Brain and Evolution

Evolutionary and ecological perspectives on why brains exist, allometry, hominin brain evolution, constraints on brain size, and whether human brains are special.

Topics

Biological fitness and the reason for brains
Body size and brain size across species: allometric relationships
Hominin brain evolution
What factors facilitate and what factors constrain brain size
- These include hypotheses concerned with ecology and diet, cognitive buffering, sexual selection, bipedalism, climate change, altricial birth, and the cognitive demands of living in social groups.
Relating brain size to function: morbidity, memory, intelligence
Are human brains special?

Preparation for class

The topic of the first lecture is not covered in Purves Neuroscience (6th ed.). I have therefore assigned a paper by Dunbar entitled The social brain hypothesis and its implications for social evolution. This will introduce some of the issues I will discuss in lecture. In reading this paper, do not concern yourself with details; aim for the gist of the main points.

I have linked a Dunbar article here and have also uploaded it into the resources section of Canvas.

Topic slide

Alison Jolly (1937–2014) was a primatologist and conservationist who received her Ph.D. from Yale University in 1962. She worked primarily with lemurs on Madagascar, and was perhaps the first to suggest that social interactions were a driving force for the evolution of primate intelligence. She wrote several books including Lucy’s Legacy: Sex and Intelligence in Human Evolution. Interested students can read her NY Times obituary and a remembrance from the Duke Lemur Center.

Robin Dunbar (b. 1947) is a professor at Oxford University and Director of the Institute of Cognitive and Evolutionary Anthropology. Dunbar built upon the work of Alison Jolly, Nicholas Humphrey, Byrne and Whiten, and others to develop the Social Brain Hypothesis. This hypothesis asserts that the evolutionary pressure to keep track of social interactions within a group provided the fitness advantage for larger brains.

Evolutionary perspective for brains

Evolutionary biologist Theodosius Dobzhansky (1900–1975) famously wrote:

Nothing in Biology Makes Sense Except in the Light of Evolution.

Seen in the light of evolution, biology is, perhaps, intellectually the most satisfying and inspiring science. Without that light it becomes a pile of sundry facts — some of them interesting or curious but making no meaningful picture as a whole.

Evolution provides a perspective for understanding the brain. We should consider what “problem” is solved by having a brain, and how having a brain — or a larger brain — improves biological fitness.

Biological fitness refers to reproductive success: an organism passing its genes on to the next generation. From the perspective of evolution, this is the only meaningful outcome measure of an organism’s success. Of course, biological fitness presupposes survival — at least long enough to reproduce. Thus, the abilities to obtain nutrients and escape predation generally improve biological fitness. However, when there is a conflict between survival and reproductive success, the latter dominates. Indeed, in many species, mating is fatal (typically for the male).

We will discuss evolution throughout the semester, and we will examine evolution with respect to function. But we should be careful not to think of changes in brain over the course of evolution as for a particular function. Evolution does not plan or anticipate. Rather, we will consider the environmental pressures experienced by individual members within a species that might select for particular structural/functional changes should those changes occur.

Taxonomies

Although not a recurring theme in this class, I will occasionally make reference to taxonomic nomenclature for life forms. For convenient reference, the standard hierarchy is presented below:

Kingdom
Phylum
Class
Order
Family
Genus
Species

There are subclassifications and sub-subclassifications for many of these descriptors. In the example below for humans, these are indented.

Kingdom (Animalia)
Phylum (Chordata)
- Subphylum (Craniata; i.e., Vertebrata)
Class (Mammalia)
Order (Primates)
- Suborder (Haplorhini)
  - Infraorder (Simiiformes)
Family (Hominidae)
- Subfamily (Homininae)
  - Tribe (Hominini)
Genus (Homo)
Species (sapiens)
- Subspecies (sapiens)

So, we see that a human is a chordate, a vertebrate, a mammal, a primate, and a hominid (Great Ape). We are also the only living species of the hominins, and the only living species of the genus Homo. As we will see below, this was not always the case.

In a later lecture, we will discuss the commonalities of the vertebrate brain plan. For future reference, vertebrates are subdivided into five major classes:

fishes
amphibians
reptiles
birds
mammals

Genotypes and phenotypes

Let’s review the distinction between genotypes and phenotypes. Changes in an organism’s DNA or genes (its genotype) can cause changes to the organism’s structure or morphology (its phenotype), which are reflected in function and behavior. Mutations are changes in DNA and can occur for a number of reasons such as exposure to radiation, exposure to mutagenic chemicals, DNA copying errors, and viral infections.

