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How Intelligent Were Our Hominin Ancestors?

3000 words

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?

neuron-and-brain-size

(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.

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Is There Progress in Hominin Brain Evolution?

2700 words

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 [22] noted the evolution of reduced brain size in the dwarf Old World monkey Miopithecus talapoin and Martin [23] 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 [24]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 [25] 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 [17]. Food scarcity is also believed to have played a role in the decrease in brain size in the island bovid Myotragus [12]. Taylor & van Schaik [24] 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.

Selection for smaller brains in Holocene human evolution

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.

What Caused Human Brain Size to Increase?

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People talk a lot about intelligence and brain size. Something that’s most always brought up is how the human brain increased in size the past 4 million years. According to PP, the trend for bigger brains in hominins is proof that evolution is “progressive”. However, people never talk about a major event in human history that caused our brains to suddenly increase: the advent of fire. When our ancestors mastered fire, it was then possible for the brain to get important nutrients that influenced growth. People say that “Intelligence is the precursor to tools”, but what if fire itself is the main cause for the increase in brain size in hominins the past 4 million or so years? If this is the case, then fire is, in effect, the ultimate cause of everything that occurred after its use.

The human brain consumes 20-25 percent of our daily caloric intake. How could such a metabolically expensive organ have evolved? The first hominin to master fire was H. erectus. There is evidence of this occurring 1-1.5 mya. Not coincidentally, brain size began to tick upward after the advent of fire by H. erectus. Erectus was now able to consume more kcal, which in turn led to a bigger brain and the beginnings of a decrease in body size. The mastery and use of fire drove our evolution as a species, keeping us warm and allowing us to cook our food, which made eating and digestion easier. Erectus’s ability to use fire allowed for the biggest, in my opinion, most important event in human history: cooking.

With control of fire, Erectus could now cook its foods. Along with pulverizing plants, it was possible for erectus to get better nutrition by ‘pre-digesting’ the food outside of the body so it’s easier to digest. The advent of cooking allowed for a bigger brain and with it, more neurons to power the brain and the body. However, looking at other primates you see that they either have brains that are bigger than their bodies, or bodies that are bigger than their brains, why is this? One reason: there is a trade-off between brain size and body size and the type of diet the primate consumes. Thinking about this from an evolutionary perspective along with what differing primates eat and how they prepare (if they do) their food will show whether or not they have big brains or big bodies. How big an organism’s brain gets is directly correlated with the amount and quality of the energy consumed.

There is a metabolic limitation that results from the number of hours available to feed and the low caloric yield of raw foods which then impose a trade-off between the body size and number of neurons which explains why great apes have small brains in comparison to their bodies. Metabolically speaking, a body can only handle one or the other: a big brain or a big body. This metabolic disadvantage is why great apes did increase their brain size, because their raw-food diet is not enough, nutritionally speaking, to cause an increase in brain size (Azevedo and Herculano-Houzel, 2016). Can you imagine spending what amounts to one work day eating just to power the brain you currently have? I can’t.

Energy availability and quality dictates brain size. A brain can only reach maximum size if adequate kcal and nutrients are available for it.

Total brain metabolism scales linearly with the number of neurons (Herculano-Houzel, 2011). The absolute number of neurons, not brain size, dictates a “metabolic constraint on human evolution”, since people with more neurons need to sustain them, which calls for eating more kcal. Mammals with more neurons need to eat more kcal per day just to power those brains. For instance, the human brain needs 519 kcal to run, which comes out to 6 kcal per neuron. The brain is hugely metabolically expensive, and only the highest quality nutrients can sustain such an organ. The advent of fire and along with it cooking is one of, if not the most important reason why our brains are large (compared to our bodies) and why we have so many neurons compared to other species. It allowed us to power the neurons we have, 86 billion in all (with 16 billion in the cerebral cortex which is why we are more intelligent than other animals, number of neurons, of course being lower for our ancestors) which power human thought.

The Expensive Tissue Hypothesis (ETA) explains the metabolic trade-off between brain and gut, showing that the stomach is dependent on body size as well as the quality of the diet (Aiello, 1996). As noted above, there is good evidence that erectus began cooking, which coincides with the increase in brain size. As Man began to consume meat around 1.5 million years ago, this allowed for the gut to get smaller in response. If you think about it, it makes sense. A large stomach would be needed if you’re eating a plant-based diet, but as a species begins to eat meat, they don’t need to eat as much to get the adequate amount of kcal to fuel bodily functions. This lead to the stomach getting smaller, and along with it so did our jaws.

So brain tissue is metabolically expensive but there is no significant correlation between brain size and BMR in humans or any other encephalized mammal, the metabolic requirements of relatively large brains are offset by a corresponding gut reduction (Aiello and Wheeler, 1995). This is the cause for the low, insignificant correlation between BMR and our (relatively large brains, which correlates to the amount of neurons we have since our brains are just linearly scaled-up primate brains).

Evidence for the ETA can be seen in nature as well. Tsuboi et al (2015) tested the hypothesis in the cichlid fished of Lake Victoria. After they controlled for the effect of shared ancestry and other ecological variables, they noted that brain size was inversely correlated with gut size. Perhaps more interestingly, they also noticed that when the fish’s’ brain size increased, increased investment and paternal care occurred. Moreover, more evidence for the ETA was found by Liao et al (2015) who found a negative correlation between brain mass and the length of the digestive tract within 30 species of Anurans. They also found, just like Tsuboi et al (2015), that brain size increase accompanied an increase in female reproductive investment into egg size.

Moreover, another cause for the increase in brain size is our jaw size decreasing. This mutation occurred around 2.4 million years ago, right around the time frame that erectus discovered fire and began cooking. This is also consistent with, of course, the rapid increase in brain size which was occurring around that time. The room has to come from somewhere, and with the advent of cooking and meat eating, the jaw was, therefore, able to get smaller along with the stomach which increased brain size due to the trade-off between gut size and brain size. Morphological changes occurred exactly at the same time changes in brain size occurred which coincides with the advent of fire, cooking, and meat eating. Coincidence? I think the evidence strongly points that this is the case, the rapid increase in brain size was driven by fire, cooking, and meat eating.

