Both absolute and relative brain sizes vary greatly among and within the major vertebrate lineages. Scientists have long debated how larger brains in primates and hominins translate into greater cognitive performance, and in particular how to control for the relationship between the noncognitive functions of the brain and body size. One solution to this problem is to establish the slope of cognitive equivalence, i.e., the line connecting organisms with an identical bauplan but different body sizes. The original approach to estimate this slope through intraspecific regressions was abandoned after it became clear that it generated slopes that were too low by an unknown margin due to estimation error. Here, we revisit this method. We control for the error problem by focusing on highly dimorphic primate species with large sample sizes and fitting a line through the mean values for adult females and males. We obtain the best estimate for the slope of circa 0.27, a value much lower than those constructed using all mammal species and close to the value expected based on the genetic correlation between brain size and body size. We also find that the estimate of cognitive brain size based on cognitive equivalence fits empirical cognitive studies better than the encephalization quotient, which should therefore be avoided in future studies on primates and presumably mammals and birds in general. The use of residuals from the line of cognitive equivalence may change conclusions concerning the cognitive abilities of extant and extinct primate species, including hominins.

General intelligence has been a topic of high interest for over a century. Traditionally, research on general intelligence was based on principal component analyses and other dimensionality reduction approaches. The advent of high-speed computing has provided alternative statistical tools that have been used to test predictions of human general intelligence. In comparison, research on general intelligence in non-human animals is in its infancy and still relies mostly on factor-analytical procedures. Here, we argue that dimensionality reduction, when incorrectly applied, can lead to spurious results and limit our understanding of ecological and evolutionary causes of variation in animal cognition. Using a meta-analytical approach, we show, based on 555 bivariate correlations, that the average correlation among cognitive abilities is low (<i>r</i> = 0.185; 95% CI: 0.087-0.287), suggesting relatively weak support for general intelligence in animals. We then use a case study with relatedness (genetic) data to demonstrate how analysing traits using mixed models, without dimensionality reduction, provides new insights into the structure of phenotypic variance among cognitive traits, and uncovers genetic associations that would be hidden otherwise. We hope this article will stimulate the use of alternative tools in the study of cognition and its evolution in animals.

Brain size variability in primates has been attributed to various domain-specific socio-ecological factors. A recently published large-scale study of short-term memory abilities in 41 primate species (ManyPrimates 2022 <i>Anim. Behav. Cogn.</i> 9, 428-516. (doi:10.26451/abc.09.04.06.2022)) did not find any correlations with 11 different proxies of external cognitive demands. Here, we found that the interspecific variation in test performance shows correlated evolution with total brain size, with the relationship becoming tighter as species with small sample sizes were successively removed, whereas it was not predicted by the often-used encephalization quotient. In a subsample, we also found that the sizes of brain regions thought to be involved in short-term memory did not predict performance better than overall brain size. The dependence on brain size suggests that domain-general cognitive processes underlie short-term memory as tested by ManyPrimates. These results support the emerging notion that comparative studies of brain size do not generally identify domain-specific cognitive adaptations but rather reveal varying selections on domain-general cognitive abilities. Finally, because attentional processes beyond short-term memory also affect test performance, we suggest that the delayed response test can be refined.

Abstract The timing and nature of evolutionary shifts in the relative brain size of Primates have been extensively studied. Less is known, however, about the scaling of the brain-to-body size in their closest living relatives, i.e., among other members of Euarchontoglires (Dermoptera, Scandentia, Lagomorpha, Rodentia). Ordinary least squares (OLS), reduced major axis (RMA), and phylogenetic generalized least squares (PGLS) regressions were fitted to the largest euarchontogliran data set of brain and body mass, comprising 715 species. Contrary to previous inferences, lagomorph brain sizes (PGLS slope = 0.465; OLS slope = 0.593) scale relative to body mass similarly to rodents (PGLS = 0.526; OLS = 0.638), and differently than primates (PGLS = 0.607; OLS = 0.794). There is a shift in the pattern of the scaling of the brain in Primates, with Strepsirrhini occupying an intermediate stage similar to Scandentia but different from Rodentia and Lagomorpha, while Haplorhini differ from all other groups in the OLS and RMA analyses. The unique brain–body scaling relationship of Primates among Euarchontoglires illustrates the need for clade-specific metrics for relative brain size (i.e., encephalization quotients; EQs) for more restricted taxonomic entities than Mammalia. We created clade-specific regular and phylogenetically adjusted EQ equations at superordinal, ordinal, and subordinal levels. When using fossils as test cases, our results show that generalized mammalian equations underestimate the encephalization of the stem lagomorph Megalagus turgidus in the context of lagomorphs, overestimate the encephalization of the stem primate Microsyops annectens and the early euprimate Necrolemur antiquus, but provide similar EQ values as our new strepsirrhine-specific EQ when applied to the early euprimate Adapis parisiensis.