Imagine that a genetic mutation within some individuals of a species causes brain size to be slightly larger. As a consequence, the species would exhibit variation in brain size. If having a larger brain confers an advantage that enables those individuals to survive and reproduce more successfully than smaller-brained individuals, then those larger-brained individuals will be more successful in passing their genes to progeny (i.e., improved biological fitness). In that case, the percentage of the population with larger brains would increase. However, if the larger brain requires more energy and nutrients, then individuals with a larger brain might be at a disadvantage, and the percentage of individuals with larger brains might decrease in the population. Having a larger brain may not confer any advantage to individuals within the species until and unless an environmental challenge makes it beneficial.

Why have a brain?

The single-cell amoeba has no nervous system or brain. Nevertheless, it responds to stimuli and moves adaptively. Its surface membrane is in direct contact with its environment, and the membrane responds to environmental signals. Thus, there is no need to create an internal representation of the external world.

Adaptive movement

Adaptive movement is a key advantage provided by a brain. Adaptive movement can assist an organism in finding a mate, finding food, and escaping predation. It links external sensory events with motor commands to move toward rewarding sensory events (such as food sources) and away from punishing events (such as predators).

Cost of brain?

Consider the sea squirt, a marine member of the Phylum Chordata. Although an invertebrate, its larval stage has a notochord that resembles a spinal cord and a collection of neurons (a neural ganglion) that constitute a primitive nervous system. Sea squirt larvae are tadpole-like and swim adaptively to find an anchoring spot. However, once anchored, the sea squirt becomes sessile and absorbs its proto-nervous system. An adult sea squirt subsists by drawing water containing microscopic food sources through its internal chambers. It is hermaphroditic and produces both sperm and egg, which are released into seawater. It can also reproduce asexually by budding.

Once adaptive movement is no longer required and an anchoring point is found, the sea squirt’s ganglionic “brain” becomes expendable. This implies that there is a cost to having a brain. Brains consume energy, and devoting a portion of an organism’s limited energy to a brain without a corresponding increase in biological fitness is not adaptive but rather maladaptive. We will consider the energy costs of the brain further below.

Is the brain entirely devoted to sensation and movement?

As we will learn in detail, the brain has regions devoted to receiving and integrating sensations from the environment, and regions devoted to planning and organizing movements. For example, humans have ~20 square feet of skin sending myriad sensory signals to the brain and ~650 named skeletal muscles to control. However, across mammals, the proportion of cortex devoted to primary sensory and motor processes diminishes as one moves from simpler to more complex species. I illustrated this progression in lecture with a slide showing the proportion of the brain devoted to primary sensory and motor functions from hedgehogs to prosimians to humans.

Why have a larger brain?

Brains vary greatly in size — humans have a big brain, but we don’t have the absolute biggest brain, or the most convoluted brain (i.e., by folding the brain’s surface, more surface can be fit into a given volume; think of crumpling a sheet of tissue to fit a small space).

Nicholas Humphrey (b. 1943) is a psychologist with a strong evolutionary perspective. He wrote:

Nature is surely at least as careful an economist as Henry Ford. It is not her habit to tolerate needless extravagance in the animals on her production lines: superfluous capacity is trimmed back, new capacity added only as and when it is needed. We do not expect therefore to find that animals possess abilities which far exceed the calls that natural living makes on them. If someone were to argue — as I shall suggest they might argue — that some primate species (and mankind in particular) are much cleverer than they need be, we know that they are most likely to be wrong.

Humphrey’s point is that evolution is unlikely to bestow costly capacities unless they are adaptive (i.e., increase biological fitness).

Is a larger brain epiphenomenal? Allometry

Perhaps brains get bigger because bodies get bigger, and brain size simply scales with body size. Arguably, a larger body has a larger sensory surface to receive input (e.g., more cutaneous receptors) and more muscles to control. Is the larger brain thus epiphenomenal (a secondary effect, not causative)? Gould and Lewontin famously cautioned scientists to be vigilant for epiphenomenal explanations and to resist the follies of overly enthusiastic adaptationism and “just-so stories” in their metaphor of the Spandrels of San Marco.