The rise of bipedalism also coincided with the brain size increase and nutritional changes. Bipedalism freed the hands so tools could be made and used which eventually led to the control of fire. Lending more credence to the hypothesis of bipedalism/tools/brain size is the fact that there is evidence that the first signs of bipedalism occurred in Lucy, our Australopithecine ancestor who had pelvic architecture that showed she was clearly on the way to bipedalism. There is more evidence for bipedalism in fossilized footprints of australopithecines around 3 mya, coinciding with Lucy, tool use and eventually the advent and use of fire as a tool to cook and ward off predators. Ancient hominids could then better protect their kin, have higher quality food to eat and use the fire to scare off predators with.

The nutritional aspect of evolution and how it co-evolved with us driving our evolution in brain size which eventually led to us is extremely interesting. Without proper nutrients, it’s not metabolically viable to have such a large brain, as whatever kcal you do eat will need to go towards other bodily functions. Moreover, diet quality is highly correlated with brain size. Great apes can never get to the brain size that we humans have, and their diet is the main cause. The discovery and control of fire, the advent of cooking and then meat eating was what mainly drove the rapid increase of brain size starting 4 mya.

In a way, you can think of the passing down of the skill of fire-making to kin as one of the first acts of cultural transference to kin. It’s one of the first means of Lamarckian cultural transference in our history. Useful skills for survival will get passed down to the next generation, and fire is arguably the most useful skill we’ve ever come across since it’s had so many future implications for our evolution. The ability to create and control fire is one of the most important skills as it can ward off predators, cook meat, be used to keep warm, etc. When you think about how much time was freed up upon the advent of cooking, you can see the huge effect the control of fire first had for our species. Then think about how we could only control fire if our hands were freed. Then human evolution begins to make a lot more sense when put into this point of view.

When thinking about brain size evolution as well as the rapid expansion of brain size evolution, nutrition should be right up there with it. People may talk about things like the cold winter hypothesis and intelligence ad nauseam (which I don’t doubt plays a part, but I believe other factors are more important), but meat-eating along with a low waist-to-hip ratio, which bipedalism is needed for all are much more interesting when talking about the evolution of brain size than cold winters. All of this wouldn’t be possible without bipedalism, without it, we’d still be monkey-like eating plant-based diets. We’d have bigger bodies but smaller brains due to the metabolic cost of the plant-based diet since we wouldn’t have fire to cook and tools to use as we would have still been quadrupeds. The evolution of hominin intelligence is much more interesting from a musculoskeletal, physiological and nutritional point of view than any simplistic cold winter theory.

What caused human brain size to increase is simple: bipedalism, tools, fire, cooking, meat eating which then led to big brains. The first sign of big brains were noticed right around the time erectus had control of fire. This is no coincidence.

Bipedalism, cooking, and food drove the evolution of the human brain. Climate only has an effect on it insofar as certain foods will be available at certain latitudes. These three events in human history were the most important for the evolution of our brains. When thinking about what was happening physiologically and nutritionally around that time, the rebuttal to the statement of “Intelligence requires tools” is tools require bipedalism and further tools require bigger brains as human brains may have evolved to increase expertise capacity and not IQ (more on that in the future), which coincides with the three events outlined here. Whatever the case may be, the evolution of human intelligence is extremely interesting and is most definitely multifaceted.

The Human Brain Is Not Particularly Special: A New Way of Looking At the Human Brain

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What if I told you that, neuronally speaking, the human brain was not particularly special? That, despite its size in comparison to our bodies, we are not particularly special in comparison to other primates or mammals. The encephalization quotient supposedly shows how “unique” and “special” humans are in terms of brain size compared to body size. We have a brain that’s seven times bigger than would be expected for our body size, and that’s what supposedly makes us unique compared to the rest of the animals kingdom.

Suzana Herculano-Houzel, the new Associate Professor of Psychology at Vanderbilt University (former Associate Professor at the Federal University of Rio de Janeiro), is a neuroscientist who challenges these notions that humans are supposedly unique in our brain size when compared to other mammals and primates. She pioneered a technique of turning brains into soup with a machine called the isotropic fractionator, which turns it into a “soup of a known volume” that contain the free cell nuclei to be colored and counted under a microscope. Using this technique, Azevedo et al (2009) showed that “with regard to numbers of neuronal and nonneuronal cells, the human brain is an isometrically scaled-up primate brain.” Every cell in the soup contains one nucleus, so counting is easy. Using this technique, they discovered that using the brain scaling of rats, a brain of 100 billion neurons would weigh 45 kg and body mass would be 109 tons. While using the primate scaling, a brain of 100 billion neurons would weigh 1.45 kg and belong to a body weighing 74 kg, suspiciously what humans are…. The human brain is constructed with the same rules as other primate’s brains. We are no different.

This is in direct opposition to brain size fetishists, who champion the fact that the human brain is some so-called ‘pinnacle of evolution’, as if all of the events that preceded us was setting the stage for our eventual arrival.

Of course, speaking in terms of body size, humans have the largest brains. However, the amount of neurons a brain has seems to be correlated to how cognitively complex the organism is. Humans have the most neurons for their brain size, however, that is one of the only things that sets us apart from other mammals/primates.

Azevedo et al (2009) write:

Our notion that the human brain is a linearly scaled-up primate brain in its cellular composition is in clear opposition to the traditional view that the human brain is 7.0 times larger than expected for a mammal and 3.4 times larger than expected for an anthropoid primate of its body mass (Marino, 1998). However, such large encephalization is found only when body-brain allometric rules that apply to nonprimates are used, as stated above, or when great apes are included in the calculation of expected brain size for a primate of a given body size.

Humans aren’t special in terms of neuronal and nonneuronal cells, our brains are just scaled-up versions of primate brains. There is nothing ‘weird’ or ‘unique’ about our brains; our brains follow the same ‘laws’ as other primates. Great apes such as the orangutans and gorillas are the ones who have brains that are smaller than their bodies. Their bodies are much larger than expected for primates of their brain size. That is where the outlier exists; not us.

The reason for our higher cognition is the 16 or so billion neurons in our cerebral cortex. For instance, the astounding human brain size in relation to body size is often touted, however, elephant’s brains are bigger, and they also have more neurons than we do. What sets us apart from elephants is that our cerebral cortex has about three times the amount of neurons compared to the elephant whose cerebral cortex is two times larger. The density of the neurons in our cerebral cortex seems to be the cause of our unique intelligence in the animal kingdom. Herculano-Houzel writes in her book The Human Advantage: A New Understanding of How Our Brains Became Remarkable (2016: 102):

The superior cognitive abilities of the human brain over the elephant brain can simply—and only—be attributed to the remarkably large number of neurons in its cerebral cortex.

