How does cognition evolve? Phylogenetic comparative psychology

Abstract

Now more than ever animal studies have the potential to test hypotheses regarding how cognition evolves. Comparative psychologists have developed new techniques to probe the cognitive mechanisms underlying animal behavior, and they have become increasingly skillful at adapting methodologies to test multiple species. Meanwhile, evolutionary biologists have generated quantitative approaches to investigate the phylogenetic distribution and function of phenotypic traits, including cognition. In particular, phylogenetic methods can quantitatively (1) test whether specific cognitive abilities are correlated with life history (e.g., lifespan), morphology (e.g., brain size), or socio-ecological variables (e.g., social system), (2) measure how strongly phylogenetic relatedness predicts the distribution of cognitive skills across species, and (3) estimate the ancestral state of a given cognitive trait using measures of cognitive performance from extant species. Phylogenetic methods can also be used to guide the selection of species comparisons that offer the strongest tests of a priori predictions of cognitive evolutionary hypotheses (i.e., phylogenetic targeting). Here, we explain how an integration of comparative psychology and evolutionary biology will answer a host of questions regarding the phylogenetic distribution and history of cognitive traits, as well as the evolutionary processes that drove their evolution.

Fig. 1

An overview of some evolutionary questions relevant to comparative psychology and the phylogenetic comparative methods designed to address them. The shaded circles in the top panel depict species similarity along a continuous quantitative dimension (e.g., percent correct responses in the example inhibitory control task). The leaf and fruit icons in the second panel represent different dietary strategies that could be tested for their association with performance on a cognitive task. The third panel shows the root node on a phylogeny, representing an extinct species for which the ancestral cognitive ability could be predicted using data from extant species along the tips of the phylogeny. The fourth panel illustrates a scenario in which there are only cognitive data for two species in the phylogeny. Phylogenetic targeting facilitates the strategic choice of which additional species are most interesting to test in order to evaluate an evolutionary hypothesis

Fig. 2

A phylogeny of the 12 primate species comprising the example dataset. As a subject watched, food was placed behind a transparent barrier. To successfully retrieve the food, subjects needed to resist reaching directly for the food (i.e., bumping into the transparent barrier) and instead perform a detour around the barrier. Mean percent correct responses (because the total number of trials varied between species) are shown for each species. Data were pooled from similar tasks used by Amici et al. (2008) and MacLean et al. (unpublished data) and are analyzed here for illustrative purposes only

Fig. 3

Rescaled phylogenetic trees transformed at a λ = 0, b λ = 0.5, and c λ = 1. When λ = 0, all internal branches are rescaled to zero, which indicates that the trait distribution among the species shows no association with phylogeny (i.e., a star phylogeny; all the branches emanate from a single node, modeling all species as equally related to one another). When λ = 1, branch lengths reflect the actual divergence dates for each lineage, indicating that variance in the trait has accumulated over time exactly as predicted by Brownian motion. For many traits, λ falls between zero and one