One way to decide this issue is to see how different body parts (such as the brain) scale against other body parts or variables. A classic example is the relationship of body size and metabolism examined by Max Kleiber. This relationship is well described by a power law; if the quantities are plotted on a log–log scale, the power-law relationship is evident as a straight line whose slope equals the exponent.

The scientific approach called allometry studies the relative sizes of body parts. If you plot body size vs. brain size (on a log–log plot) across species, you would expect a straight-line relationship if a larger brain is simply a secondary effect of body size. Such plots do reveal an overall power-law relationship between body size and brain size — i.e., much of the variation in brain size across species can be attributed to body size.

What is most interesting, however, are the deviations of different taxa from that straight line. Deviations can be below the line expected by strict isometry (negative — hypoallometry) or above the line (positive — hyperallometry).

Wikipedia has a helpful summary of key terms (see here):

Isometric scaling happens when proportional relationships are preserved as size changes during growth or over evolutionary time.
Allometric scaling is any change that deviates from isometry.
A classic example is the mammalian skeleton: skeletal structure becomes much stronger and more robust, relative to body size, as size increases.
If a property is smaller than predicted values, this is negative allometry or hypoallometry.
Conversely, larger-than-predicted values indicate positive allometry or hyperallometry.

In lecture, I showed allometric plots of brain weight vs. body weight. The figures showed two linear relationships — one for mammals and one for lower vertebrates (fishes, amphibians, reptiles). One difference between mammals and fishes/reptiles is that the latter lack a six-layered cortex. This shifts the intercept of those lines (the point on the Y-axis representing brain weight).

Encephalization quotient (EQ)

In 1973, UCLA psychologist Harry Jerison published the influential book Evolution of the Brain and Intelligence, which develops the concept of the Encephalization Quotient (EQ).

A simple way to think of EQ is that it represents how much bigger or smaller a species’ brain is than its predicted size. The prediction is derived from the brain sizes of other animals of the same body size (the regression line of body size vs. brain size for a reference group — e.g., all vertebrates, all mammals, or all primates). A more technical description is here. Regardless of the reference group, humans have the largest EQ.

EQ systematizes brain/body size relationships across many species. But what does it represent functionally — for example, does a larger EQ translate into more intelligence? Robert Deaner and colleagues have argued that among primates, absolute brain size (not scaled by body size) best predicts cognitive ability, not EQ.

Some researchers have suggested that EQ was devised to make the human brain appear special. This perspective is captured in a quote from Ralph Holloway (2015):

Just as the human animal is curious, it is also vainglorious, always trying to find a measure that places it at the top. Thus we can fabricate a device, the Encephalization Coefficient or EQ, which shows that relative to any database, the human animal is the most encephalized animal living.

EQs do not evolve, only brain weight/body weight relationships do, and EQs are simply a heuristic device enabling comparisons between taxa; they have no reality outside of the database chosen, or species within a taxa, and are not designed to discuss within-species variation. For example, female humans are “more” encephalized than males, given their smaller body sizes, more body fat which is not innervated, and smaller brains, but the relationship might be simply a statistical artifact with no known gross behavioral manifestation given the sexes’ equal overall intelligence.

It is notable that humans do not have the largest brain in absolute weight, volume, or percentage of body mass. A blue whale’s brain weighs about 15 pounds compared to 3 pounds in humans — but a blue whale can weigh ~330,000 pounds compared to our ~150 pounds. Thus, a blue whale is ~2,000× a human’s body weight and ~5× its brain weight. Put another way, the ~3-pound human brain is about 2% of a human’s lean body mass, while the blue whale’s brain is ~0.5% of its body weight. An elephant weighs ~12,000 pounds and its brain ~12 pounds (80× body size, 4× brain size relative to humans). By contrast, the mouse brain is ~10% of its body mass. Among insects, the ant’s brain accounts for ~17% of body weight.

How to compare brains among such widely differing species is problematic. A more reasonable approach is to compare brain sizes among closely related species, where differences in brain function and behavioral repertoire can also be more easily compared.

