.
He claims that some dinosaurs would have eventually reached an EQ of humans—specifically the troodon. They had EQs about 6 times higher than the average dinosaur, had fingers to grasp, had small teeth, ate meat, and appeared to be social. Dale Russel claims that had the K-T extinction not occurred, the troodon would look similar to us with a brain size around 1100 cc (the size of erectus before he went extinct). This is what he believes the dinosauroid troodon would look like had they not died out 65 mya:
When interviewed about the dinosauroid he imagined, he stated:
The “dinosauroid” was a thought experiment, based on an observable, general trend toward larger relative brain size in terrestrial vertebrates through geologic time, and the energetic efficiency of an upright posture in slow-moving, bipedal animals. It seems to me that such speculation remains acceptable, particularly if directed toward non-anthropoid anatomical configurations. However, I very nearly decided not to publish the exercise because of the damaging effects it might have had on the credibility of my work in general. Most people remained polite, although there were hostile reactions from those with “ultra-quantitative” and “ultra-intuitive” world views.
Why does it look so human? Why does he assume that the ‘ideal body plan’ is what we have? It seems to be extremely biased towards a humanoid morphology, just as other reconstructions are biased towards what we think about certain areas today and how the people may have looked in our evolutionary past. Anthropocentric bias permeates deep in evolutionary thinking, this is one such example.
Thinking of this thought experiment of a possible ‘bipedal dinosauroid’ we need to be realistic in terms of thinking of its anatomy and morphology.
Let’s accept Russel’s contention as true; that troodontids or other ‘highly encephalized species’ reached a human EQ, as he notes, of 9.4, with troodontids at .34 (the highest), archaeopteryx at .32, triconodonts (early extinct mammal of the cretaceous) with a .29 EQ, and the diademodon with an EQ of .20 (Russel, 1983). Russel found that the troodontids had EQs 6 times higher than the average dinosaur, so from here, he extrapolated that the troodon would have had a brain our size. However, Stephen Jay Gould argued the opposite in Wonderful Life writing:
If mammals had arisen late and helped to drive dinosaurs to their doom, then we could legitimately propose a scenario of expected progress. But dinosaurs remained dominant and probably became extinct only as a quirky result of the most unpredictable of all events—a mass dying triggered by extraterrestrial impact. If dinosaurs had not died in this event, they would probably still dominate the large-bodied vertebrates, as they had for so long with such conspicuous success, and mammals would still be small creatures in the interstices of their world. This situation prevailed for one hundred million years, why not sixty million more? Since dinosaurs were not moving towards markedly larger brains, and since such a prospect may lay outside the capability of reptilian design (Jerison, 1973; Hopson, 1977), we must assume that consciousness would not have evolved on our planet if a cosmic catastrophe had not claimed the dinosaurs as victims. In an entirely literal sense, we owe our existence, as large reasoning mammals, to our lucky stars. (Gould, 1989: 318)
If a large brain was probably outside of reptilian design, then a dinosaur—or a descendant (troodon included)—would have never reached human-like intelligence. However, some people may say that dinosaur descendants may have evolved brains our size since birds have brains that lie outside of reptilian design (supposedly).
However, one of the most famous fossils ever found, archaeopteryx, was within reptilian design, having feathers and along with wings which would have been used for gliding (whether or not they flew is debated). Birds descend from therapods. Anchiornis, and other older species are thought to be the first birds. Most of birds’ traits, such as bipedal posture, hinged ankles, hollow bones and S-shaped neck in birds are derived features from their ancestors.
If we didn’t exist, then if any organism were to come close to our intelligence, I would bet that some corvids would, seeing as they have a higher packing density and interconnections compared to the “layered mammalian brain” (Olkowicz et al, 2016). Nick Lane, biochemist and author of the book The Vital Question: Evolution and the Origins of Complex Life believes a type of intelligent ocotopi may have evolved, writing:
Wind back the clock to Cambrian times, half a billion years ago, when mammals first exploded into the fossil record, and let it play forwards again. Would that parallel be similar to our own? Perhaps the hills would be crawling with giant terrestrial octopuses. (Lane, 2015: 21)
We exist because we are primates. Our brains are scaled-up primate brains (Herculano-Houzel, 2009). Our primate morphology—along with our diet, sociality, and culture—is also why we came to take over the world. Our body plan—which, as far as we know, only evolved once—is why we have the ability to manipulate our environment and use our superior intelligence—which is due to the number of neurons in our cerebral cortex, the highest in the animal kingdom, 16 billion in all (Herculano-Houzel, 2009). Why postulate that a dinosaur could have looked even anywhere close to us?
This is also ignoring the fact that decimation and diversification also ‘decide the fates’ so to speak, of the species on earth. Survival during an extinction event is strongly predicated by chance (and size). The smaller an organism is, the more likely it will survive an extinction event. Who’s to say that the troodon doesn’t go extinct due to an act of contingency, say, 50 mya if the K-T extinction never occurred?
In conclusion, the supposed ‘trend’ in brain size evolution is just random fluctuations—inevitabilities since life began at the left wall of complexity. Gould wrote about a drunkard’s walk in his book Full House (Gould, 1996) in which he illustrates an example of a drunkard walking away from a bar with the bar wall being the left wall of complexity and the gutter being the right wall. The gutter will always be reached; and if he hits the wall, he will lean against the wall “until a subsequent stagger propels him in the other direction. In other words, only one direction of movement remains open for continuous advance—toward the gutter” (Gould, 1996: 150).
I bring up this old example to illustrate but one salient point: In a system of linear motion structurally constrained by a wall at one end, random movement, with no preferred directionality whatever, will inevitably propel the average position away from a starting point at the wall. The drunkard falls into the gutter every time, but his motion includes no trend whatever toward this form of perdition. Similarly, some average or extreme measure of life might move in a particular direction even if no evolutionary advantage, and no inherent trend, favor that pathway (Gould, 1996: 151).
We humans are lucky we are here. Contingencies of ‘just history’ are why we are here, and if we were not here—if the K-T extinction never occurred—and the troodon or another dinosaur species survived to the present day, they would not have reached our ‘level’ of intelligence. To believe so is to believe in teleological evolution—which certainly is not true. Anthropometric bias runs deep in evolutionary biology and paleontology. People assume that since we are—according to some—the ‘pinnacle’ of evolution, that us, or something like us, would eventually have evolved.
Any ‘trends’ can be explained as life moving away from the left wall of complexity, with the left wall—the mode of life, the modal bacter-–being unchanged. We are at the extreme tail of the distribution of complexity while bacteria are at the left wall. Complex life was inevitable since bacteria, the most simple life, began at the left wall. And so, these ‘trends’ in brain size are just that, increasing complexity, not any type of ‘progressive evolution’. Evolution just happens, natural selection occurs based on the local environment, not any inherent or intrinsic ‘progress’.
Gould, S. J. (1989). Wonderful life: the burgess Shale and the nature of history. New York: Norton.
Gould, S. J. (1996). Full house: The Spread of Excellence from Plato to Darwin. New York: Harmony Books.
Herculano-Houzel, S. (2009). The human brain in numbers: a linearly scaled-up primate brain. Frontiers in Human Neuroscience,3. doi:10.3389/neuro.09.031.2009
Lane, N. (2015). The vital question: energy, evolution, and the origins of complex life. New York: W.W. Norton & Company.
Olkowicz, S., Kocourek, M., Lučan, R. K., Porteš, M., Fitch, W. T., Herculano-Houzel, S., & Němec, P. (2016). Birds have primate-like numbers of neurons in the forebrain. Proceedings of the National Academy of Sciences,113(26), 7255-7260. doi:10.1073/pnas.1517131113
Rushton J P (1997). Race, Evolution, and Behavior. A Life History Perspective (Transaction, New Brunswick, London).
Russell, D. A. (1983). Exponential evolution: Implications for intelligent extraterrestrial life. Advances in Space Research,3(9), 95-103. doi:10.1016/0273-1177(83)90045-5
What is the relationship between traumatic brain injury (TBI) and IQ? Does IQ decrease? Stay the same? Increase? A few studies have looked at the relationship between TBI and IQ, and the results may be quite surprising to some. Tonight I will look through a few studies and see what the relationship is between TBI and IQ—does IQ decrease substantially or is there only a small decrease? Does it decrease for all subtests or only some?
TBI and IQ
In a sample of 72 people with TBI who had significant brain injuries had an average IQ of 90 (study 1; Bigler, 1995). Bigler also says that whatever correlation exists between brain size and IQ “does not persist post injury” (pg 387). This finding has large implications: can there be a minimal hit to IQ depending on age/severity of injury/brain size/education level?
As will be seen when I review another study on IQ and brain injury, every individual in the cohort in Bigler (1995) was tested after 42 days of brain injury. This does matter, as I will get into below.
Table 1 in study 1 shows that whatever positive relationship between IQ and brain size that is there before injury does not persist after injury (Bigler, 1995: 387). Study 1 showed that, even with mild-to-severe brain damage, there was little change in measured IQ—largely because the correlation between brain size and IQ is .51 at the high end (which I will use—the true correlation is between .24 [Pietschnig et al, 2015] to .4 [Rushton and Ankney, 2009]), this means that if the correlation were to be that high, brain size would only explain 25 percent of the variation in IQ (Skoyles, 1999). That leaves a lot of room for other reasons for differences in brain size and IQ in individuals and groups.
In study 2 (Bigler, 1995: 389-391), he looked into whether or not there were differences in IQ between high and low brain volume people (95 men). Results summed in table 3 (pg 390). Those with low brain volume (1185), aged 28, had an IQ of 82.61 while those with high brain volume (1584), aged 34 had an IQ of 92 (both cohorts had similar education). Bigler showed in study 1 IQ was maintained post injury, so we can say that this was their IQ preinjury.
In table 2, Bigler (1995) compares IQs and brain volumes of mild-to-moderate and moderate-to-severe individuals with TBI. Brain volume in the moderate-to-severe group was 1289.2 whereas for the mild-to-moderate TBI-suffering individuals had a mean brain volume of 1332.9. Amazingly, both groups had IQ scores in the normal range (90.0 for moderate-to-severe TBI and 90.7 for individuals suffering from mild-to-moderate TBI. In study 3, Bigler (1995) shows that trauma-induced atrophic changes in the brain aren’t related to IQ postinjury, nor to the amount of focal lesion volume.