Moreover, the absolute expansion of the cerebral cortex and its relative increase over the rest of the brain have been particularly fast in primate evolution (Herculano-Houzel, 2016: 110). I will return to the cause for this later.

She also noticed that in all of the papers that she read about the brain that the constant number quoted for the amount of neurons in the human brain was 100 billion. She continuously searched for the original citation and couldn’t find it. It wasn’t until she used her isotropic fractionator to get the true amount of neurons in the human brain—86 billion, which coincided with another stereological estimate.

Human brains are normally thought of as the ‘pinnacle of evolution’. Some people believe that everything preceding us was just setting the stage for the eventual Dawn of Man. This couldn’t be further from the truth. She writes on page 112:

And at the pinnacle of evolution, supposedly, is the human cerebral cortex, with the largest relative size compared to the brain. That, however, is only to be expected, both because we are primates and because, among primates, we have the largest brain and cerebral cortex, not because we are special.

Moreover, what I hardly see discussed is the fact that the brain is the most metabolically expensive organ the body has. Our brain weighs in at 2 percent of our body weight, yet takes 500 kcal—or 25 percent of our daily energy needs—to power. Further, 500 kcals per day translates to 24 watts of power, slightly more than half the amount of energy it takes to power a 40 watt light bulb and just over one-third of the power it takes to power a 60-watt laptop. Our muscles, in comparison, generate over 3 times the amount of energy (75 watts) and even more in short bursts (think Type II muscle fibers). Amazingly, the amount of energy the brain uses stays constant at 24 watts. This is attributed to some parts of the brain being more active while some are less active. However, the redistribution of blood flow from the less active to more active parts of the brain explains how the brain can use a constant amount of energy and never go above its daily requirements (Herculano-Houzel, 2016: 174).

When thinking about the overall brain size of a species, the amount of caloric energy that organ needs daily has to be taken into account. For instance, as noted previously, the human brain needs 129 grams of glucose or 519 kcal to run per day. Consuming the amount of kcal we need to keep our brains running efficiently is easy in the modern-day world: one cup of sugar contains the amount of kcal needed to power the brain all day. There is a trade-off between body size and number of neurons. Thinking about this from a metabolic point of view, there are metabolic limitations on how big a brain can get in comparison to how many kcal the primate in question consumes.

In her Ted Talk (starting at 10 minutes in), she talks about how there is a trade-off between body and brain size. She says that a primate that eats 8 hours per day would have 53 billion neurons if it weighed 25 kg, 45 billion neurons if it weighed 50 kg, if it had 30 billion neurons it would weigh 75 kg, if it had 12 billion neurons it would weigh 100 kg and the amount of neurons would not be viable if it weighed 150 kg. Keep in mind that primates eat 8-9 hours per day—which seems to be the upper limit on the amount of time they can spend eating. So you can clearly see there is a trade-off between brain size and body size—the bigger the body gets for a primate, the brain gets smaller. And, obviously, we humans got around that—but how?

Neurons are extremely expensive from a caloric point of view. Using our brains in the previous comparison, for a brain with 86 billion neurons in a body weighing g 60-70 kg, we should have to eat for over 9 hours to attain the caloric energy needed to power our huge (in terms of neurons) brains. And, obviously, eating for over 9 hours per day just to power our neurons isn’t viable. So how did we get so many neurons if they are so dependent on adequate kcal to power? The thing is, the energy availability in a raw diet never would have powered brains as big as ours (Azevedo and Herculano-Houzel, 2012).

Let’s talk about what we know so far: as detailed above, our brains cost just as much energy as it should and we can’t eat for over 9 hours a day to attain the amount of kcal in order to power and sustain our huge brains, how did our brains get so big?

There is a ‘simple’ way of getting around these energy restraints: cooking. Cooking allowed us to ‘pre-digest’ food, so to speak, before we ingested it. PumpkinPerson always talks about the ‘radical behavioral change’ that occurred, well it occurred with the advent of cooking allowing us to extract nutrients quicker from our food to power our big brain with 86 billion neurons. Without one of the most important events in human history, everything you see around you today would not exist. The best evidence we have is that our ancestors starting with the australopithecines and going to habilis and erectus, was that there was a huge increase in brain size and the only thing that could possibly explain such an increase was the advent of cooking. Our ancestors 1.5 million years ago showed the first signs of cooking, which led to the increase in brain size in our species. Fire played a huge role in our evolution and it could be argued that, without fire, we wouldn’t be here today (or, at least with our current cognitive ability). Our ancestors who were alive around that time did have the capability to make tools, so the digestion process could have begun outside the body by grinding and mashing food before it was eaten.

In sum, the human brain is not special. It follows the same laws as all other primate brains. It has the amount of neurons that are expected for a brain its size in a primate. We can either take ‘brains’ or ‘brawn’, meaning our brains will get smaller as our bodies get bigger and vice versa (in primates anyway). The size of our brains is completely predicated on the amount of caloric energy we intake. Human evolution was driven by fire when our first ancestors started to use it to cook to pre-digest food before eating it. That’s what drove the evolution of our bigger brains which started around 1-1.5 million years ago, and without the ability to consume quality calories with the right amount of nutrients for brain growth, human evolution never would have occurred how it did—especially for the evolution of our brains. Moreover, without the rise of bipedalism, our hands would have never been free to make tools, to use fire and cook food to get our bigger brains because, as shown above, the amount of hours we would need to eat would not be feasible to sustain the brain that we have.

The human brain is just a linearly scaled-up primate brain (Herculano-Houzel, 2009) and has the amount of neurons that a brain our size that an organism of our size would be expected to have. What sets us apart is the amount of neurons that are crowded into our cerebral cortex—16 billion in total—which is responsible for our cognitive superiority over other species on earth. Our overall brain size is not responsible for our domination and conquest of earth, it was the amount of neurons in our cerebral cortex that allowed for our cognitive sophistication over other animals on earth. What sustained our big brains with energy-demanding neurons was the advent of fire and cooking, which allowed us to consume the amount of kcal needed in order to carry around such big brains. The real “Human Advantage” is cooking which led to bigger brains and more cognitive sophistication due to the amount of neurons in our cerebral cortex, not our overall brain size.

