The evolution of mammalian brain size.

Relative brain size has long been considered a reflection of cognitive capacities and has played a fundamental role in developing core theories in the life sciences. Yet, the notion that relative brain size validly represents selection on brain size relies on the untested assumptions that brain-body allometry is restrained to a stable scaling relationship across species and that any deviation from this slope is due to selection on brain size. Using the largest fossil and extant dataset yet assembled, we find that shifts in allometric slope underpin major transitions in mammalian evolution and are often primarily characterized by marked changes in body size. Our results reveal that the largest-brained mammals achieved large relative brain sizes by highly divergent paths. These findings prompt a reevaluation of the traditional paradigm of relative brain size and open new opportunities to improve our understanding of the genetic and developmental mechanisms that influence brain size.

Testing species' deviation from allometric predictions using the phylogenetic regression.

Phylogenetic generalized least squares (PGLS) has become one of the most commonly used phylogenetic comparative methods. Despite its common use, descriptions, and applications of methods to test for species' deviations from allometric predictions using phylogenetic regression have been piecemeal. We simplify previous computational descriptions of PGLS standard errors in a manner that can be easily generalized toward more complex general linear models. We focus on the implementation of phylogenetic analysis of covariance, which provides a direct test for the equality of intercepts and slopes. Our computational descriptions allow testing whether individual species, or a group of species, deviate significantly from allometric predictions. The use of PGLS confidence and prediction intervals and phylogenetic analysis of covariance is exemplified in an analysis of brain structure volumes in primates.

Worldwide variation in hip fracture incidence weakly aligns with genetic divergence between populations.

UNLABELLED: This study investigates the influence of genetic differentiation in determining worldwide heterogeneity in osteoporosis-related hip fracture rates. The results indicate that global variation in fracture incidence exceeds that expected on the basis of random genetic variance. INTRODUCTION: Worldwide, the incidence of osteoporotic hip fractures varies considerably. This variability is believed to relate mainly to non-genetic factors. It is conceivable, however, that genetic susceptibility indeed differs across populations. Here, we present the first quantitative assessment of the effects of genetic differentiation on global variability in hip fracture rates. METHODS: We investigate the observed variance in publically reported age-standardized rates of hip fracture among 28 populations from around the world relative to the expected variance given the phylogenetic relatedness of these populations. The extent to which these variances are similar constitutes a "phylogenetic signal," which was measured using the K statistic. Population genetic divergence was calculated using a robust array of genome-wide single nucleotide polymorphisms. RESULTS: While phylogenetic signal is maximized when K > 1, a K value of only 0.103 was detected in the combined-sex fracture rate pattern across the 28 populations, indicating that fracture rates vary more than expected based on phylogenetic relationships. When fracture rates for the sexes were analyzed separately, the degree of phylogenetic signal was also found to be small (females: K = 0.102; males: K = 0.081). CONCLUSIONS: The lack of a strong phylogenetic signal underscores the importance of factors other than stochastic genetic diversity in shaping worldwide heterogeneity in hip fracture incidence.

The macroevolutionary consequences of phenotypic integration: from development to deep time.

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution.

Brain reorganization, not relative brain size, primarily characterizes anthropoid brain evolution.

Comparative analyses of primate brain evolution have highlighted changes in size and internal organization as key factors underlying species diversity. It remains, however, unclear (i) how much variation in mosaic brain reorganization versus variation in relative brain size contributes to explaining the structural neural diversity observed across species, (ii) which mosaic changes contribute most to explaining diversity, and (iii) what the temporal origin, rates and processes are that underlie evolutionary shifts in mosaic reorganization for individual branches of the primate tree of life. We address these questions by combining novel comparative methods that allow assessing the temporal origin, rate and process of evolutionary changes on individual branches of the tree of life, with newly available data on volumes of key brain structures (prefrontal cortex, frontal motor areas and cerebrocerebellum) for a sample of 17 species (including humans). We identify patterns of mosaic change in brain evolution that mirror brain systems previously identified by electrophysiological and anatomical tract-tracing studies in non-human primates and functional connectivity MRI studies in humans. Across more than 40 Myr of anthropoid primate evolution, mosaic changes contribute more to explaining neural diversity than changes in relative brain size, and different mosaic patterns are differentially selected for when brains increase or decrease in size. We identify lineage-specific evolutionary specializations for all branches of the tree of life covered by our sample and demonstrate deep evolutionary roots for mosaic patterns associated with motor control and learning.

Primate prefrontal cortex evolution: human brains are the extreme of a lateralized ape trend.

The prefrontal cortex is commonly associated with cognitive capacities related to human uniqueness: purposeful actions towards higher-level goals, complex social information processing, introspection, and language. Comparative investigations of the prefrontal cortex may thus shed more light on the neural underpinnings of what makes us human. Using histological data from 19 anthropoid primate species (6 apes including humans and 13 monkeys), we investigate cross-species relative size changes along the anterior (prefrontal) and posterior (motor) axes of the cytoarchitectonically defined frontal lobe in both hemispheres. Results reveal different scaling coefficients in the left versus right prefrontal hemisphere, suggest that the primary factor underlying the evolution of primate brain architecture is left hemispheric prefrontal hyperscaling, and indicate that humans are the extreme of a left prefrontal ape specialization in relative white to grey matter volume. These results demonstrate a neural adaptive shift distinguishing the ape from the monkey radiation possibly related to a cognitive grade shift between (great) apes and other primates.