Nevertheless, Bigler (1995) shows that those with bigger brains had less of a cognitive hit after TBI than those with smaller brains. PumpkinPerson pointed me to a study that shows that TBI stretches far back into our evolutionary history, with TBI seen in australopithecine fossils along with erectus fossils found throughout the world. This implies that TBI was a driver for brain size (Shivley et al, 2012); if the brain is bigger, then if/when TBI is acquired, the cognitive hit will be lessened (Stern, 2002). This is a great theory for explaining why we have large brains despite the negatives that come with them—if we were to acquire TBI in our evolutionary past, then the hit to our cognition would not be too great, and so we could still pass our genes to the next generation.
The fact that changes in IQ are minimal when brain damage is acquired shows that brain size isn’t as important as some brain-size-fetishists would like you to believe. Though, preinjury (PI) IQ was not tested, I have one study where it was.
Wood and Rutterford (2006) showed results similar to Bigler (1995)—minimal change to IQ occurs after TBI. The whole cohort pre-injury (PI) had a 99.79 IQ. T1 (early measure) IQ for the cohort was 90.96 while T2 (late measure) IQ for the cohort was 92.37. For people with greater than 11th-grade education (n=30), IQ decreased from 106.57 PI to 95.19 in T1 to 100.17 in T2. For people with less than an 11th-grade education (n=44), IQ PI was 95.16 and decreased to 86.99 in T1 and increased to 87.96 in T2. Male (n=51) and female (n=23) were similar, with male PI IQ being 99.04 to women’s 101.44 with a 90.13 IQ in T1 for men with a 90.72 IQ in T1 for women. In T2 for men it was 92.94 and for women, it was 92.83. So this cohort shows the same trends as Bigler (1995).
The most marked difference in subtests post-injury was in vocabulary (see table 3) with similarities staying the same, and digit symbol, and block design increasing between T1 and T2. Neither group differed between T1 and T2. The only significant association in performance change over time was years of education. Less educated people were at greater risk for cognitive decline (see table 2).
The difference for PI IQ after T2 for less educated people was 7.2 whereas for more educated people it was 6.4. Though more educated people gained back more IQ points between T1 and T2 (4.98 points) compared to less educated people (.97 IQ points). And: “The participants in our study represent a subgroup of patients with severe head injury reported in a larger study assessing long‐term psychosocial outcome.”
Bigler (1995) didn’t have PI IQ, but Wood and Rutterford (2006) did, and from T1 to T2 (Bigler 1995 tested what would be equivalent to T1 in the Wood and Rutterford 2006 study), IQ hardly increased for those with lower education (.97 points) but substantially increased for those with higher education (4.98 points) with there being a similar difference between PI IQ and T2 IQ for both groups.
Brain-derived neurotrophic protective factor (BDNF) also promotes survival and synaptic plasticity in the human brain (Barbey et al, 2014). They genotyped 156 Vietnam War soldiers with frontal lobe lesion and “focal penetrating head injuries” for the BDNF polymorphism. Though they did find differences in the groups with and without the BDNF polymorphism, writing that there were “substantial average differences between these groups in general intelligence (≈ half a standard deviation or 8 IQ points), verbal comprehension (6 IQ points), perceptual organization (6 IQ points), working memory (8 IQ points), and processing speed (8 IQ points) after TBI” (Barbey et al, 2014). This supports the hypothesis that BDNF is protective against TBI; and since BDNF was important in our evolutionary history which is secreted by the brain while endurance running (Raichlen and Polk, 2012), this could have also been another protective factor against hits to cognition that were acquired, say, during hunts or fights.
Nevertheless, one study found in a sample of 181 children Crowe et al (2012) found that children with mild-to-moderate TBI had IQ scores in the average range, whereas children with severe TBI had IQ scores in the low average range (80 to 90; table 3).
Infants with mild TBI had IQ scores of 99.9 (n=20) whereas infants with moderate TBI has IQs of 98.0 (n=23) and infants with severe TBI had IQs of 90.7 (n=7); preschoolers with mild TBI had IQ scores of 103.8 (n=11), whereas preschoolers with moderate TBI had IQ scores of 100.1 (n=19) and preschoolers with severe TBI had IQ scores of 85.8 (n=13); middle schoolers with mild TBI had IQ scores of 93.9 (n=10), whereas middle schoolers with moderate TBI had IQ scores of 93.5 (n=21), and middle schoolers with severe TBI had IQ scores of 86.1 (n=14); finally, children with mild TBI in late childhood had a mean FSIQ of 107.3 (n=17), while children with moderate TBI had IQs of 99.5 in late childhood (n=15), and children with severe TBI in late childhood had FSIQs of 94.7 (Crowe et al, 2012; table 3). This shows that age of acquisition and severity influence IQ scores (along with their subtests), and that brain maturity matters for maintaining average intelligence post-TBI. Königs et al (2016) also show the same trend; the outlook is better for children with mild TBI, while children faired far worse with severe TBI compared to mild when compared to adults (also seen in Crowe et al, 2012).
People who got into motor vehicle accidents suffered a loss of 14 IQ points (n=33) after being tested 20 months postinjury (Parker and Rosenblum, 1996). The WAIS-IV Technical and Interpretive Manual also shows a similar loss of 16 points (pg 111-112), however, the 22 subjects were tested within 6 to 18 months within acquiring their TBI, with no indication of whether or not a follow-up was done. IQ will recover postinjury, but education, brain size, age, and severity all are factors that contribute to how many IQ points will be gained. However, adults who suffer mild, moderate, and severe TBIs have IQs in the normal range. TBI severity also had a stronger effect on children aged 2 to 7 years of age at injury, with white matter volume and results on the Glasgow Coma Scale (which is used to assess consciousness after a TBI) were related to the severity of the injury (Levin, 2012).
TBI can occur with a minimal hit to IQ (Bigler, 1995; Wood and Rutterford, 2006; Crowe et al, 2012). IQs can still be in the average range at a wide range of ages/severities, however the older one is when they suffer a TBI, the more likely it is that they will incur little to no loss in IQ (depending on the severity, and even then they are still in the average range). It is interesting to note that TBI may have been a selective factor in our brain evolution over the past 3 million years from australopithecines to erectus to Neanderthals to us. However, the fact that people with severe TBI can have IQ scores in the normal range shows that the brain size/IQ correlation isn’t all it’s cracked up to be.
Barbey AK, Colom R, Paul E, Forbes C, Krueger F, Goldman D, et al. (2014) Preservation of General Intelligence following Traumatic Brain Injury: Contributions of the Met66 Brain-Derived Neurotrophic Factor. PLoS ONE 9(2): e88733. https://doi.org/10.1371/journal.pone.0088733
Bigler, E. D. (1995). Brain morphology and intelligence. Developmental Neuropsychology,11(4), 377-403. doi:10.1080/87565649509540628
Crowe, L. M., Catroppa, C., Babl, F. E., Rosenfeld, J. V., & Anderson, V. (2012). Timing of Traumatic Brain Injury in Childhood and Intellectual Outcome. Journal of Pediatric Psychology,37(7), 745-754. doi:10.1093/jpepsy/jss070
Green, R. E., Melo, B., Christensen, B., Ngo, L., Monette, G., & Bradbury, C. (2008). Measuring premorbid IQ in traumatic brain injury: An examination of the validity of the Wechsler Test of Adult Reading (WTAR). Journal of Clinical and Experimental Neuropsychology,30(2), 163-172. doi:10.1080/13803390701300524
Königs, M., Engenhorst, P. J., & Oosterlaan, J. (2016). Intelligence after traumatic brain injury: meta-analysis of outcomes and prognosis. European Journal of Neurology,23(1), 21-29. doi:10.1111/ene.12719
Levin, H. S. (2012). Long-term Intellectual Outcome of Traumatic Brain Injury in Children: Limits to Neuroplasticity of the Young Brain? Pediatrics, 129(2), e494–e495. http://doi.org/10.1542/peds.2011-3403
Parker, R. S., & Rosenblum, A. (1996). IQ loss and emotional dysfunctions after mild head injury incurred in a motor vehicle accident. Journal of Clinical Psychology,52(1), 32-43. doi:10.1002/(sici)1097-4679(199601)52:1<32::aid-jclp5>3.3.co;2-1
Pietschnig, J., Penke, L., Wicherts, J. M., Zeiler, M., & Voracek, M. (n.d.). Meta-Analysis of Associations Between Human Brain Volume And Intelligence Differences: How Strong Are They and What Do They Mean? SSRN Electronic Journal. doi:10.2139/ssrn.2512128
Raichlen, D. A., & Polk, J. D. (2012). Linking brains and brawn: exercise and the evolution of human neurobiology. Proceedings of the Royal Society B: Biological Sciences,280(1750), 20122250-20122250. doi:10.1098/rspb.2012.2250
Rushton, J. P., & Ankney, C. D. (2009). Whole Brain Size and General Mental Ability: A Review. The International Journal of Neuroscience, 119(5), 692–732. http://doi.org/10.1080/00207450802325843
Shively, S., Scher, A. I., Perl, D. P., & Diaz-Arrastia, R. (2012). Dementia Resulting From Traumatic Brain Injury: What Is the Pathology? Archives of Neurology, 69(10), 1245–1251. http://doi.org/10.1001/archneurol.2011.3747
Skoyles R. J. (1999) HUMAN EVOLUTION EXPANDED BRAINS TO INCREASE EXPERTISE CAPACITY, NOT IQ. Psycoloquy: 10(002) brain expertise
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society,8(03), 448-460. doi:10.1017/s1355617702813248
Wood, R. L., & Rutterford, N. A. (2006). Long‐term effect of head trauma on intellectual abilities: a 16‐year outcome study. Journal of Neurology, Neurosurgery, and Psychiatry, 77(10), 1180–1184. http://doi.org/10.1136/jnnp.2006.091553
Much has been written in the scientific literature on our brain size increase, which has doubled in the timespan of about 3 million years. It is assumed that our brains became bigger so we could become smarter. However, recent data shows that the amount of blood our brains use dramatically increased over the course of human evolution—the amount of blood our brains use increased some 600 percent over the course of human evolution, substantially more than our brain size increase (350 percent).
Seymour, Bosiocic, and Snelling (2016) showed that while there was a 3.5-fold increase in brain size while there was a 6-fold increase in total cerebral blood flow rate. This is due to increased interneuron connectivity, synaptic activity and cognitive function which all depend on the cerebral metabolic rate. This is yet another reason why cooking was so important during our brain evolution. If the brain has a higher metabolic rate, only a high-quality diet will allow it to function. This can only occur if and only if there is a high-quality diet in the first place.