Why Are Men Attracted To Low Waist-to-Hip Ratios?

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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 AdviceThe 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.

An increase in omega-3 consumption leads to decreased damage from heart attacks.

Omega-3 may also reduce damage after a stroke.

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 Diseaseover 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)

Conclusion

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 generationsThe 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.

(Also see Eternal Curves by the Lassek and Gaulin and their book Why Women Need Fat for more information.)

Are Caesarian Sections Affecting Human Evolution?

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Our brains are the most metabolically demanding organ we have, sapping 5-600 kcal per day (25 percent of our daily energy needs). Due to how cost-efficient the brain is, it only would have evolved if it gave us a bigger fitness advantage (which it obviously did). In the news a couple of days ago, it broke that C-sections may be affecting our evolution. But in all of the articles I read about it I didn’t see any one of them talking about how C-sections may affect human evolution in America between race. Clearly, if  C-sections are having this effect on the country as a whole, there must be racial differences as well. Could this have an effect on brain size between race in America?

C-sections have increased in frequency since 1996. Clearly, if there is any selection it’s for more narrow-hipped women and bigger-brained babies. The regular use of C-sections has led to an evolutionary increase of fetopelvic disproportion rates by 10 to 20%. (Mitteroecker et al, 2016) Fetopelvic disproportion is the inability of a babe’s head to pass through the mother’s birth canal. This is because the head—and along with it the brain—is too big, leading to emergency C-sections. Mitteroecker et al (2016) also say (which slightly amused me):

Mitteroecker et al (2016) also say (which slightly amused me):

Neonatal size and maternal pelvic dimensions influence fitness (i.e., reproductive success) of the newborn and the mother in multiple ways. Undoubtedly, relative brain size had increased during human evolution in response to directional selection. Recently, it has also been suggested that the large human brain may be the result of runaway selection for the childcare of infants that are born prematurely because of their large brain (12). It is unclear whether any of this selection still persists after the slight decrease of brain size in the late Pleistocene. However, birth weight, which correlates with brain size at birth, is strongly positively associated with infant survival rate (13) and has also been reported to correlate negatively with the risk of multiple diseases (14). Reducing neonatal brain size by shortening gestation length seems to be equally disadvantageous: Delivery before term clearly increases the likelihood of impaired cognitive function in later life (15, 16).

Brain size is decreasing. Associate professor of anthropology at the University of Wisconsin John Hawks also states in his blog post, Selection for smaller brains in Holocene human evolution, where he says (contrary to Pumpkin Person’s assertion) that human brain size has gotten smaller in the past 10,000 years:

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.

The reduction in brain size began around 28 kya and accelerated around 10 kya after the dawn of agriculture. The planet getting warmer also played a part in the decrease in brain size, which also allowed for the beginning of agriculture. Anyway, I’m sidetracking, I will return to this point in the future.

Large brains were also selected for since we needed to care for helpless babies. Natural selection for large brains led to more premature births which itself selected for even larger brains.

One-hundred years ago, a narrow-hipped mother who was pregnant with a big-headed baby would have died. Narrow-hipped women with big-headed babies can now survive, transmitting genes for both big brains and narrower pelvises. This is natural selection currently at work as we speak.

One thing that I obviously didn’t see in any article I’ve read on this matter is how will this affect racial differences in brain size? Which race has the most C-sections and will that select for bigger heads and smaller pelvises in that population?

Black women are substantially more likely to deliver by C-section than are white women (pg. 4). Though, one reason that C-sections occur is due to obesity. Black women are the most likely to be obese, which is part of the reason why they have more C-sections. If this trend continues, I could see a slight uptick in black brain size, as even smaller hips get selected for in black women, along with an increase in brain size. That’s one reason why Africans have smaller heads and brains than East Asians and Europeans: they have narrower hips which allows for better athleticism. Conversely, Europeans and East Asians have wider hips which allows for bigger-brained children but hampers athletic ability.

While on the topic of race and C-sections, Asian female-European Male couples have higher rates of C-sections. The obvious explanation is that the Asian woman’s pelvis is too narrow to birth bigger babies. In the study, Asian female-white male couples had babies that had a median weight of 8 pounds, while Asian-Asian couples had babies that had a median weight of 7.1 pounds and finally Asian male-white female couples’ babies had a median weight of 7.3 pounds. However, Asian female-white male couples had an increased rate of C-section deliveries, proving that a significant differences exist between sex of the parent (whether the father or mother is Asian or white influences birth weight) which leads to increased C-section rates due to the white father passing clearly influencing the birth weight more, thusly making it difficult for his Asian partner to birth the baby. There are 100 deaths per 100,000 live births per year in the U.S., a rate of .1 percent. Clearly, though the death rate is low, C-sections lead to maternal mortality and since Asian females are more likely to have a C-section when the father is white due to the baby being bigger, the mortality rate is slightly increased when this interracial pairing occurs.

C-sections are causing natural selection, favoring for bigger heads and narrower hips. This helped us, evolutionarily speaking, as human bipedalism is promoted by a narrow pelvis. C-sections could possibly select for bigger-brained African Americans. Though brain size has decreased in the past 10,000 years, our brain size will slightly increase over time due to this selection pressure. Asian women and white male couples have C-sections more often. Pretty good case against race-mixing, if I don’t say so myself.

More Thoughts on Bipedalism

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I wrote about bipedalism last week, however, in a conversation with a commented on PumpkinPerson’s blog, I came to a slightly different conclusion than I did in my previous article on the matter.

I quoted Daniel Liberman, author of the book The Story of the Human Body: Evolution, Health, and Disease:

As one might expect, other selective pressures are hypothesized to have favored bipedalism in the first hominins. Additional suggested advantages of being upright include improved abilities to make and use tools, to see over tall grass, to wade across streams, and even to swim. None of these hypotheses bear up under scrutiny. The oldest stone tools appear millions of years after bipedalism evolved.(Lieberman, 2013: 43)

However, after being linked to this journal article Shallow-water habitats as sources of fallback foods for homininsI began to rethink my position on this matter.