Evolution of the hominin brain

This is a course about the human brain, so the evolution of the brains of hominids and hominins is of particular interest. Let’s define some terms and establish a rough timeline. Hominids are members of the family Hominidae (the Great Apes): Pongo (orangutans), Gorilla (gorillas), Pan (chimpanzees and bonobos), and Homo (humans). The great apes diverged from the Lesser Apes (e.g., gibbons) ~12–18 million years ago (mya), which split off from Old World monkeys ~25–30 mya. Primates diverged from other mammals ~55–85 mya.

Within the Hominids, chimpanzees (Pan troglodytes) and modern humans (Homo sapiens) diverged from the lineage leading to modern gorillas ~12 mya. The last common ancestor of humans and chimps lived ~6–8 mya.

Some key temporal relationships are shown in the figure below taken from Encyclopedia Britannica’s article on hominins. Divergence dating is often uncertain and occasionally controversial, determined by fossils, radioactive decay rates, and molecular dating. Thus, the range of dates for the divergence of a species can be considerable, and that variability is expressed in the following figure.

When considering the evolution of species such as chimpanzees and modern humans, remember that humans did not evolve from chimpanzees. Rather, humans and chimpanzees diverged from a common ancestor. Modern chimps and humans have evolved independently for 6–8 million years. Despite that long period of independent evolution, modern humans and chimps have about 98.8% of their DNA in common. This underscores the power of regulatory gene networks: chimps and humans have very similar genes that make similar protein products, but differences in when and for how long genes are expressed can yield very different phenotypes.

The relationship of body and brain size in primates (prosimians, monkeys, apes, humans) compared to other mammals has a power-law relationship with a higher intercept than observed in non-primate mammals. This is shown in the figure below from Schoenemann (2013). Notably, species of Homo (modern and extinct) show a hyperallometric relationship between body and brain size.

Hominins

The members of the lineage that led to modern humans are called hominins. All hominin species are now extinct save for Homo sapiens. This wasn’t always true; for long periods different species of Homo coexisted. Indeed, Homo neanderthalensis coexisted with Homo sapiens in parts of Europe for ~5–8 thousand years until Neanderthals became extinct ~40,000 years ago. There is clear DNA evidence of interactions between these species. Modern humans typically have ~1–4% Neanderthal DNA in their genomes (varying regionally). There are also hypotheses about cultural transmission between these species.

Note

Note. Some researchers refer to Neanderthals as Homo neanderthalensis and others use Homo sapiens neanderthalensis. This reflects a lack of consensus as to whether Neanderthals are a distinct species or a subspecies of Homo sapiens.

Note

Note. Dating of fossils can be controversial and is revised as new techniques emerge. Determination of lineages — and whether a fossil is a member of a known species or a new one — can also be controversial. DNA extraction from fossils has been revolutionary, but most successful in colder climates (e.g., Siberia). Recovery is relatively unsuccessful in warmer regions, including equatorial Africa where the hominin lineage began, creating an unfortunate regional bias in these data.

Brain changes over four million years of hominin evolution

For our purposes, the most interesting aspect of hominin evolution is the growth in brain size. The brain quadrupled in size from the earliest hominins that diverged from the lineage leading to chimpanzees. Some brain growth was allometric (scaled with body size). However, much of the growth was hyperallometric — greatly exceeding what would be expected from body size alone.

The figure below from Schoenemann (2013) shows evolutionary time (log scale) on the X-axis and cranial capacity (linear) on the Y-axis. Different hominin species are indicated by different symbols (legend at right). Vertical lines show the range for Homo sapiens, Great Apes, and other primates. Particularly striking is an acceleration in brain growth beginning ~2.5 mya.

Did hominin brains get smaller?

A close examination of brain size by evolutionary time suggests a decrease in brain size for Homo sapiens in the recent past. Although distributions overlap, Neanderthal brains are somewhat larger than those of H. sapiens. There are also shape differences (Neanderthals more elongated; H. sapiens more globular), possibly reflecting changes in association cortices (parietal, temporal). Neanderthals were also larger in body size.

A recent paper by Zollikofer and colleagues argues that changes in the skull of H. sapiens over the past 200,000 years were driven not by changes in brain size or shape, but by diet: facial shape and musculature changed as diets changed, producing a smaller, more child-like face.