The metabolic intensity of cerebral tissue in our lineage could only be satisfied by a high-quality cooked diet. Clearly, the evolution of the human brain most always goes back to nutrition and the quality of the human diet. Without erectus’ control of fire around 1.5 mya, our brains wouldn’t have been able to grow this big, nor would we have the cerebral blood flow we eventually had. The below picture is figure 1 from the paper. The left slide is Australopithecus Afarensis, the middle is a Neanderthal, and the right is archaic Homo Sapiens.
They measured the lumen radius of the internal carotid arteries and were able to deduce that there were large changes in cerebral blood flow in hominin evolution due to the increasing size of the ICAs. Arterial size, blood flow rate and metabolic rate are tightly related. So if there are bigger ICAs, then that hominin had more blood flow to feed a bigger brain. This is clear evidence that as our brain size increased that we needed more blood to feed our growing brain.
Kilroy et al (2013) hypothesize that due to widespread anatomical differences in the anterior cingulate cortex (ACC), PFC and insula and subcortical cortices, those regions must be a “central node of the brain’s network underlying individual differences in intellectual development throughout childhood and adolescence.” Cerebral blood flow in the subgenual/ACC correlates the highest with IQ. They also showed that it’s possible to delineate “where CBF is modulated by IQ.” More blood flow in these regions means a higher IQ. Since the ICAs grew larger over the course of hominin brain evolution to increase intelligence, it’s no surprise that more blood flow to certain parts of the brain is related to higher intelligence in children and adolescents.
Even CBF at rest is correlated with higher intelligence and creativity (Takeuchi et al, 2011). They showed that gray and white matter in the brain is correlated with CBF at rest and significantly and positively with psychometric intelligence. Further, the Raven’s Advanced Progressive Matrices (RAPM) and scores on the creativity test that were administered to the cohort correlated positively with white matter and cerebral blood flow. They also noticed that there was an association between negative mood and increased cerebral blood flow. Grey and white matter CBF at rest were both correlated with the RAPM and the creativity test administered. This is yet more evidence that blood flow to certain parts of the brain dictates intelligence (and most likely individual differences in intelligence as well).
The more vampiric a brain is (especially in certain regions), the higher one’s intelligence will be, on average. By looking back at the fossil skulls of our hominin ancestors and the radius of the ICA, we can infer that as hominin evolution ‘progressed’ through time, the ICA radius increased which meant increased blood flow to the brain. This is directly related to brain metabolism and could only be afforded with a high-quality diet which started with the advent of tool-making and the use of fire to cook by erectus. Cerebral blood flood in the anterior cingulate cortex is significantly and positively correlated with IQ. CBF at rest is also correlated with IQ and certain regions of the brain. This shows that a brain with a higher metabolic rate will be, on average, more intelligent than a brain that has a lower one. The current data on intelligence and CBF points to increased blood flow in certain parts of the brain is related to higher levels of intelligence. This does make sense, as our blood flow to the brain increased by 600 percent over the course of human evolution. So, in a way, we can say that along with our brain size increasing for expertise capacity (which was most definitely needed over the course of hominin evolution) (Skoyles, 2009) along with more cerebral blood flow due to larger arteries and a higher metabolic rate.
This does make sense, as our blood flow to the brain increased by 600 percent over the course of human evolution. So, in a way, we can say that along with our brain size increasing for expertise capacity (which was most definitely needed over the course of hominin evolution) (Skoyles, 2009) along with the need for more blood to the brain to increase intelligence (as blood will also shuttle oxygen to the brain). This is yet another reason why our not-so-special brains are remarkable compared to the rest of the animal kingdom—the one variable that gives us our cognitive superiority over other animals is the ability to cook and use fire. A lot of our physiologic, anatomic and brain evolution can be explained simply as: no cooking, fire, and meat, no big brains (and as a consequence, everything you see around you today would not be here), and the only thing that can drive such a metabolically demanding brain is cooking and eating high-quality foods. The outstanding number of neurons crowded into our cerebral cortex along with much blood our vampiric brain guzzles explains our cognitive superiority over other animals.
Kilroy, E., Yan, L., Wang, D. J., Dapretto, M., Mendez, M. F., Liu, C. Y., & Kim, Y. C. (2011). Relationships between Cerebral Blood Flow and IQ in Typically Developing Children and Adolescents. Journal of Cognitive Science,12(2), 151-170. doi:10.17791/jcs.2011.12.2.151
Seymour, R. S., Bosiocic, V., & Snelling, E. P. (2016). Fossil skulls reveal that blood flow rate to the brain increased faster than brain volume during human evolution. Royal Society Open Science,3(8), 160305. doi:10.1098/rsos.160305
Dr. John R. Skoyles (1999) HUMAN EVOLUTION EXPANDED BRAINS TO INCREASE EXPERTISE CAPACITY, NOT IQ. Psycoloquy: 10(002)
Takeuchi, H., Taki, Y., Hashizume, H., Sassa, Y., Nagase, T., Nouchi, R., & Kawashima, R. (2011). Cerebral Blood Flow during Rest Associates with General Intelligence and Creativity. PLoS ONE,6(9). doi:10.1371/journal.pone.0025532
With all of my recent articles on neurons and brain size, I’m now asking the following question: do neurons differ by race? The races of man differ on most all other variables, why not this one?
As we would have it, there are racial differences in total brain neurons.In 1970, an anti-hereditarian (Tobias) estimated the number of “excess neurons” available to different populations for processing bodily information, which Rushton (1988; 1997: 114) averaged to find: 8,550 for blacks, 8,660 for whites and 8,900 for Asians (in millions of excess neurons). A difference of 100-200 million neurons would be enough to explain away racial differences in achievement, for one. Two, these differences could also explain differences in intelligence. Rushton (1997: 133) writes:
This means that on this estimate, Mongoloids, who average 1,364 cm3 have 13.767 billion cortical neurons (13.767 x 109 ). Caucasoids who average 1,347 cm3 have 13.665 billion such neurons, 102 million less than Mongoloids. Negroids who average 1,267 cm3 , have 13.185 billion cerebral neurons, 582 million less than Mongoloids and 480 million less than Caucasoids.
Of course, Rushton’s citation of Jerison, I will leave alone now that we know that encephilazation quotient has problems. Rushton (1997: 133) writes:
The half-billion neuron difference between Mongoloids and Negroids are probably all “excess neurons” because, as mentioned, Mongoloids are often shorter in height and lighter in weight than Negroids. The Mongoloid-Negroid difference in brain size across so many estimation procedures is striking
Of course, small differences in brain size would translate to differences differences neuronal count (in the hundreds of millions), which would then affect intelligence.
The ability to plan for the future, a significant function of prefrontal regions of the cortex, may be key indeed. According to the best definition I have come across so far, put forward by MIT physicist Alex Wissner-Gross, intelligence is the ability to make decisions that maximize future freedom of action—that is, decisions that keep most doors open for the future. (Herculano-Houzel, 2016: 122-123)
You can see the difference in behavior and action in the races; how one race has the ability to make decisions to maximize future ability of action—and those peoples with a smaller prefrontal cortex won’t have this ability (or it will be greatly hampered due to its small size and amount of neurons it has).
With a smaller, less developed frontal lobe and less overall neurons in it than a brain belonging to a European or Asian, this may then account for overall racial differences in intelligence. The few hundred million difference in neurons may be the missing piece to the puzzle here.Neurons transmit information to other nerves and muscle cells. Neurons have cell bodies, axons and dendrites. The more neurons (that’s also packed into a smaller brain, neuron packing density) in the brain, the better connectivity you have between different areas of the brain, allowing for fast reaction times (Asians beat whites who beat blacks, Rushton and Jensen, 2005: 240).
Remember how I said that the brain uses a certain amount of watts; well I’d assume that the different races would use differing amount of power for their brain due to differing number of neurons in them. Their brain is not as metabolically expensive. Larger brains are more intelligent than smaller brains ONLY BECAUSE there is a higher chance for there to be more neurons in the larger brain than the smaller one. With the average cranial capacity (blacks: 1267 cc, 13,185 million neurons; whites: 1347 cc, 13,665 million neurons, and Asians: 1,364, 13,767 million neurons). (Rushton and Jensen, 2005: 265, table 3) So as you can see, these differences are enough to account for racial differences in achievement.
A bigger brain would mean, more likely, more neurons which would then be able to power the brain and the body more efficiently. The more neurons one has, the more likely it it that they are intelligent as they have more neuronal pathways. The average cranial capcities of the races show that there are neuronal differences between them, which these neuronal differences then are the cause for racial differences, with the brain size itself being only a proxy, not an actual indicator of intelligence. The brain size doesn’t matter as much as the amount of neurons in the brain.
A difference in the brain of 100 grams is enough to account for 550 million cortical neurons (!!) (Jensen, 1998b: 438). But that ignores sex differences and neuronal density. However, I’d assume that there will be at least small differences in neuron count, especially from Rushton’s data from Race, Evolution and Behavior. Jensen (1998) also writes on page 439:
I have not found any investigation of racial differences in neuron density that, as in the case of sex differences, would offset the racial difference in brain weight or volume.
So neuronal density by brain weight is a great proxy.
Racial differences in intelligence don’t come down to brain size; they come down to total neuron amount in the brain; differences in size in certain parts of the brain critical to intelligence and amount of neurons in those critical portions of the brain. I’ve yet to come across a source talking about the different number of neurons in the brain by race, but when I do I will update this article. From what we know, we can make the assumption that blacks have less packing density as well as a smaller number of neurons in their PFC and cerebral cortex. Psychopathy is associated with abnormalities in the PFC; maybe, along with less intelligence, blacks would be more likely to be psychopathic? This also echoes what Richard Lynn says about Race and Psychopathic Personality:
There is a difference between blacks and whites—analogous to the difference in intelligence—in psychopathic personality considered as a personality trait. Both psychopathic personality and intelligence are bell curves with different means and distributions among blacks and whites. For intelligence, the mean and distribution are both lower among blacks. For psychopathic personality, the mean and distribution are higher among blacks. The effect of this is that there are more black psychopaths and more psychopathic behavior among blacks.
Neuronal differences and size of the PFC more than account for differences in psychopathy rates as well as differences in intelligence and scholastic achievement. This could, in part, explain the black-white IQ gap. Since the total number of neurons in the brain dictates, theoretically speaking, how well an organism can process information, and blacks have a smaller PFC (related to future time preference); and since blacks have less cortical neurons than Whites or Asians, this is one large reason why black are less intelligent, on average, than the other races of Man.
