Pattern and process in hominin brain size evolution are scale-dependent

Abstract

A large brain is a defining feature of modern humans, yet there is no consensus regarding the patterns, rates and processes involved in hominin brain size evolution. We use a reliable proxy for brain size in fossils, endocranial volume (ECV), to better understand how brain size evolved at both clade- and lineage-level scales. For the hominin clade overall, the dominant signal is consistent with a gradual increase in brain size. This gradual trend appears to have been generated primarily by processes operating within hypothesized lineages-64% or 88% depending on whether one uses a more or less speciose taxonomy, respectively. These processes were supplemented by the appearance in the fossil record of larger-brained species and the subsequent disappearance of smaller-brained and taxa. When the estimated rate of within-lineage ECV increase is compared to an exponential model that operationalizes generation-scale evolutionary processes, it suggests that the observed data were the result of episodes of directional selection interspersed with periods of stasis and/or drift; all of this occurs on too fine a timescale to be resolved by the current human fossil record, thus producing apparent gradual trends within lineages. Our findings provide a quantitative basis for developing and testing scale-explicit hypotheses about the factors that led brain size to increase during hominin evolution.

The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area

“…The PGS for global SA ( p -value threshold = 0.005 yielding 266 LD-independent SNPs) was 0.035, indicating that derived alleles within the fetal brain HGEs are associated with 13 increases in global SA in GWAS data, when considered in aggregate. This finding is consistent with the known expansion of human global SA compared to macaque 14 and further along our lineage 4 . Across the 34 gyrally-defined regions, there was considerable variability in whether the derived alleles, in aggregate, showed association with increases or decreases in regional SA, controlling for global SA ( Figure 4B ).…”

“…Investigations of interindividual variation within current human populations have found 4 substantial overlaps in the genomic architecture underlying endocranial volume and total neocortical surface area, while also supporting the existence of differential genetic effects on the surface area of specific cortical regions 15,16 . A few notable studies have identified genomic differences that may have impacted aspects of brain structure along our lineage 13,17,18 , but the genetic variation that shaped the cortex across human evolution is still largely undetermined.…”

“…The distinctive size, shape, and neural architecture of the modern human brain reflects the cumulative effects of selective pressures over evolutionary history. Analyses of fossilized skulls indicate that endocranial volume has increased dramatically on the lineage that led to Homo sapiens in the ~6 million years since our last common ancestor with chimpanzees [1][2][3][4] ( Figure 1 ). It is thought that these volumetric increases were driven in large part by expansions of neocortical surface area [5][6][7] , although changes in other brain structures, including the cerebellum, also likely played a significant role 8,9 .…”

Biological Anthropology in 2018: Grounded in Theory, Questioning Contexts, Embracing Innovation

“…Du et al. () analyzed endocranial volumes across ninety‐four hominin fossils from different taxa, arguing that brain size did not increase gradually and consistently across the hominin clade but rather via diverse, within‐lineage mechanisms, including directional selection, drift, the sudden emergence of larger‐brained species, and the extinction of smaller‐brained ones. Tucci et al.…”

Testing for correlation between traits under directional evolution

“…We considered the logarithms of cranial capacity and body mass data such as in Kappelman (1996); Henneberg (1998); Leonard et al (2003); Snodgrass et al (2009);Navarrete et al (2011);Du et al (2018). Taking the logarithm of quantitative trait values is quite usual since it accounts for the fact that for instance, an increase of 100 g does not have the same significance for an organism of 1 kg as for a organism of 100 kg.…”