However, the decrease in brain size may have occurred for H. sapiens over the past ~30,000 years (since the end of the last ice age), when Neanderthals were already extinct. While body sizes did get slightly smaller over that period, the brain change was disproportionate to body size. There is no consensus about why (or even whether) H. sapiens brains have gotten smaller. One intriguing hypothesis by DeSilva and colleagues (2022) is that increases in social living purged the most aggressive individuals and off-loaded decision-making to the group — a form of self-domestication, paralleling the ~25% brain-size reductions seen in domesticated animals relative to wild counterparts.

Why did brains get larger?

Data above indicate that hominin brains became larger relative to body size, with an acceleration beginning ~2.5 mya with Homo habilis and Homo erectus. What factors led to this growth, and how does a larger brain improve biological fitness?

Asking why is complicated in evolution. Brain size changes occurred because some animals experienced mutations that resulted in larger brains, and environmental pressures favored those mutations. When I ask why, I mean: what advantage did a larger brain confer that improved fitness? With that caveat, consider four hypotheses for how larger brains could improve fitness within and across species.

Foraging and dietary hypotheses

Animals require energy in the form of food and nutrients to survive long enough to reproduce. A larger brain could be an adaptation for finding food and/or storing (caching) food. In lecture, I provided examples from birds and monkeys, briefly recapped below.

Monkeys. Howler monkeys are generalist leaf eaters (folivorous), while spider monkeys are fruit specialists (frugivorous). Despite similar body size, frugivorous spider monkeys have larger and more folded brains, presumably due to increased neural processing associated with foraging, spatial memory for fruit locations, improved vision to discriminate food from background, and the cognitive/motor effort involved in extraction (e.g., cracking nuts).
Birds. Among corvids and titmice, species that hide (cache) food for later have a larger hippocampus (implicated in spatial memory and navigation) than closely related species that do not cache. Some birds (e.g., mountain chickadees) survive winter on cached seeds, making spatial memory essential for survival — a direct link between hippocampal size and fitness.

Diet and the expensive tissue hypothesis

An improved diet generates more energy. Two factors have been identified in hominin evolution that increase energy extraction from food: meat consumption and cooking. Meat is energy-rich; cooking increases palatability and digestibility, yielding more calories and nutrients than raw foods.

A diet dependent on raw plant foods requires a longer alimentary canal, which is an “expensive tissue” — it consumes many calories. A shift to a calorie-rich diet reduces the need for a long gut, which saves calories that can be devoted to the brain. This is the essence of the expensive tissue hypothesis (Aiello and colleagues). While supported in some respects (humans have a much shorter large intestine than other primates), there are inconsistencies in other species.

Nevertheless, the general idea holds: adaptations that reduce the caloric needs of other tissues free calories to support a larger brain. For example, humans have a greater fat-to-muscle ratio than other primates. At rest, a pound of muscle consumes ~3× the calories of a pound of fat. From a comparative perspective, humans are “under-muscled” and “over-brained.”

Cognitive buffer hypothesis

A bit more brain helps when a species is challenged by changes in environment, food supply, etc. In lecture, I noted bird mortality data: bigger-brained birds (corrected for body size) show lower mortality in nature. The mechanisms are uncertain, but many investigators conjecture that larger brains confer behavioral flexibility — an advantage in novel or changing conditions.

Researchers have attempted to measure intelligence across species. The best metrics emphasize flexibility and novel solutions. Using these metrics, intelligence appears to have evolved more than once. There are more- and less-intelligent species within mammals and within birds; note that birds and mammals diverged >300 mya.

Sexual selection hypothesis

Sexual selection is an evolutionary process recognized by Darwin that operates within species and is associated with mate choice and preference; it can work rapidly.

Geoffrey Miller offers a popular account in The Mating Mind.

Sexual selection operates on mate choice within a species.
Competition among males for mating opportunities can alter male morphology.
Female mate choice can quickly differentiate males if preferred traits spread through the population.
Sexual selection can work quickly relative to other evolutionary processes.

The peacock and the Irish Elk are extreme examples: elaborate tails and massive antlers are costly traits that may signal genetic quality to females (e.g., Stephen J. Gould noted healthy Irish Elk antlers could weigh ~40 kg vs. ~20 kg in sickly/malnourished males). Even if the ornaments are not directly useful, they carry information about male health.

Sexual selection can also act on less showy traits. For example, female mountain chickadees appear to choose mates based on spatial navigation ability — essential for winter survival via cached food.