Now, the climate change when humans and chimps diverged is still the primary cause of bipedalism, but after reading this abstract, I came to think that the climate change (getting warmer) rose the sea levels which then drove Man to walk on two legs, gather food, and, eventually, wade in water to find more food which led to some selection for bipedalism in our ancestors. Humans needed to become bipedal to find more food as the climate change made their primary food more scarce. This then drove early Man into shallow waters to look for food.

As the climate was getting warmer, the same foodstuffs we ate were not as readily available. So what drove us to be bipedal was 1) the need for immediate food, i.e., looking for food on the forest floors and 2) when adequate food could not be found on the floors of the forests, Man then had to go into the water. This had multiple advantages. One could escape from predators, find more food with adequate nutrients which, in turn, had as evolve bigger brains, and the most important aspect, it’s much easier to be bipedal in water as it’s easier to stand in water.

This paper, The evolution of the upright posture and gait—a review and a new synthesisconcludes:

Wading was an appropriate trigger not only to stand up but also forced the primate to walk on. It seems likely that habitual bipedalism began not long after the separation from the gorilla and chimpanzee clade(s). From that time onwards, throwing could be evolved with free upper extremities much more successfully than before. Selective factors related to the reduction of incoming solar radiation became effective. Endurance running and adaptations to carry tools (like weapons) started their evolutionary improvements. If these processes took about 4 Ma, the wading hypothesis is consistent with a rather perfect bipedal anatomy as shown, e.g., in Homo ergaster (WT 15000), about 1.6 Ma ago. In this way, many of the hypotheses competing in the past may be harmonised, as some of them have yielded important contributions to the understanding of the evolution of the human habitual upright gait.

The first sentence corroborates what Lieberman says in The Story of the Human Body. The final sentence brings together all of the theories that drove bipedalism in humans into a ‘new synthesis’.

Now, climate change (the earth getting warmer) is still the ultimate cause, but a proximate cause of bipedalism is wading in the water to 1) find more food and 2) escape predators.

This ‘new synthesis’ of how Man became bipedal is a great way to unify a lot of theories of bipedalism that gave us great understanding of human evolution in regards to bipedalism. In that vain, it’s like E.O. Wilson’s Sociobiology: A New Synthesis in which he sought to unify the evolutionary mechanics of altruism, aggression, and nurturance– our main social behaviors. This ‘new synthesis’ in the study of how we became bipedal unifies competing theories into a more understandable theory.

Moreover, bipedalism made it easier to consume more kcal which led to bigger brains. To quote Suzana Herculano-Houzel from her book The Human Advantage: A New Understanding of How Our Brain Became Remarkable:

“The remaining way to work around an energetic constraint to the number of neurons in the brain involves dietary changes that would allow for more calories to be obtained in the same amount of time, or even less. Some first changes in that direction probably took place 4 million years ago when our australopithecine ancestors stood upright and became habitual bipeds. As Daniel Lieberman explores in detail in The Story of the Human Body, bipedality potentially increases the amount of calories that can be amassed in a day by extending the range of food picking, for it is much easier and costs four times fewer kilocalories to walk on two feet, as humans do, than on all fours, as modern great apes do and the ancestor from which australopithecines originated must have done. Roaming away from home to find food, is the definition of a food gatherer, as opposed to a food picker, which is what great apes remain to this day. Bipedality made food gatherers of our ancestors.” (Herculano-Houzel, 2016: 189)

bipedalism-and-cooking

This graph from her book shows that bipedality preceded cooking which increased our brain size (I will write on that soon).

More neurons in the cerebral cortex is the cause for our amazing brains. But we are NOT unique!! This kcal increase led to more neurons in our cerebral cortex which then allowed for reasoning, finding patterns, developing technology and passing it on through culture. Cooking is why we are so ‘unique’ in comparison to other animals. As shown in the graph above, the increase in brain size happened around the time of H. Erectus. They show smaller teeth at that period, which shows that the selection was already occurring. The smaller teeth to break down food more to extract nutrients from the food they gathered shows that bipedalism evolved alongside the evolution of smaller teeth.

In sum, the ultimate cause of bipedality is still climate change, but the proximate cause, in part, was wading in the water which led to our ancestors to find more food. And, over time, we were selected for bipedalism as I wrote in my previous article on the matter. We can see that bipedalism slightly predated cooking, which the ultimate cause of which was to find more food. This is seen in the records we have. I will write more on this in the future as I read into this more.

Neanderthals, Inbreeding, r/K Selection Theory and Eurasian Birthrates

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(Note, 6/24/17: Rushton’s r/K selection in applications to human races is dead. It’s been dead for almost 30 years after and ecologist critiqued his method and use of ecological theory in application to human races. Now, that doesn’t meant that everything written below—or even on my whole blog—is fully wrong, just that the attempted explanation is wrong. It still holds that Eurasians have worse fitness than Africans, which is partly due to deleterious Neanderthal variants, however, r/K theory does not explain it.)

Science Daily reported last week that Neanderthals left humans a genetic burden, which is having less offspring. Of course, these deleterious alleles only introgressed into non-African populations due to Africans not leaving Africa. This manifests itself today in birth rates within countries and between them based on the ethnic/racial mix. And (not) coincidentally, the areas with the highest rate of children are in sub-Saharan Africa.

The Neanderthals existed in small bands, so inbreeding was common. Due to this inbreeding, Neanderthals were more homogenous than we are today. When humans migrated out of Africa, they encountered the inbred Neanderthals who they interbred with. Harmful genetic variants acquired from Neanderthals are shown to reduce the fitness of populations with certain deleterious alleles. There are of course tradeoffs with everything in life. Increased intelligence and being better able to weather the Ice Age, among numerous other factors, were positive things gained from interbreeding with  Neanderthals. Negative effects were the acquisition of deleterious alleles which still persist today in non-African hominids. These deleterious alleles decreased biological fitness which manifests itself in the birthrate of Eurasian populations throughout the world (the Germann and Japanese birthrate is 1.3 for reference).

Harris and Nielson also hypothesize that since Neanderthals existed in small bands that natural selection was less effective, allowing for weakly harmful mutations to pass on and not get weeded out over the generations. However, when introduced back into humans these effects become lost over time due to a large population with natural selection selecting against the deleterious Neanderthal alleles. Using a computer program, Harris and Nielson quantify how much of a negative effect the Neanderthal genome had on modern populations. The conclusion of the results was that Neanderthals are 40 percent LESS genetically fit than modern humans.

