General Intelligence as a Major Source of Cognitive Variation Among Individuals of Three Species of Lemur, Uniting g with G

• Published in: Evolutionary psychological science 2022-09, Vol.8 (3), p.241-253
• Main Authors: Woodley of Menie, Michael A., Peñaherrera-Aguirre, Mateo
• Format: Article
• Language: English
• Subjects: Behavioral Science and Psychology; Brain; Cognition & reasoning; Cognitive ability; Hypotheses; Intelligence; Monkeys & apes; Personality and Social Psychology; Phylogenetics; Primates; Psychology; Research Article
• ISSN: 2198-9885; 2198-9885
• DOI: 10.1007/s40806-021-00304-x

A significant open issue in the field of comparative psychology is the apparent inability to reconcile the existence of ‘little g ’ (general intelligence) common factor variance among cognitive performance data involving individuals within species, with the existence of higher-level ‘Big G ’ factor variance among species-level cognitive aggregates. Here, using a cognitive individual differences dataset of three Lemur species (grey mouse lemur; Microcebus murinus , ruffed lemur, Varecia variegata , and ring-tailed lemur, Lemur catta ), we replicate a previously published solution to this problem. This is based on the hypothesis that there does exist g or g -like variance that is predictive of species differences, but that many of the measures employed in cross-species cognition tests impose floor or ceiling effects on one or more of the species being compared. These will obscure the alignment between g and G when individuals of multiple species are compared. An iterative latent variable moderation model is used, whereby sequentially removing subtests based on lowest coefficient of variance (CV) increases the degree to which g -loadings moderate the species differences among the remaining subtest pool. The correlation between moderator effect magnitude and rising CV across twelve iterations (from fourteen to three subtests) ranges from .710 to .854 based on which pairs of species are being compared. This result is consistent with the expectation that across species, g is highly predictive of species differences (and thus, g and G are one and the same), although significant ‘modular’ differences doubtlessly also exist. Predictions stemming from these observations are outlined using simulations. Finally, the implication of these findings for constructing trans-species valid measures of g and ‘IQ’ for use in future research (such as trans-species GWAS) is discussed.