Tl;dr: Two of our most recent ancestors have IQs, theoretically speaking, near ours. This suggests that there were beneficial effects of cultural accumulation and transference. This also lends credence to Gould’s work in Full House, where he writes that “cultural change can vastly outstrip the maximal rate of Darwinian evolution.” Brain size may not have increased for IQ, but for expertise capacity. This is seen in the !Kung, gamblers at the horse track, chess players and musicians. There is both theoretical and empirical evidence that expertise needs large amounts of brain to store “and actively process its informational chunks.” These two studies in combination, in my opinion, shows how important the advent of ‘culture’ was for humans. Tool use got passed down as it gave us fitness advantages, then when Erectus discovered fire, that’s when the game changed. One of the first instances of cultural transference then happened, which set the stage for the rest of human evolution. Looking at it from this perspective, the importance of cultural inheritance and transference cannot be understated. It was due to that ‘behavioral change’ that allowed us all of the advantages we have over our ancestors; we have them to thank for everything we see around us today. For if not for them passing down the beginnings of culture that increased our fitness, individuals would have had to learn things for themselves which would decrease fitness. It’s due to this transference that we are here today.
My recent articles have consisted of what caused our big brains, whether or not there is ‘progress’ in hominin brain evolution, why humans are cognitively superior to other animals, and that the human brain is a linearly scaled-up primate brain (Herculano-Houzel, 2009). Knowing what we know about the human brain and the cellular scaling rules for primates (Herculano-Houzel, 2007), we can infer the amount of neurons that our ancestors Erectus, Heidelbergensis, and Neanderthals had. How intelligent were they? Does the EQ predict intelligence better for non-human primates, or does overall brain weight matter most? If our immediate ancestors had the same amount of neurons as we do, what does that mean for our supposed cognitive superiority over them?
How many neurons did our ancestors have, and what did it mean for their intelligence levels? Herculano-Houzel (2013) estimated the amount of neurons that our ancestors had: Afarensis (35 b), Paranthropus (33 b), to close to 50-60 billion neurons in our species Homo from rudolfensis to antecessor, H. Erectus (62 b), Heidelbergensis (76 b), and Neanderthals (85 b), which is within the range for modern Sapiens. From our knowledge of the average human’s IQ (say, 100) and the total number of neurons the brain has (86 billion), what can we say about the IQs of Erectus, Afarensis, Paranthropus, rudolfensis, antecessor, Heidelbergensis, and Neanderthals?
(chart from Herculano-Houzel and Kaas, 2011)
Since Afarensis had about 35 billion neurons we can infer that his IQ was about 40. Paranthropus with about 33 billion neurons had an IQ of about 38. Homo habilis had 40 billion neurons, equating to IQ 46. Erectus with 62 billion neurons comes in at IQ 72., which differs with PP’s estimate by 22 points. (You can see the brain size increase [more on that later] and total neuron increase between habilis and erectus, with an almost 20 IQ point difference. The cause of this is the advent of cooking and the tool-use by habilis, named ‘Handy Man’.) Now we come to a problem. The total number of neurons in the brain of Heidelbergensis, Neanderthals, and humans are about the same.
Heidelbergensis had 76 billion neurons which equates to IQ 88. Neanderthals had about 85 billion neurons, equating to IQ 99. Our IQs are 100 with 86 billion neurons. As you can see, the leap from habilis (who may have eaten meat) to Erectus, a jump of 22 billion neurons and along with it 22. (The rise of bipedalism and tool use, fire, cooking, and meat eating led to the huge increase in neurons in our species Homo.) Then from Erectus to Heidelbergensis was a jump of 14 billion neurons along with an increase of 16 IQ points, then from Heidelbergensis to Neanderthal is an increase of 9 billion neurons, increasing IQ about 11 points. Neanderthals to us is about 1 billion neurons showing a difference of 1 IQ point.
This leads us to a troubling question: did Neanderthals and Hheidelbergensis at least have the capacity to become as intelligent as us? Herculano-Houzel and Kaas (2011) write:
Given that cognitive abilities of non-human primates are directly correlated with absolute brain size [Deaner et al., 2007], and hence necessarily to the total number of neurons in the brain, it is interesting to consider that enlarged brain size, consequence of an increased number of neurons in the brain, may itself have contributed to shedding a dependence on body size for successful competition for resources and mates, besides contributing with larger cognitive abilities towards the success of our species [Herculano-Houzel, 2009]. In this regard, it is tempting to speculate on our prediction that the modern range of number of neurons observed in the human brain [Azevedo et al., 2009] was already found in H. heidelbergensis and H. neanderthalensis, raising the intriguing possibility that they had similar cognitive potential to our species. Compared to their societies, our outstanding accomplishments as individuals, as groups, and as a species, in this scenario, would be witnesses of the beneficial effects of cultural accumulation and transmission over the ages.
If true, this is a huge finding as it echoes what Stephen Jay Gould wrote 21 years ago in his book Full House, as I documented in my article Stephen Jay Gould and Anti-Hereditarianism:
“The most impressive contrast between natural evolution and cultural evolution lies embedded in the major fact of our history. We have no evidence that the modal form of human bodies or brains has changed at all in the past 100,000 years—a standard phenomenon of stasis for successful and widespread species, and not (as popularly misconceived) an odd exception to an expectation of continuous and progressive change. The Cro-Magnon people who painted the caves of the Lascaux and Altamira some fifteen thousand years ago are us—and one look at the incredible richness and beauty of this work convinces us, in the most immediate and visceral way, that Picasso held no edge in mental sophistication over these ancestors with identical brains. And yet, fifteen thousand years ago no human social grouping had produced anything that would conform with our standard definition of civilization. No society had yet invented agriculture; none had built permanent cities. Everything that we have accomplished in the unmeasurable geological moment of the last ten thousand years—from the origin of agriculture to the Sears building in Chicago, the entire panoply of human civilization for better or for worse—has been built upon the capacities of an unaltered brain. Clearly, cultural change can vastly outstrip the maximal rate of natural Darwinian evolution.” (Gould, 1996: 220)
But human cultural change is an entirely distinct process operating under radically different principals that do allow for the strong possibility of a driven trend for what we may legitamately call “progress” (at least in a technological sense, whether or not the changes ultimately do us any good in a practical or moral way). In this sense, I deeply regret that common usage refers to the history of our artifacts and social orginizations as “cultural evolution.” Using the same term—evolution—for both natural and cultural history obfuscates far more than it enlightens. Of course, some aspects of the two phenomena must be similar, for all processes of genealogically constrained historical change must share some features in common. But the differences far outweigh the similarities in this case. Unfortunately, when we speak of “cultural evolution,” we unwittingly imply that this process shares essential similarity with the phenomenon most widely described by the same name—natural, or Darwinian, change. The common designation of “evolution” then leads to one of the most frequent and portentious errors in our analysis of human life and history—the overly reductionist assumption that the Darwinian natural paradigm will fully encompass our social and technological history as well. I do wish that the term “cultural evolution” would drop from use. Why not speak of something more neutral and descriptive—“cultural change,” for example? (Gould, 1996: 219-220)
The implications of the findings of the neuron count in Heidelbergensis and Neanderthals, if true, is a huge finding. Because it implies, as Herculano-Houzel and Kaas say, that “our outstanding accomplishments as individuals, as groups, and as a species … would be witnesses of the beneficial effects of cultural accumulation and transmission through the ages.” I’ve been thinking about this one sentence all week, racking my brain on what it could mean, while thinking about alternate possibilities.
I came across a paper by Dr. John Skoyles titled Human Evolution Expanded Brains to Increase Expertise, Not IQ (saying that around this part of the internet is the equivalent of heresy), in which he reviews studies of people living with microcephaly, showing that a lot of people who have the average brain size of Erectus have average, and even sometimes above average/genius IQs. Yes, microcephaly is correlated with retardation and low IQ, but a significant percentage of individuals inflicted with the disease showed average IQ scores (7 percent overall, 22 percent in 1 subgroup) (Skoyles, 1999). As I’ve documented in the past few days, Erectus was the hominin that learned how to control fire and kicked off the huge spurt in our brain growth. When this increase occurred, brain growth still had to happen outside of the brain, making the baby a fetus for one year after it is born. To achieve its larger brain size, the fetus must have a larger brain before birth, with it increasing postnatally.
The solution to this was to widen the hips of women. This would allow the birth canal to be ‘just right’ in terms of size so the baby could just barely make the squeeze. Physiological differences like this are why there are such huge sex differences in sports. Skoyles (1999) writes:
Research of three kinds suggests that small brained people can have normal IQs: (i) a recent MRI survey on brain size (Giedd et al. 1996), (ii) data on individuals born with microcephaly (head circumference 2 SD below the mean; Dorman, 1991); and (iii) data on early hemispherectomy (the removal of a dysfunctional cerebral hemisphere; Smith & Sugar, 1975; Griffith & Davidson, 1966; Vining et al., 1993).
He also writes that in a sample of 1006 school children, 2 percent (19 students) were found to be microcephalic. Of the 19 microcephalics, only 12 were in districts that did intelligence testing. Of the 12, 7 of them had an average IQ, with one having an IQ of 129. Skoyler even cites a study where a woman’s cranial capacity may have possibly been 760 cc (one the lower end of the range of Erectus brains)!! Her employment was described as ‘semi-skilled’, which Skoyler notes is normal for her ability level. Skoyler also says that Medline shows 21 other studies showing that microcephalic individuals have average IQs.
There is also one incidence of a man having a smaller brain than erectus while having a normal intelligence level, showing no peculiarities or mental retardation. Upon his death, his brain was weighed and they discovered that it weighed 624 grams!
Now, of course, the studies that Skoyler brings up are outliers, but they raise very interesting questions when you think about the supposed link with IQ and brain size. More interestingly, even sudden brain damage will leave a small change, if any, in IQ (Bigler, 1995). Finally, the .35 brain size-IQ correlation needs to be talked about. Let’s be generous and say the correlation is .5, 74 percent of the variance in IQ would still be unexplained (Skoyler, 1999: 8).