The researchers’ simulations also suggest that humans and Neanderthals mated more freely, which leads more credence to the idea that Neanderthals got absorbed into the Homo Sapien population and not mostly killed off. The estimation for Neanderthal DNA in modern hominids from the simulation was around 10 percent, which then continued to drop as the Neanderthal-Homo Sapiens hybrids interbred with those who hardly had any Neanderthal DNA. More evidence also shows that the percentage of Neanderthal DNA was higher in the past in Eurasians as well. Which makes sense since Asians have on average 20 percent more Neanderthal DNA than Europeans due to a second interbreeding event.

However, Harris and Nielson end up concluding that non-Africans historically had a 1 percent loss in biological fitness due to Neanderthal genetics. Moreover, a better immune system came from Neanderthal genetics. Skin color is another trait inherited from Neanderthals as well.

Along with the acquisition of deleterious Neanderthal alleles, early Eurasians also encountered the same environment as the Neanderthals. Those selection pressures, along with interbreeding due to small bands lead to a decrease in the number of children had. Fewer children are easier to care for as well as show more attention to. All of these variables in that environment lead to fewer children produced. It’s a better evolutionary strategy to have fewer children in more northerly climes than in more southerly ones due to the differing selection pressures. Environmental effects are also one reason why birthrates are lower for populations that evolved in northerly climes (Neanderthals and post-OoA hominids). Harsh winters lead to a decreased population size, as evidenced by the Inuit and Eskimoes, which their low population size didn’t allow for selection for high IQ despite having the same brain size as East Asians.

I couldn’t help but think that, yet again, for the second time in two weeks, one of JP Rushton’s theories was confirmed. This confirms one of the many variables of Rushton’s r/K Selection Theory. Just like I covered how Piantadosi and Kidd corroborated Rushton’s theory of brain size and earlier child birth. Neanderthals had bigger brains than we do today, and knowing what we know about the correlation between IQ, brain size and early childbirth, I would assume that Neanderthals also had earlier childbirths as well,.

Along with these deleterious gene variants from Neanderthals, other variables that contribute to the decline in Eurasian populations also include higher IQ as well, as JP Rushton says, is an extreme way to have control over their environment and individuality. These traits are seen in higher IQ populations in comparison to lower IQ populations. We could also make the inference that since Eurasian children have bigger heads, that multiple childbirths would be taxing on the Eurasian woman’s birth canal while it would be less taxing on the African woman’s.

This study also shows that Neanderthals also had less offspring due to being more intelligent. They had bigger brains than we do today, and since we know that higher IQ is correlated with fewer children conceived, we can say that they were pretty damn smart (they buried their dead 50,000 years ago. There was also a recent discovery of a 176,500-year-old Neanderthal constructions in a French cave).  A main cause for the current trend in birthrates in Eurasian populations is due interbreeding with Neanderthals. These events also attributed more to the decline of the Neanderthals.

Deleterious Neanderthal alleles are yet another reason for lower Eurasian birthrates, which shows = that the current trend currently happening in the world with these populations is natural and evolutionarily based. I’ve said a few times that by showing positive things to women on television will increase the white birth rate, with Rushton cites National Socialist Germany as one example. By showing women happy with children, this lead to a massive boom in the German population. To ameliorate the effects of low natural birth rates, these positive things need to be shown on television to women to start to reverse the effects of low natural childbirths.

It’s been a great month for Rushton’s theories, with two of them being corroborated in one month. It’s only a matter of time before the denial of human nature is completely discarded from modern science. As the data piles up on human genetic diversity we will not be able to deny these clearly evident factors any longer.

Individual and Racial Differences in IQ and Allele Frequencies

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In the past 100 years since the inception of the IQ test there have been racial differences in test scores. What causes these score differences? Genetics? Environment? Both? Recently it has come out that populations do differ in allele frequencies that affect intelligence. David Piffer’s “forbidden paper on population genetics and IQ” was rejected by the new editor of the journal Intelligence. In the paper, he shows how IQ alleles vary in frequency by population. One reviewer even said it should not be put up for review, which Piffer believes there was a hidden agenda or a closed minded attitude. He even puts reviewers comments and responds to them. He says science should be transparent, which is why he’s showing the researchers’ comments on his paper.

His December, 2015 paper titled: A review of intelligence GWAS hits: Their relationship to country IQ and the issue of spatial autocorrelation shows that there are differing allele frequencies in which IQ between populations that affect IQ which are then correlated highly with average IQ by country (r=.92, factor analysis showed a correlation of .86). There was also a “positive and significant correlation between the 9 SNPs metagene and IQ”(pg. 45). However, Piffer does conclude that since the 9 alleles are present within all populations (Africans, Latin Americans, Europeans, South Asians, and East Asians) that the intelligence polymorphisms don’t appear to be race-specific, but were already present in Homo Sapiens before the migration out of Africa. He then goes on to say that it’s extremely likely that the vast majority of alleles were subject do differential selection pressure which lead increases in cognitive abilities at different rates rates in different geographical areas (pg. 49). It’s of course known that differing populations faced differing selection pressures which then lead to genotypic changes which then affected the phenotype. It’s not surprising that genes that correlate strongly with intelligence have differing frequencies in different geographical populations; it’s to be expected with what we know about evolution and natural selection. Below is the scatter plot showing the relationship between polygenic score GWAS (Genome Wide Association Studies) hits and IQ:

Scatter plot IQ-polygenic score

The fact that these differences exist should not come as a shock to those who want to seek the truth, but as seen with how David Piffer didn’t even get consideration for a revision, this shows the bias in science to studies such as this that show racial differences in intelligence exist.

Piffer’s data also corroborates Lynn and Meisenberg’s (2010) finding of a correlation of .907 with measured and estimated IQ. This shows that the differing allele frequencies affect IQ, which then affect a countries GDP, GNP, and over all quality of life.

With a sample with a huge n (over 100,000 subjects) cognitive abilities tests were performed on verbal-numerical reasoning, memory and reaction time (a huge correlate for IQ itself, see Rushton and Jensen, 2005). Davies et al (2016) discovered that there were significant genome-wide SNP based associations in 20 genomic regions, with significant gene-based regions on 46 loci!! Once we find definitive proof that intelligence differences vary between individuals, as well as the loci and genomic regions responsible, we can then move on to difference in allele frequency in depth (which Piffer 2015 was one of the starts to this project).