Geoffrey Miller (and others) have argued that a larger brain in humans may be the result of sexual selection, functioning as a kind of ornament. Artistic, athletic, and other high-skill behaviors might signal “good genes” because they are complex and require healthy brains to perform. The analogy is a Swiss watch: accurate time-keeping indicates that all internal parts are functioning perfectly. This line of thought has been used to “explain” social skills in the arts and storytelling. It is interesting, but recall our caveats about adaptationism and spandrels.

Social relationships

In lecture, I highlighted passages from Alison Jolly and Nicholas Humphrey concerning social relationships as selection pressure for more capable brains. This perspective is also shared by Holloway (2015), who writes:

…the major underlying selectional pressures for the evolution of the human brain were mostly social. It was an extraordinary evolutionary “decision” to go with an animal that would take longer to mature, reach sexual maturity later, and be dependent for its food and safety upon its caretakers (parents?) for a longer period of time. The benefits for the animal were many, including a longer learning period, a more advanced, larger, and longer-growing brain, and an increasing dependence on social cohesion and tool making and tool using to cope with the environments that they encountered. Needless to say, language abilities using arbitrary symbol systems were an important ingredient in this evolution.

Holloway continues with two important points:

The fossil record shows us that there was a feedback between the complexity of stone tools (which must be seen as a part of social behavior) and increasing brain size and the expansion of ecological niches. The “initial kick,” however, the process that got the ball rolling, was a neuroendocrinological change affecting regulatory genes and target-tissue hormonal interactions that caused delayed maturation of the brain and a longer growing period, during which learning became one of our most important adaptations.

The first point highlights niche construction: brains evolve in response to environmental pressures, but organisms alter their environments (e.g., with tools), which in turn feeds back into selective pressures. The second is a reminder that causal events in brain evolution are changes to regulatory genes.

So which hypothesis is correct?

The Social Brain Hypothesis helped fuel Social Neuroscience and questions about brain regions specific to social interaction (e.g., amygdala). But the ecological argument (diet, spatial memory, extractive strategies) dismissed by Dunbar has not been convincingly rejected, and explanations based on species-specific ecological/foraging strategies still have support. For example, a 2017 study by DeCasien and colleagues directly compared social complexity and ecological dietary factors in 140 primate species — far more than Dunbar examined — and found strong evidence that dietary factors explained larger brains, with no evidence that social complexity explained additional variance.

This extended conflict between competing hypotheses as new data accumulate is common in science. It often takes time for consensus to emerge. Moribund hypotheses are sometimes revived by new methods. Students wanting “the facts right now” may find this disconcerting, but living with uncertainty is part of science — and often the source of creativity. (Don’t worry: there are plenty of facts we are certain about.)

What limits brain size?

If a larger brain improves fitness, why not larger still? What prevents our brains from expanding to the outsized proportions seen in science fiction?

Energy requirements

Follow the energy: brains are expensive.

Brains are roughly 2% of human lean body weight.
Brain consumes ~20% of adult metabolism.
Brain consumes >60% of infant metabolism.

In lecture, I discussed a simulation showing the brain–brawn trade-off for a typical non-human primate diet. To maintain given body and brain sizes, a certain number of calories must be consumed daily. Gorillas already eat about the maximum number of hours per day possible to maintain their brain–brawn. To change this ratio, diet would need to change (more energy per hour of foraging) and/or energy expenditures reduced. Thus, one important limitation on brain size is its enormous energy requirement.

Sources of increased calories include more meat and cooking. Recent studies also suggest carbohydrates were important: humans have more copies of the amylase gene (which breaks down starches) than chimps. We also discussed ways to save calories: bipedalism, a higher fat-to-muscle ratio, and a smaller gut.

Connectivity

A larger brain means more brain cells. The principal cell is the neuron, and communication is achieved via connections among neurons. As neuron count increases linearly, potential connections scale roughly as (N(N-1)). Even small increases in neuron number can massively increase possible connections.

Connections are made through axons, which have mass, occupy space, and consume energy. If neuron count increased greatly while connections per neuron remained the same, brains would become enormous. Not all species have the same connectivity: for example, rodent brains have more connections per neuron than human brains. It has been argued that a rodent-like connectivity pattern scaled to ~89B neurons (human count) would weigh ~77 pounds. We will discuss constraints and solutions later (sparse connectivity, modularity).