Skoyler then says that IQ tests “show very moderate to zero correlations with people’s ability to acquire expertise (Ackerman, 1996; Ceci & Liker, 1986; Doll & Mayr, 1987; Ericsson & Lehmann, 1996; Shuter-Dyson & Gabriel, 1981).” So he says that one’s capacity for expertise isn’t necessarily predicated on their IQ as measured by IQ tests. Skoyler writes:
Hence, whereas nonexpert players see only chess pieces, chess masters see possible future moves and potential strategies. Such in depth perception arises from acquiring and being able to actively use a larger numbers of informational “chunks” in analyzing a problem. The number of such chunks in chess masters has been estimated at 50,000 (Gobet & Simon, 1996). Such information processing chunks take many years to acquire. After reviewing performance in sport, medicine, chess and music, Ericsson and Lehmann (1996) propose that before people can show expertise in any domain they must have performed several hours of practice a day for a minimum of 10-years
So, this ‘expertise capacity’ seems to be a trained—not inherited—trait. He then cites a study on people who’ve spent decades at the daily race track betting on horse races. Cece and Liker (1986) measured the IQs of 12 of the experts, and found that they ranged between IQ 81 and 128 (“four were between 80 and 90, three between 90 and 100, two between 100 and 110 and only three above 120 Table 6”). The authors write: “whatever it is that an IQ test measures, it is not the ability to engage in cognitively complex forms of multivariate reasoning.” Moreover, Skoyler writes, expertise in chess (see Erickson, 2000) and music (see Deutsch, 1982: 404-405) “correlates poorly, or not at all with IQ.”
Now that we know that the capacity to develop expertise isn’t needed in the modern world, what did it mean for our hunter-gatherer ancestors? Looking at some of the few hunter-gatherer tribes left today, we can make some inferences.
The !Kung bushmen use in-depth expert knowledge and reasoning. Just by looking at a few tracks in the dirt, a bushman can infer whether the animal that made the track is sick, whether it was alone, its age and sex. They are able to do this by reading the shape and depth of the track in the dirt. Such skill, obviously, is learned, and those who didn’t have the capacity for expertise would have died out. Further, expertise in hunting is more important than physical ability, with the best hunters being over the age of 39 and not those in their 20s. This can further be seen when the young men go out for hunting. The young men do the physical work while the elder reads tracks, a learned ability.
This, Skoyler writes, suggests that those who had the highest capacity for expertise would have had the best chance for survival. Expertise in hunting is not the only thing that we need expertise for, obviously. The skill of ‘expertise’ translates to most all facets of human life. And over time, the advantages conferred by success with these activities “would result in the natural selection of brains with increased capacity for expertise.” So, even possibly, the success of our expertise could have selected for bigger brains which would have further increased the capacity for our expertise.
Since expertise is linked to the number of brain chunks that a brain can “hold and actively process”, that capacity for expertise “may be related to the number of cortical columns able to specialise neural networks in representing and processing them, and through this to cerebral mass Jerison (1991).” And, in brain scans of expert violinists, they have two to three times as much of their cortical area devoted to their left fingers as nonviolinists. ” This suggests that a strong connection should exist between the capacity for acquiring expertise skills and brain mass.”
I’m, of course, not denying the usefulness of IQ tests. What I’m saying, is that IQ tests don’t test a person’s capacity to learn a skill and become an expert in something. IQ tests, as shown, do not measure expertise capacity. IQ tests, then, don’t test for what was central to our evolution as hominins: expertise capacity. Of course, it’s not only expertise in hunting that led to the selection for bigger brains, and along with it expertise capacity. Obviously, this would hold for other things in our evolution that we can become experts in, from scavenging, to gathering, to language, social relationships, tool-making, and passing on useful skills that would infer an increase in fitness.
IQs for hominins are as follows: Paranthropus: IQ 38 (33 billion neurons); Afarensis: IQ 40 (35 billion neurons); Habilis: IQ 46 (40 billion neurons); Erectus: IQ 72 (62 billion neurons); Heidelbergensis: IQ 88 (76 billion neurons); Neanderthals: IQ 99 (85 billion neurons) and Sapiens: IQ 100 (85 billion neurons). So if Heidelbergensis and Neanderthals had IQs around ours (theoretically speaking), and Erectus had an IQ around modern-day Africans today, what explains our achievements over our hominin ancestors if we have around the same IQs?
Lamarckian cultural inheritance. If you think about when brain size began to increase, it was around the time that bipedalism occurred in the fossil record, along with tool use, fire, cooking, and meat eating. I’m suggesting here today that the beginnings of cultural transference happened with Afaraensis, Habilis, and Erectus. Passing down culture (useful traits for survival back then) would have been paramount in hominin survival. One wouldn’t have to learn how to do things on their own, and could learn from and elder the crucial survival skills they needed. This would have selected for a bigger brain due to the need for a higher expertise capacity, as with a bigger brain there is more room for cortical columns and neurons which would better facilitate expertise in that hominin.
I’m still thinking about what this all means, so I haven’t taken a side on this yet. This is an extremely interesting look into hominin brain size evolution, which shows that big brains didn’t evolve for IQ, but to increase expertise capacity. Though there is an extremely strong possibility that we gained over 20 billion neurons from Erectus due to his cooking, which then capped out our intelligence in our lineage. That would then mean that Neanderthals and Heidelbergensis would have had the capacity for the same IQ as us. One thing I can think of that set us apart 70 kya was the advent of art. That was a new way of transferring information from our hugely metabolically expensive neurons. This was also, yet another way of cultural transference. But what this means in terms of Neanderthal and Heidelbergensis IQ and what it means for our accomplishments since them is another story, which I will return to in the future.
The past few articles I have written touched on the fact that the human brain isn’t special and is just a scaled-up primate brain, bipedalism, tools, fire, cooking and meat eating had the largest effect on hominin brain evolution, and that, despite seeing a so-called ‘upward trend’ in the evolution of primate brain size, the reverse was occurring. So what makes us cognitively superior to other animals?
The most oft-cited reason why humans are cognitively superior to other animals is that we have the largest EQ compared to other animals. Ours is 7.5, meaning that we have a brain that’s 7.5 times larger than a mammal for our size but only 3.4 times as larger than expected for an anthropoid primate of its body mass (Azevedo et al, 2009). However, in stark contrast to the view of the people who view EQ as the reason why we are cognitively superior to other animals, what separates us in terms of cognitive ability is the difference in cortical neurons compared to other primates.
We humans have the most cortical neurons in our cerebral and prefrontal cortexes, relatively high neuron packing density (NPD), and much more cortical neurons of mammals of the same brain size (Roth and Dicke, 2012). Differences in intelligence across primate taxa best correlate with differences in number of cortical neurons, information processing speed, and synapses. Though, the human brain stands out having a “large cortical volume with a relatively NPD, high conduction velocity and high cortical parcellation.” This is why we are much more intelligent than other primates, due to the amount of cortical neurons we have as well as higher neuron packing density (keep this in mind for later). Encephalization quotient doesn’t explain intelligence differences within species, hence there being a problem with the use of encephalization to as the reason for human cognitive superiority, our Human Advantage, if you will.
Harry Jerison, the originator of the encephalization quotient, came to the conclusion that “human evolution … had been all about an advancement of encephalization quotients culminating in man.” (Herculano-Houzel, 2016: 15) What a conclusion. Just because EQ increased throughout hominin evolution, that means that it was all an advancement of EQs culminating to man. That’s circular logic.
Moreover, the “circular assumption” that higher EQ mean superior cognitive abilities in humans wasn’t founded on “tried-and-true correlations with actual measures of cognitive capacity.” (Herculano-Houzel, 2016: 15)
In second place on the EQ chart is the capuchin monkey coming in with an EQ of 2, which is more than double that of great apes who fall way below 1. That would imply that capuchin monkeys are more intelligent than great apes and outsmart great apes, right? Wrong. Great apes are. Total brain size predicts cognitive abilities in non-human primates better than EQ (Deaner et al, 2007).
Great apes significantly outperform other lineages. (Deaner, Schaik, and Johnson, 2006) Yet they have smaller EQs compared to other less intelligent primates. This is one of the largest problems with the EQ: total brain size is a better predictor of cognitive ability in non-human primates (Herculano-Houzel, 2011). She proposes that the absolute number of neurons, irrespective of brain size or body weight, is a better predictor of cognitive ability than is EQ.
Another problem with the EQ is that it assumes that all brains are made the same, and they aren’t. They scale differently between species. That’s one pretty huge flaw. Scaling is not the same across species, only within certain species. This one fatal flaw in EQ comparing different species of humans is why there is a problem with EQ in assessing cognitive abilities and why total brain size predicts cognitive abilities in non-human primates better than EQ.
Absolute brain size is a much better indicator of intelligence than the encephalization quotient.
So what exactly explains human cognitive superiority over other animals if the most often-used metric—the EQ—is flawed? An enlarged frontal cortex? No, the prefrontal areas in a human brain occupy 29 percent of the mass of the cerebral cortex. Moreover, the prefrontal cortex of humans, bonobos, chimpanzees, gorillas, and orangutans occupies the same 35-37 percent of all cortical volume (Semendeferei et al, 2002). (See also Herculano-Houzel, 2016: 119 and Gorillas Agree: Human Frontal Cortex is Nothing Special). Just because our frontal cortexes are all the same size, doesn’t mean that we don’t have a higher neuron packing density (NPD) than other primates. However, the human brain has the amount of neurons expected for its grey matter volume and total number of neurons remaining in the cerebral cortex; it has the white matter volume expected for amount of neurons; and the white matter volume and number of neurons expected for the number and volume of neurons in the “nonprefrontal subcortical white matter” (Herculano-Houzel, Watson, and Paxinos, 2013). The human prefrontal cortex is no larger than it ‘should’ be.
However, there seems to be a problem with Herculano-Houzel’s (2011) theory that absolute number of neurons predicts cognitive superiority (Mortenson et al, 2014). The long-finned pilot whale has 37,200,000 neurons in its cerebral cortex, more than double that of humans (16 billion). Does this call into question Herculano-Houzel’s (2011) theory on absolute number of neurons being the best case of human cognitive superiority over other animals?
In short, no. Neuron density is higher in humans than in the pilot whale. We have more neurons packed into our cerebral cortex. Their higher cell count is due only to their larger brains. And where it matters: pilot whales have a higher than expected amount of neocortical neurons relative to body weight, although not higher than humans. Herculano-Houzel’s (2011) theory is still in play here. They have big brains and in turn large amounts of glial cells to counter heat loss. So even then, this doesn’t counter Herculano-Houzel’s theory that the absolute amount of neurons dictates overall cognitive superiority.
Moreover, there is the same amount of cortical neurons in mice brains and human brains, with both mice and humans housing 8 percent of their total neurons in the prefrontal cortex. So what accounts for human cognitive superiority in humans compared to other primates? Most likely, the connectivity of the brain.
The connectivity in the brain of humans is not different from other species. The density of gray matter within species is fairly constant within mammalian species (Herculano-Houzel, 2016: 122). If true, then human prefrontal cortex, being nowhere near the largest, wouldn’t have the most synapses in our prefrontal cortex or anywhere else in the brain, and thus these wouldn’t be the largest. So, what does explain the cognitive superiority of humans over other animals in the animal kingdom?