Moreover, genes that influence intelligence determine how well axons are encased in myelin, which is the fatty insulation that coats our axons, allowing for fast signaling to the brain. Thicker myelin also means faster nerve impulses. The researchers used HARDI to measure water diffusion in the brain. If the water diffuses rapidly in one direction, that shows the brain has very fast connections. Whereas a more broad diffusion would indicate slower signaling, thus lower intelligence. It basically gives us a picture of an individuals mental speed. Thinking of reaction time tests where Asians beat whites who beat blacks, this could possibly show how differing process times between populations manifest itself in reaction time. Since myelin is correlated with fast connections, we can make the inference that Asians have more than whites who have more than blacks, on average. The researchers also say that it’s a long time from now, but we may be able to increase intelligence by manipulating the genes responsible for myelin. This leads me to believe that there must be racial differences in myelin as well, following Rushton’s Rule of Three.

Since the mother’s IQ is the best predictor of the child’s IQ, this should really end the debate on its own. Sure on average, intelligent black mothers would birth intelligent children, but due to regression to the mean, the children would be less intelligent than the mother. JP Rushton also says that regression works in the opposite way. Both blacks and whites who fall below their racial means will have children who regress to the means of 85 and 100 respectively, showing the reality of the genetic mean in IQ between the races.

Why would differing allele frequencies lead to the same cognitive processes in the brain in genetically isolated populations? I’ve shown that brain circuits vary by IQ genes, and populations do differ in this aspect, like all other differing genotypic/phenotypic traits.

East Asians have bigger brains, as shown by MRI studies. Rushton and Rushton (2001) showed that the three races differ in IQ, brain size, and 37 different musculoskeletal traits. We know that West Africans and West African-descended people have genes for fast twitch muscle fibers (Type II) (Nielson and Christenson, 2001). Europeans and East Asians have slow twitch muscle fibers (Type I) for strength and endurance. (East Africans have this as well, which allows for ability to run for distance, which fast twitch fibers do not allow for. The same is true for slow twitch fibers and sprinting events.) Bengt Saltin showed that European distance runners have up to 90 percent slow twitch fibers (see Entine, 2000)! So are genetic IQ differentials really that hard to believe? With all of these differing variables in regards to intelligence that all point to a strong genetic cause for individual differences in other genes that lead to stark phenotypic differences between the races, is it really not plausible that populations differ in intelligence, which is largely inherited?

Is it really plausible that differing populations would be the same cognitvely? That they would have the same capacity for intelligence? Even when evolution occurred  in differing climates?  The races/ethnicities differ on so many different variables with differing genes being responsible for it. Would IQ genes really be out of the question? Evolution didn’t stop from the neck up. Different populations faced different selection pressures, so different human traits then evolved for better adaption in that environment. Different traits clearly developed in genetically isolated populations that had no gene flow with each other for tens of thousands of years. These differing evolutionary environments for the races put different pressures on them, selecting some for high IQ alleles and others for low IQ alleles.

We are coming to a time where intelligence differences between populations will become an irrefutable fact. With better technology to see how differing genes or sets of genes affect our mind as well as physiology, we will see that most all human differences will come down to differing allele frequencies along with differing gene expression. Following Rushton’s simple rule based on over 60 variables, East Asians will have the most high IQ alleles followed by Europeans and then blacks. The whole battery of different cognitive abilities tests that have been conducted over the past 100 years show us that there are differences, yet we haven’t been able to fully explain it by GWAS and other similar techniques. Charles Murray says within the next 5 to 10 years we will have definitive proof that IQ genes exist. After that, it’s only a matter of time before it comes out that racial differences in IQ are due to differing allele frequency as well as gene expression.

More g Denialism and more Gould Refuting

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It seems like every day something new comes out that attempts to discredit the reality of g (This paper came out in 2012.). Steven Jay Gould (in)famously wrote in The Mismeasure of Man:

The argument begins with one of the fallacies—reification, or our tendency to convert abstract concepts into entities (from the Latin res, or thing). We recognize the importance of mentality in our lives and wish to characterize it, in part so that we can make the divisions and distinctions among people that our cultural and political systems dictate. We therefore give the word “intelligence” to this wondrously complex and multifaceted set of human capabilities. (emphasis mine)

Which is the same thing that the researchers of the paper Fractioning Human Intelligence said to The Independent:

“The results disprove once and for all the idea that a single measure of intelligence, such as IQ, is enough to capture all of the differences in cognitive ability that we see between people,”

“Instead, several different circuits contribute to intelligence, each with its own unique capacity. A person may well be good in one of these areas, but they are just as likely to be bad in the other two,”

Just like The Mismeasure of Man is “the definitive refutation to the argument of The Bell Curve”, right?

In the above paper, they cite Gould twice writing:

It remains unclear, however, whether population differences in intelligence test scores are driven by heritable factors or by other correlated demographic variables such as socioeconomic status, education level, and motivation (Gould, 1981; . . .

They have been shown over numerous studies that population differences in intelligence are driven by heritable factors (Rushton and Jensen, 2005Lynn and Vanhanen, 2006Winick, Meyer, and Harris, 1975Frydman and Lynn, 1988Rushton, 2005)

More relevantly, it is questionable whether they relate to a unitary intelligence factor, as opposed to a bias in testing paradigms toward particular components of a more complex intelligence construct (Gould, 1981;

I will prove the existence of in this article. There is also an empirical basis for the factor.

It’s getting old now that researchers still think that they can “disprove g”, as a multitude of studies have already corroborated Spearman’s hypothesis as an empirical fact. That is, applying the scientific method, using the same hypothesis over a multitude of different studies and testing those predictions by experiment or further observation and modify the hypothesis when new information comes to light.  Then, repeat the aforementioned steps until there are no discrepancies between the theory and experiment/observations.Then when consistency is obtained it then becomes a theory that provides a coherent set of premises that explain a class of events.

How many times has the Hampshire et al hypothesis been corroborated? I doubt it has been corroborated as many times as Spearman’s hypothesis has.