This argument is valid but simplified; other factors influence brain volume and weight beyond neuron number and connectivity. These include neuron packing density, neuron size, and numbers of other cells such as glial cells. A recent summary is provided by Suzana Herculano-Houzel.

Gestational limitations

One often reads (as undisputed fact) about the obstetrical dilemma: human infants are “born premature” relative to other species because a large head at birth is incompatible with a pelvis optimized for bipedalism. I have tried to track down evidence for this “fact” and found little. Recent simulations suggest it may not be true. There are, however, indisputable limitations on the energy costs of gestation.

Maternal energy hypothesis

Human infants are born with ~25% of the neurons they will eventually have; there is considerable brain growth up to ~age 7. As noted earlier, >60% of infant metabolism supports the brain. There is a limit to the calories a mother can provide a developing fetus, which may determine when infants are born. After birth, the infant still requires many calories to continue developing, and this may select for brains that support socially adept behaviors. Examples include:

Cooperative breeding, which helps provide the calories required by developing infants.
The grandmother hypothesis, whereby non-reproducing members of the group contribute to infant development.
Specialized food acquisition behaviors (hunter–gatherer, farming).

Large brain summary

There is probably no single reason the human brain is so large. It is likely the result of interactions among multiple factors such as:

Improved diet through foraging and the discovery of cooking
Reduced calorie costs of bipedalism compared to knuckle-walking
Cognitive buffering
Maternal subsidies (e.g., grandmothering) and cooperative breeding
Managing social relationships

Are human brains special?

There has been interest since antiquity in what makes humans special or unique among animals. I gave the example of the debate between Huxley and Owen about the uniqueness of the hippocampus. Although their debate has been misrepresented, Owen argued that the hippocampus (among other structures) was uniquely human and not found in the gorilla. This is incorrect: the hippocampus is an ancient structure found in all mammals (and many other species). Debates continue about “uniquely human” brain areas. The spindle cell (von Economo neuron) was once thought to be uniquely human; it is not (it has been found in elephants and other animals). Because of its relatively restricted location, it was even proposed to be responsible for consciousness. My advice: be skeptical of claims for human uniqueness. Evolution rarely works that way.

Nevertheless, humans appear to have capabilities unmatched in magnitude. Humans deviate from the linear body–brain relationship and have the largest EQ. Are human capabilities simply a matter of quantity (more brain) rather than a qualitative difference? One way to frame this is to ask whether the human brain is simply a scaled-up primate brain. The issue remains contentious.

As discussed above, relative brain size is larger in hominins (extant and extinct) than in great apes. There are reports that different brain structures in humans show hyperallometry — e.g., some argue neocortex size is hyperallometric compared to other primates.

A long-standing “fact” held that the frontal lobes made humans human — appearing hyperallometric and involved in high-level abstract behavior. More recent data suggest that frontal lobes are actually isoallometric — about the size expected for a primate of human body size. However, prefrontal gyrification appears hyperallometric in humans (i.e., proportionally more folded). Whether gyrification is merely a way to pack surface area or has additional functional consequences is unclear.

The debate about whether the human brain is unique in kind or just in degree continues. See Suzana Herculano-Houzel for a recent review. My own view is that a quantitative increase of sufficient magnitude can lead to an apparent qualitative change in function.

Revisions

This chapter was last updated on September 20, 2025.

Topics

Preparation for class

Topic slide

Evolutionary perspective for brains

Taxonomies

Genotypes and phenotypes

Why have a brain?

Adaptive movement

Cost of brain?

Is the brain entirely devoted to sensation and movement?

Why have a larger brain?

Is a larger brain epiphenomenal? Allometry

Encephalization quotient (EQ)

Evolution of the hominin brain

Hominins

Brain changes over four million years of hominin evolution

Did hominin brains get smaller?

Why did brains get larger?

Foraging and dietary hypotheses

Diet and the expensive tissue hypothesis

Cognitive buffer hypothesis

Sexual selection hypothesis

Social relationships

The Social Brain Hypothesis

So which hypothesis is correct?

Food production and social cooperation are interdependent

What limits brain size?

Energy requirements

Connectivity

Gestational limitations

Maternal energy hypothesis

Large brain summary

Are human brains special?

Revisions