All though all mammals use 8 percent of their total neurons in their prefrontal cortex, there is a differing distribution due to the amount of total neurons in each brain (remember, all brains aren’t made the same. It doesn’t hold for humans, and it especially doesn’t hold across phyla). We have 1.3 billion cortical neurons in our prefrontal cortex, baboons have 230 million, the macaque has 137 million and the marmoset has 20 million (Herculano-Houzel, 2016: 122). Prefrontal neurons are able to add complexity and flexibility, among other associative functions, to behavior while making planning for the future possible. All of these capabilities would increase with the more neurons a prefrontal cortex has (remember back to my article that the seat of intelligence (g) is the prefrontal cortex). So this seems to confirm the past studies showing the seat of intelligence to be the frontal cortex, due to the large amount of cortical neurons it has.
Herculano-Houzel writes the best definition of intelligence she’s ever heard, from MIT physicist Alex Wissner-Gross, which I believe is a great definition of intelligence:
The ability to plan for the future, a significant function of prefrontal regions of the cortex, may be key indeed. According to the best definition I have come across so far, put forward by MIT physicist Alex Wissner-Gross, intelligence is the ability to make decisions that maximize future freedom of action—that is, decisions that keep most doors open for the future. (Herculano-Houzel, 2016: 122-123)
All of the above are the direct result of more neurons in our frontal cortexes compared to other primates, which is why she finds it is the best definition of intelligence she’s ever heard.
Our ‘Human Advantage’ over other species comes down to the number of cortical neurons we have in our prefrontal cortex compared to other primates as well as the most neurons along with the highest NPD in the animal kingdom—which will be matched by no animal. The encephalization quotient has a lot of problems, with overall brain weight being a much better predictor of intelligence (Herculano-Houzel, 2011). Human cognitive superiority comes down to the total amount of neurons in our frontal cortex (1.3 billion neurons—where we will not be beaten) and our cerebral cortexes (16 billion neurons [long-finned pilot whales beat us out by more than double the amount, but we have more neurons packed into our cerebral cortex signifying our higher cognitive abilities). Within primates, total brain size predicts cognitive abilities better than EQ (Deaner et al, 2007).
Human cognitive superiority, contrary to popular belief, is not due to the EQ. It’s due to our NPD and amount of neurons in our frontal and cerebral cortexes that no other animal has–and we will not find another animal like this. This only would have been possible with the advent of bipedalism, tool-making, fire, cooking and meat eating. That’s what drives the evolution of brain size—and our evolution as a whole. Energy. Energy to reproduce, which then produce mutations which eventually coalesce new species.
Tl;dr: The ‘trend’ in the evolution of hominin brain size is only due to diet quality and abundance. If there is any scarcity of food or a decrease in nutritional quality, there will be a subsequent decrease in brain size, as seen with H. floresiensis. Brain size, contrary to popular belief, has been decreasing for the past 20,000 years and has accelerated in the past 10,000. This trend is noticed all over the world with multiple hypotheses put out to explain the phenomenon. Despite this, people still deny that a decrease is occurring. Is it? Yes, it is. It’s due to a decrease in diet quality along with higher population density. If the human diet were to decrease in quality and caloric amount, our brains—along with our bodies—would become smaller over time.
Is there progress in hominin brain evolution? Many people may say yes. Over the past 7 million years, the human brain has tripled in size with most of this change occurring within the past 2 million years. This perfectly coincides with the advent of bipedalism, tool-making, fire, cooking and meat eating. Knowing the causal mechanisms behind the increase in hominin (primate) brain size, is there ‘progress’ to brain size in hominin evolution?
Looking at the evolution of hominin brain size in the past 7 million years, one can rightfully make the case that there is an evolutionary trend with the brain size increase. I don’t deny there is an increase, but first, before one says there is ‘progress’ to this phenomenon, you must look at it from both sides.
Montgomeroy et al (2010) reconstructed the ‘ups and downs’ of primate brain size evolution, and of course, decreases in hominin brain size can’t be talked about without bringing up H. floresiensis and his small brain and body mass, which they discuss as well. They come to the conclusion that “brain expansion began early in primate evolution”, also showing that there have been brain size increases in all clades of primates. Humans only show a bigger increase in absolute mass, with rate of proportional change in mass and relative brain size “having greater episodes of expansion elsewhere on the primate phylogeny”. Decreases in brain size also occurred in all of the major primate clades studied, they conclude that “while selection has acted to enlarge primate brains, in some lineages this trend has been reversed.” The selection can only occur in the presence of adequate kcal, keeping everyone sated and nourished enough to provide for the family, ensuring a woman gets adequate kcal and nutrients during pregnancy and finally ensuring that the baby gets the proper amount of energy for growth during infancy and childhood.
Montgomery et al write:
The branch with the highest rate of change in absolute brain mass is the terminal human branch (140,000 mg/million years). However for rate of proportional change in absolute brain mass the human branch comes only fourth, below the branches between the last common ancestor of Macaques and other Papionini, and the last common ancestor of baboons, mangabeys and mandrills (48 to 49), the ancestral primate and ancestral haplorhine (38 to 39) and the branch between the last common ancestor of Cebinae, Aotinae and Callitrichidae, and the ancestral Cebinae (58 to 60). The rate of change in relative brain mass along the human branch (0.068/million years) is also exceeded by the branch between the last common ancestor of Alouatta, Ateles and Lagothrix with the last common ancestor of Ateles and Lagothrix (branch 55 to 56; 0.73), the branch connecting the last common ancestor of Cebinae, Aotinae and Callitrichidae, and the ancestral Cebinae (branch 58 to 60; 0.074/million years) and the branch connecting the last common ancestor of the Papionini with the last common ancestor of Papio, Mandrillus and Cercocebus (branch 48 to 49; 0.084). We therefore conclude that only in terms of absolute mass and the rate of change in absolute mass has the increase in brain size been exceptional along the terminal branch leading to humans. Once scaling effects with body mass have been accounted for the rate of increase in relative brain mass remains high but is not exceptional.
“Remains high but is not exceptional”, ie, expected for a primate of our size (Azevedo et al, 2009). Of course, since evolution is not progressive, then finding any so-called ‘anomalies’ that ‘deviate’ from the ‘progress’ in brain size evolution makes sense. They conclude that floresiensis’ brain size and body mass decrease fell within the expected range of Argue et al’s (2009) proposed phylogenetic scenario. Though, only if he evolved from habilis or Dmansi hominins if the insular dwarfism hypothesis was taken into account (which is a viable explanation for the decrease).
The effects of food scarcity and its effect on hominin brain size is hardly ever spoken about. However, as I’ve been documenting here recently, caloric quality and amount dictate brain size. Montgomeory et al (2010) write:
Although many studies have investigated the possible selective advantages and disadvantages of increased brain size in primates [5, 17, 18, 19, 20, 21], few consider how frequently brain size has reduced. Periods of primate evolution which show decreases in brain size are of great interest as they may yield insights into the selective pressures and developmental constraints acting on brain size. Bauchot & Stephan  noted the evolution of reduced brain size in the dwarf Old World monkey Miopithecus talapoin and Martin  suggested relative brain size in great apes may have undergone a reduction based on the cranial capacity of the extinct hominoid Proconsul africanus. Taylor & van Schaik reported a reduced cranial capacity in Pongo pygmaeus morio compared to other Orang-utan populations and hypothesise this reduction is selected for as a result of scarcity of food. Finally, Henneberg  has shown that during the late Pleistocene human absolute brain size has decreased by 10%, accompanied by a parallel decrease in body size.
These authors suggest this reduction is associated with an increase in periods of food scarcity resulting in selection to minimise brain tissue which is metabolically expensive . Food scarcity is also believed to have played a role in the decrease in brain size in the island bovid Myotragus . Taylor & van Schaik  therefore propose that H. floresiensis may have experienced similar selective pressures as Myotragus and Pongo p. morio.
Nice empirical vindication for me, if I don’t say so myself. This lends further credence to my scenario of an asteroid impact on earth halting food production leading to a scarcity in food. It’s hypothesized that floresiensis went from eating (if evolved from erectus) 1800 kcal per day and 2500 while nursing to 1200 per day and 1400 while nursing (Lieberman, 2013: 125). This, again, is proof that big brains need adequate energy and that cooking meat was what specifically drove this facet of our evolution.
Montgomeroy et al (2010) conclude:
Finally, our analyses add to the growing number of studies that conclude that the evolution of the human brain size has not been anomalous when compared to general primate brain evolution [59, 61, 91, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94].
In other words, humans are not ‘special’ in terms of brain size. While there is a ‘trend’ in the increase in brain size, this ‘trend’ is only possible with the advent of fire, cooking, and meat eating. Without that causal mechanism, big brains would not be metabolically viable.
A big brain (large amounts of neurons) can only evolve with enough energy, mainly the advent of cooking meat (Herculano-Houzel, 2009). Primates have much higher neuronal densities than other mammals (Herculano-Houzel, Manger, and Kaas, 2014). Since the amount of energy the brain needs per day depends on how many total neurons it has (Azevedo and Herculano-Houzel, 2012), quality calories are needed to power such a metabolically expensive organ. Only with the advent of fire could we consume enough high-quality energy to evolve such big brains.
Mammalian brains that have 100 million neurons require .6 kcal, brains with 1 billion neurons use 6 kcal per day, and brains with 100 billion neurons use 600 kcal per day (humans with 86 billion neurons use 519 kcal, coming out to 6 kcal per neuron) regardless of the volumes of the brains (Herculano-Houzel, 2011). Knowing that the amount of neurons a brain has is directly related to how much energy it needs, it doesn’t seem so crazy now that, like with the example of floresiensis, a brain could decrease in size even when noticing this ‘upward trend’ in hominin brain size. This is simply because how big a brain is directly related to amount of energy available in an area as well as the most important variable: quality of the food.
If floresiensis is descended from habilis (and there is evidence that habilis was a meat eater, so along with a low amount of energy for floresiensis on Flora as well as there being no large predators on the island, a smaller size would have been advantageous to floresiensis), then this shows that what I’ve been saying for a few months is true: the diet quality as well as amount of energy dictates whether an organism evolves to be big or small. Energy is what ‘drives’ evolution in a sense and energy comes from kcal. The highest quality energy is from meat, and that fuels our ‘big brains’ with our high neuron count.
Imagine this scenario: an asteroid hits the earth and destroys the world power grid. All throughout the world, people cannot consume enough food. The sun is blocked by dust clouds for, say, 5000 years. The humans that survive this asteroid collision would evolve a smaller brain and body as well as better eyesight to see in an environment with low light, among other traits. Natural selection can only occur on the heritable variants already in the population, so whatever traits that would increase fitness in this scenario would multiply and flourish in the population, leading to a different, smaller-brained and smaller-bodied human due to the effects of the environment.