As I said the other day, Jensen tested Spearman’s hypothesis on 25 large independent samples, with each sample confirming Spearman’s hypothesis. Even matching blacks and whites for SES didn’t diminish the effect. Jensen then concludes that the overall chance for Spearman’s hypothesis being wrong is over 1 in a billion. Pretty high odds.

Even then, if this study were to be replicated the amount of times that Spearman’s hypothesis has, it still wouldn’t disprove g. 

On page 558-559 of the Afterword to The Bell CurveCharles Murray responds to many of Gould’s criticisms of the book. He writes:

He (Gould) continues: “The fact that Herrnstein and Murray barely mention the factor-analytic argument forms a central indictment around The Bell Curve and is an illustration of its vacuousness.” Where, Gould asks, is the evidence that “captures a real property in the head?

Murray states that they “barely brought up the factor-analytical argument” because it was out of date; Gould was using statistics on g that were 50 + years old. Also, a reviewer of his book for the journal Nature said that Gould’s “discussion of the theory of intelligence stops at the stage it was more than a quarter of a century ago.” Gould was using old arguments, and, as Arthur Jensen states in his response to Gould:

Of all the book’s references, a full 27 percent precede 1900. Another 44 percent fall between 1900 and 1950 (60 percent of those are before 1925); and only 29 percent are more recent than 1950.

More than half of Gould’s references in The Mismeasure of Man are outdated by more than 50 years. Clearly, he was attempting to denigrate the old studies of intelligence, i.e., phrenology, even though this recent paper in the journal Nature recently said:

The genomic regions identified include several novel loci, some of which have been associated with intracranial volume

So, we have several loci that are associated with intracranial volume; this shows that those skull studies of yesteryear weren’t crazy. Moreover, the fact that Rushton and Ankney (1996) “reviewed 32 studies correlating measures of external head size with IQ scores or with measures of educational and occupational achievement, and they found a mean r  .20 for people of all ages, both sexes, and various ethnic backgrounds, including African Americans” shows that there is a correlation of .20, albeit not too high but there, with external head size and IQ. This shows that Gould’s argument on phrenology is bunk, as modern studies confirm that there is a slight correlation between head size and IQ, and therefore g. 

The fact that researchers are still bringing up Gould’s arguments on show that there really is no good argument to discount it. Basically, any and all arguments that attempt to discredit are bunk as Spearman’s hypothesis has been empirically verified:

Conclusion: Mean group differences in scores on cognitive-loaded instruments are well documented over time and around the world. A meta-analytic test of Spearman’s hypothesis was carried out. Mean differences in intelligence between groups can be largely explained by cognitive complexity and the present study shows clearly that there is simply no support for cultural bias as an explanation of these group differences. Comparing groups, whether in the US or in Europe, produced highly similar outcomes. 

Along with Jensen’s 25 large independent studies that showed that the probability that Spearman’s hypothesis is false is 1 in a billion, this proves that Spearman’s hypothesis is an empirical scientific fact.

Newman and Just, (2005) state in verbal and spatial conditions that the frontal cortex revealed greater activation for high-in comparison to low-g, supporting the idea that g reflects functions of the frontal lobe. The “seat” of general intelligence is the prefrontal cortex (Cole, et al, 2011Roth, 2011). This can also be verified with MRI scans that show that those who have higher have bigger prefrontal cortexes than those with lower g. 

Moreover, the fact that Colom, et al (2006) show that in their sample that neuroanatomic areas underlying the factor could be found across the entire brain including the frontal, parietal, temporal and occipital lobes, shows that this factor is present throughout the brain and all are correlated with and work together in concert to manifest intellectual ability.

Other researchers have also used the method of correlated vectors on functional Magnetic Resonance Imaging (fMRI), which measures brain activity by detecting changes associated with blood flow. This technique is proven useful due to the fact that cerebral blood flow and neuronal action are correlated. Lee, et al write:

In conclusion, we suggest that higher order cognitive functions, such as general intelligence, may be processed by the coordinated ability may be attributable to the functional facilitation rather than the structural peculiarity of the neural network for g. In addition, our results demonstrated that the posterior parietal regions including bilateral SPL and right IPS could be the neural correlates for superior general intelligence. These findings would be the early step toward the development of biological measures of g which leads to new perspectives for behavior interventions improving general cognitive ability.

They also used the MCV to find that the frontal and parietal lobes are associated with g. Even these studies show that shows up throughout the brain and not in one solitary spot (though, the PFC is still the seat of intelligence), this shows yet another biological basis for g.

Hampshire, et al write:

Thus, these results provide strong evidence that human intelligence is a construct that emerges from the functioning of anatomically dissociable brain networks.

However, with the above studies confirming that the seat of intelligence is the prefrontal cortex, along with great ability possibly be attributable to the functional facilitation rather than the structural peculiarity of the neural network for g, this shows, along with the study proving Spearman’s hypothesis, that is a real and measurable thing. g’s seat is the prefrontal cortex, and exceptional may possibly be attributed to the functional facilitation of the neural network for g . What all of these studies show is that all though the Hampshire paper showed how they “demonstrate that different components of intelligence have their analogs in distinct brain networks.” that a) higher order cognitive functions may be processed by the coordinated activation of widely distributed brain areas (disproving the above quote), b) the seat of is the prefrontal cortex, c) those with more have bigger prefrontal cortexes and therefore bigger brains since the prefrontal cortex is the ‘seat’ of intelligence and d) Spearman’s hypothesis has been corroborated numerous times by many different researchers not named Arthur Jensen.

Highfield (one of the researchers in the study) ends the article as follows:

“We already know that, from a scientific point of view, the notion of race is meaningless. Genetic differences do not map on to traditional measurements of skin colour, hair type, body proportions and skull measurements.

This is something that never ends; it always comes up no matter how many times it’s been said. People can say “race is a social construct” all they want, it doesn’t make it true as there is a biological reality to race.

Now we have shown that IQ is meaningless too,” Dr Highfield said.

IQ is not biased, nor is it “meaningless“.

When will people learn not to cite men who have smeared their legacy in an attempt to defame men who they disagreed with ideologically? Citing Steven Jay Gould in 2016 shows a bias to want to discredit as a main factor for many things in life including SES, educational attainment, wealth attainment and so forth. The factor is a measurable thing, with the seat of the factor being the prefrontal cortex. No amount of attempting to dispute this factor can be done, as it’s been empirically verified numerous times.