While on the subject of the decrease in human brain size, something that’s troubling to those who champion the ‘increase in hominin brain size’ as the ‘pinnacle of evolution’: our brains have been decreasing in size for at least the past 20,000 years according to John Hawks associate professor of anthropology at the University of Wisconsin-Madison. Keep in mind, this is someone that Pumpkin Person brings up saying that our brains have been increasing for the past 10,000 years. He has also said that the increase in better nutrition has allowed us to gain back the brain size of our hunter-gatherer ancestors (with no reference), which is not true. Because what John Hawks actually wrote on his blog about this says a different story:
The available skeletal samples show a reduction in endocranial volume or vault dimensions in Europe, southern Africa, China, and Australia during the Holocene. This reduction cannot be explained as an allometric consequence of reductions of body mass or stature in these populations. The large population numbers in these Holocene populations, particularly in post-agricultural Europe and China, rule out genetic drift as an explanation for smaller endocranial volume. This is likely to be true of African and Australian populations also, although the demographic information is less secure. Therefore, smaller endocranial volume was correlated with higher fitness during the recent evolution of these populations. Several hypotheses may explain the reduction of brain size in Holocene populations, and further work will be necessary to uncover the developmental and functional consequences of smaller brains.
In fact, from the Discover article on decreasing brain size, John Hawks says:
Hawks spent last summer measuring skulls of Europeans dating from the Bronze Age, 4,000 years ago, to medieval times. Over that period the land became even more densely packed with people and, just as the Missouri team’s model predicts, the brain shrank more quickly than did overall body size, causing EQ values to fall. In short, Hawks documented the same trend as Geary and Bailey did in their older sample of fossils; in fact, the pattern he detected is even more pronounced. “Since the Bronze Age, the brain shrank a lot more than you would expect based on the decrease in body size,” Hawks reports. “For a brain as small as that found in the average European male today, the body would have to shrink to the size of a pygmy” to maintain proportional scaling.
This is in stark contrast to what PP claims he says about the evolution of human brain size over the past 10,000 years, especially Europeans who he claims Hawks has said there has been an increase in European brain size. An increase in brain size over the past 100 years doesn’t mean a trend is occurring upward, since all other data on human brain size says otherwise.
Our brains have begun to decrease in size, which is due to the effects of overnutrition and diseases of civilization brought on by processed foods and the agricultural revolution. Another proposed cause for this is that population density tracks with brain size, with brain size increasing with a smaller population and decreasing with a bigger population. In a way, this makes sense. A bigger brain should have more neurons than a smaller brain, which would aid in cognitive tasks and have that one hominin survive better giving it a better chance to pass on its genes, so if you think about it, when the population increases when social trust forms, you can piggyback off of others and they wouldn’t have to do things on their own. As population size increased from sparse to dense, brain size decreased with it.
On this notion of ‘progress’ in brain size, some people may assume that this puts us at the ‘pinnacle’ of evolution due to our superior cognitive ability (which is due to the remarkably large amount of neurons in our cerebral cortex [Hercualno-Houzel, 2016: 102]), Herculano-Houzel writes on page 91 of her book The Human Advantage: A New Understanding of How Our Brains Became Remarkable:
We have long deemed ourselves to be at the pinnacle of cognitive abilities among animals. But that is different than being at the pinnacle of evolution in a number of important ways. As Mark Twain pointed out in 1903, to presume that evolution has been a long path leading to humans as its crowning achievement is just as preposterous as presuming that the whole purpose of building the Eiffel Tower was to put the final coat of paint on its tip. Moreover, evolution is not synonmous with progress, but simply change over time. And humans aren’t even the youngest, most recently evolved species. For example, more than 500 new species of cichlid fish in Lake Victoria, the youngest of the great African Lakes, have appeared since it filled with water some 14,500 years ago.
Using PP’s logic, the cichlid fishes of Lake Victoria are ‘more highly evolved’ than we are since they’re a ‘newer species’. Using that line of logic makes no sense now, putting it in that way.
Looking at the ‘trend’ in human brain size over the past 7 million years, and its acceleration in the past 2 million, without thinking about what jumpstarted it (bipedalism, tools, fire, meat eating) is foolish. Moreover, any change to our environment that decreases our energy input would, over time, lead to a decrease in our overall brain size perhaps more rapidly, showing that this ‘trend’ in the increase in brain size is directly related to the quality and amount of food in the area. This is why floresiensis’ brain and body shrunk, and why certain primate lineages show increases in brain size: because they have a higher-quality diet. But it comes at a cost. Since primates largely eat a plant-based diet, they have to eat upwards of 10 hours a day to get enough energy to power either their brains or their bodies. If their bodies are large, their brains are small and vice versa. A plant-based diet cannot power a large brain with a high neuron count like we have, it’s only possible with meat eating (Azevedo and Herculano-Houzel, 2012). This is one reason why floresiensis’ brain shrunk along with not enough kcal to sustain their larger brain and body mass that their ancestor they evolved from previously had.
Our brains are not particularly special, and in a way, you can thank fire and cooking meat for everything that’s occurred since erectus first controlled fire. For without a quality diet in our evolution, this so-called ‘trend’ (which is based on the environment due to food quality and scarcity/abundance which fluctuate) would not have occurred. In sum, this ‘progress’ will halt and ‘reverse’ if the amount of energy consumed decreases or diet quality decreases.
Why are men attracted to low waist-to-hip ratios (WHR)? Like with a lot of our preferences, there is an evolutionary reason why men are attracted to low WHR. I came across a paper the other day by M.D. William Lassek, “Assistant Professor of Epidemiology and Research Associate in the department of Anthropology at the University of California, Santa Barbara” and co-author P.h.D. Steven Gaulin, Professor of Anthropology with specific research interests in “evolutionary psychology, cognitive adaptations, the human voice, sexual selection, evolution of sex differences, lipid metabolism and brain evolution.” This paper fascinates me because it talks about the evolution of human intelligence through a lens of nutrition and micronutrients, something that I’m well-read on due to my career. First, I will discuss the benefits of fish oil and the main reason for taking them: omega-3 fatty acids and DHA. Then I will discuss the WHR/intelligence theory.
Fish Oils, DPA/EPA, and Omega-3 Fatty Acids
Misinformation about fish oils is rampant, specifically in the HBD-sphere, specifically with Steve Sailer’s article HBD and Diet Advice. The study he cites (with no reference) I assume is this study by Yano et al (1978) in which they found that Japanese men who ate more carbohydrates had less of a chance to die of cardiovascular heart disease (CHD). He says that the first generation ate mostly rice and no fat while the second generation “ate cheeseburgers and had higher rates of coronary disease than their parents.” He then says that these diet recommendations (low-fat, high-carb) were put onto all populations with no proven efficacy for all ethnies/racial groups. These diet recommendations began around two decades before the 80s, however.
He then quotes an article by the NYT science write, Carl Zimmer, talking about how the Inuit study has “added a new twist to the omega-3 fatty acid story”. Now, I read papers on nutrition every day due to my career, I don’t know what kind of literature they read on the subject, but fish oil, more specifically DPA/EPA and omega-3s are hugely important for optimal brain growth, health, and function.
Controlled studies clearly show that omega-3 consumption had a positive influence on n-3 (fatty acid) intake. N-3 has also been recognized as a modulator of inflammation as well as the fact that omega-3 fatty acids down-regulate genes involved in chronic inflammation, which show that n-3 is may be good for atherosclerosis.
Dietary epidemiology has also shown a link between n-3 and mental disorders such as Alzheimers and depression. N-3 intake is also linked to intelligence, vision and mood. Infants who don’t get enough n-3 prenatally are at risk for developing vision and nerve problems. Other studies have shown n-3’s effects on tumors, in particular, breast, colon and prostate cancer.
Omega-3’s are also great for muscle growth. Omega-3 intake in obese individuals along with exercise show a speed up in fat-loss for that individual.
Where do these people get their information from? Not only are omega-3’s good for damage reduction after a stroke and a heart attack, they’re also good for muscle growth, breast, colon and prostate tumor reduction, infants deficient in omega-3 prenatally are at risk for developing nerve and vision problems. Increase in omega-3 consumption is also linked to increases in cognition, reduces chronic inflammation and is linked to lower instances of depression.
Clearly, fish oils have a place in everyone’s diet, not only Inuits’.
This also reminds me of The Alternative Hypothesis’s argument that there are differing CHO metabolisms based on geographic origin (not true, to the best of my knowledge).
WHR and Intelligence
Most of the theories of the increase in brain size and intelligence have to do with climate, in one way or another, along with sexual selection. Though recently, I’ve been rethinking my position on cold winters having that big of an effect on intelligence due to some new information I’ve come across. The paper titled Waist-hip ratio and cognitive ability: is gluteofemoral fat a privileged store of neurodevelopmental resources? by Lassek and Gaudin (2008) posits a very sensible theory about the evolution of human intelligence: mainly that men prefer hour-glass figures due to an evolutionary adaptation.
Why may this be the case? One of the most important reasons I can think of is that women with high WHR have a higher chance of rate of death. The Nurses Health Study followed 44,000 women for 16 years and found that women who had waists bigger than 35 inches had a two times higher risk of dying from heart disease when compared to women with the lowest waist size of less than 28 inches. Clearly, men prefer women with low WHR since they will live longer, conceive more children and be around longer to take care of said children. So while a low WHR is not correlated with fertility per se, it is correlated with longevity, so the woman can have more children to spread more of her genes.
Lassek and Gaulin also bring up the ‘thrifty gene hypothesis’, which states that these genes evolved in populations that experienced nutritional stress, i.e., famines. I’ve read a lot of books on nutrition and human evolution (I highly recommend The Story of the Human Body: Evolution, Health, and Disease) over the years and most of them discredit the idea of the thrifty gene hypothesis. However, recent research has shown the existence of these ‘thrifty genes’ in populations such as the Samoans and ‘Native’ Americans. It’s simple, really. Stop eating carbohydrates and the problems will fade away. (Hunter-gatherers don’t have these disease rates that we do in the West; it’s clear that the only difference is our diet and lifestyle. I will cover this in a future post titled “Diseases of Civilization”.)
Lassek and Gaulin pursued the hypothesis that gluteofemoral fat (fat stored in the thighs and buttocks) was the cause for the difference in the availability of neurodevelopmental nutrients available to a fetus. If correct, this could show why men prefer women with a low WHR and could show why we underwent such rapid brain growth: due to the availability of neurodevelopmental nutrients in the mother’s fat stores. Gluteofemoral body fat is the main source of long-chain polyunsaturated fatty acids (LPUFA) for children, along with another pertinent nutrient for fetal development: DHA. Lassek and Gaulin also state that 10 to 20 percent of the fat stored by a young woman during puberty is gluteofemoral fat, obviously priming her for childbearing. Even with caloric restriction, the gluteofemoral fat is not tapped utilized until late pregnancy/lactation when the baby needs nutrients such as DPA/EPA and omega-3s.
Further, 10 to 20 percent of the dry weight of the brain is made up of LCPUFA, which shows how important this one nutrient is for proper brain development in-vitro as well as the first few years of life. Lassek and Gaulin state:
A recent meta-analysis estimates that a child’s IQ increases by 0.13 point for every 100-mg increase in daily maternal prenatal intake of DHA (Cohen, Bellinger, Connor, & Shaywitz, 2005), and a recent study in England shows a similar positive relationship between a mother’s prenatal consumption of seafood (high in DHA) and her child’s verbal IQ (Hibbeln et al., 2007).
Along with what I cited above about these nutrients and their effects on our bodies while we’re in our adolescence and even adulthood, this is yet another huge reason WHY we should be consuming more fish oils, not only for the future intelligence of our offspring, but for our own brain health as a whole. Lassek and Gaulin state on pg. 3:
Each cycle of pregnancy and lactation draws down the gluteofemoral fat store deposited in early life; in many poorly nourished populations, this fat is not replaced, and women become progressively thinner with each pregnancy, which is termed “maternal depletion” (Lassek & Gaulin, 2006). We have recently shown that even well-nourished American women experience a relative loss of gluteofemoral fat with parity (Lassek & Gaulin, 2006). In parallel, parity is inversely related to the amount of DHA in the blood of mothers and neonates (Al, van Houwelingen, & Hornstra, 1997).
That critical fatty acids are depleted with parity is also consistent with studies showing that cognitive functioning is impaired with parity. IQ is negatively correlated with birth order (Downey, 2001), and twins have decreased DHA (McFadyen, Farquharson, & Cockburn, 2001) and compromised neurodevelopment compared to singletons (Ronalds, De Stavola, & Leon, 2005). The mother’s brain also typically decreases in size during pregnancy (Oatridge et al., 2002).
This also could explain why first born children are more intelligent than their siblings: because they have first dibs on the neurodevelopmental nutrients from the gluteofemoral fat, which aids in their brain growth and intelligence. What also lends credence to the theory is how the mother’s brain size typically decreases during pregnancy, due to the neurodevelopmental nutrients going to the child. (I also can’t help but wonder if this has any effect on Chinese IQ, since they had a nice increase in intelligence due to the Flynn Effect from 1982 to 2012. I will cover that in the future.)
“This hypothesis,” the authors write, “thus unites two derived (evolutionarily novel) features of Homo sapiens: sexually dimorphic fat distributions and large brains. On this view, a low WHR signals the availability of critical brain-building resources and should therefore have consequences for cognitive performance.”
The authors put forth three predictions for their study: 1) that a woman’s WHR should be negatively correlated with the cognitive ability of her offspring, 2) a woman’s WHR should be negatively correlated with her own intelligence since a woman passes on DPA as well as her own genes for low WHR to female offspring and 3) “cognitive development should be impaired in women whose first birth occurred early as well as in her future offspring, but lower WHRs, which indicate large stores of LCPUFA should be significantly protective for both” the mother and the child.
Lassek and Gaulin used data from the NHANES (National Health and Nutrition Examination Survey) III which included over 16,000 females with a mean age of 29.9 years. Measurements were taken on waist and hip circumference, WHR, BMI, and body fat as measured from bioelectrical impedance.*
For 752 “nulligravidas” (medical term for a woman who has never been pregnant), WHR explained 23 percent of the variance in total body fat estimated from the bioelectrical impedance (ugh, such a horrible measure). Moreover, “controlling for age and race/ethnicity” showed an increase of “0.01 in WHR increases total body fat by .83 kg” (1.82 pounds in freedom units). They also discovered that WHR explains 28 percent of the variance in BMI, with an increase of .47 kg per square meter, increasing the WHR by 0.01. BMI also explained 89 percent of the variance in body fat (garbage ‘body fat measuring instrument’ aside) with an increase of 1 kg per square meter increasing fat by 1.8 kg (close to 4 pounds in freedom units), but when added to the regression model, WHR made no additional contribution.
Lassek and Gaulin’s first hypothesis was corroborated when they found that the mother’s WHR was negatively correlated with the child’s intelligence on 4 cognitive tests. WHR accounted for 2.7 percent of the variation in test scores, “with a decrease of 0.01 in the mother’s current WHR increasing the child’s mean cognitive score by 0.061 points”. In the first subsample, they controlled for mother’s age, parental education, family income and race/ethnicity. Even when these variables were controlled for, WHR was still negatively correlated with the cognitive score. When these variables were controlled for, a decrease of 0.01 in WHR increased the average score by 0.024 points.
Their second hypothesis was also confirmed: that women with lower WHR would be more intelligent than women with higher WHRs. In girls aged 14-16, the WHR accounted for 3.6 percent of the variance in the average of the four cognitive tests. Also discovered was that in women aged 18 to 49, WHR accounted for 7 percent of the variance in years of education and 6 percent of the variance in two tests of cognitive ability. Even when controlling for age, parity, family income, age at first birth, and race/ethnicity, the negative correlation was still seen in 14 to 16-year-old girls.
There is also competition neurodevelopmental resources between mother and child. As I showed earlier in this article, a woman’s brain size decreases during pregnancy. This decrease in brain size during pregnancy is due to the babe getting more of the neurodevelopmental nutrients for brain growth from the mother. Clearly, as the mother’s stores of brain-growing nutrients become depleted, so does her brain size as te nutrients from her stored fat goes to developing the fetuses’ brain.
Lassek and Gaulin confirmed their hypothesis that a woman with a lower WHR would be more intelligent as well as have more intelligent children. WHR predicts the cognitive ability of the offspring while BMI does not. However, controlling for family income and parental education decreases the effect of WHR on the child’s intelligence, the effect still remains giving strong support to the hypothesis that women with low WHR pass on genes for low WHR as well as nutrients needed for neurodevelopment. Further, controlling for parental cognitive ability may mask the effects of the WHR. It’s well known that the mother’s intelligence is the best predictor for her offspring’s intelligence, which is due to the mother and grandmother passing on genes that augment the effect of LCPUFAs, along with the genes for lower WHR.
Women with a lower WHR were found to be more intelligent, and a lower WHR helps to protect cognitive resources (neurodevelopmental nutrients) for the mother and child. The mother’s body has a dilemma, though: it has to store nutrients for the mother’s own cognition; store resources for future pregnancies; and provide nutrients for their growing fetus. Obviously, especially in young mothers, this poses a problem as there is a conflict for what the brain should do with the nutrients the mother ingests. Children born to teenaged mothers have lower cognitive test scores, but, they are protected from this fate if the mother has a low WHR. This shows, definitively, that young mothers who are still growing will show no negative effects on their growth when pregnant if they have a low WHR which signals they have a large amount of LCPUFAs and other essential neurodevelopmental nutrients for the baby’s brain growth.
LCPUFAs are scarce in human diets. Thusly, an evolutionary preference for low WHR evolved for men so their children can have optimal nutrients while growing in the mother’s womb. The study confirmed that large brains, and along with it higher intelligence, and sexually dimorphic fat distribution have a strong link. Clearly, if a mother doesn’t have adequate levels of LCPUFAs, neurodevelopment will be impeded since the babe will not be getting the optimal nutrients for brain growth. Moreover, diets low in omega-3s should have consequences for intelligence and brain size of a baby, since when a baby is in the womb that is the most important time for it to get optimal brain nutrients. Is there any type of environment we can make ourselves and lifestyle choices we can take for ourselves, spouses and children to foster higher intelligence in them? I will cover that in the future.
Men love hour-glass figures, a low WHR. As I’ve shown in this article, there is an evolutionary reason for this. Men were asked to rate women who had surgery to move fat to their buttocks. Body weight stayed the same, but the fat was redistributed. It was found in brain scans of the men that the same parts of the brain related to reward lit up, including regions associated with drugs and alcohol. (more information here)
I’ve long known of the tons of positive benefits of omega-3 fatty acids and fish oil on human brain development. Fish oils and the nutrients in them are imperative for a healthy and growing brain. Without it, brain development will suffer. As a man, I can say firsthand that a low WHR is the most attractive. Now I understand the evolutionary reason behind it: fostering high intelligence due to the mothers lower-body fat stores. Omega-3s and LCPUFA are extremely important for optimal fetal brain growth. Moreover, the current American diet is low in omega-3s, while high in omega-6s. There is evidence of high omega-6 intake being related to obesity, metabolic syndromes, a progressive increase in body fat over the generations. The omega-6 and -3 ratios in the body also play a role in obesity, with a lower omega-3 ratio and higher omega-6 ratio being related to obesity. This is due to adipogenesis, browning of the fat tissue, lipid homeostasis, and systemic inflammation. Clearly, as shown in this article, it’s imperative to have a balance of omega-3 and omega-6 fatty acids. This could also have to do with the hyperactivity of the cannabinoid system (which we all know what that’s involved with: eating more) and that could also be a cause for obesity with out-of-whack omega-6 to -3 fatty acid levels in the body. That’s for another day, though.
The totality of evidence is clear. If you want healthy children, choose a mate with a low WHR. She and her offspring will be more likely to be more intelligent. Clearly, if you’re reading this, you’re interested in intelligence as well as having the best possible life and life outcomes for your children. Well, choose a woman with a low WHR and you’ll be more likely to have more intelligent children!
* I have one problem with this study. They assessed body fat with bioelectrical impedance. The machine sends a light electrical current through the body and measures the degree of resistance to the flow of the current, which body fat can then be estimated. Problems with measuring body fat this way are as follows: it depends on how hydrated you are, whether you exercised that day, when you last ate, even whether your feet are calloused. Most importantly, they vary depending on the machine as well. Two differing machines will give two differing estimates. This is my only problem with the study. I would like if, in a follow-up study, they would use the DXA scan or hydrostatic weighing. These two techniques would be much better than using bioelectrical impedance, as the variables that prevent bioelectrical impedance from being a good way to measure body fat don’t exist with the DXA scan or hydrostatic weighing.