The repeatability of cognitive performance: a meta-analysis

Behavioural and cognitive processes play important roles in mediating an individual's interactions with its environment. Yet, while there is a vast literature on repeatable individual differences in behaviour, relatively little is known about the repeatability of cognitive performance. To further our understanding of the evolution of cognition, we gathered 44 studies on individual performance of 25 species across six animal classes and used meta-analysis to assess whether cognitive performance is repeatable. We compared repeatability (R) in performance (1) on the same task presented at different times (temporal repeatability), and (2) on different tasks that measured the same putative cognitive ability (contextual repeatability). We also addressed whether R estimates were influenced by seven extrinsic factors (moderators): type of cognitive performance measurement, type of cognitive task, delay between tests, origin of the subjects, experimental context, taxonomic class and publication status. We found support for both temporal and contextual repeatability of cognitive performance, with mean R estimates ranging between 0.15 and 0.28. Repeatability estimates were mostly influenced by the type of cognitive performance measures and publication status. Our findings highlight the widespread occurrence of consistent inter-individual variation in cognition across a range of taxa which, like behaviour, may be associated with fitness outcomes.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.

Dynamic material characterization of the human heel pad based on in vivo experimental tests and numerical analysis

A numerical-experimental, proof-of-concept approach is described to characterize the mechanical material behavior of the human heel pad under impact conditions similar to a heel strike while running. A 3D finite-element model of the right foot of a healthy female subject was generated using magnetic resonance imaging. Based on quasi-static experimental testing of the subject's heel pad, force-displacement data was obtained. Using this experimental data as well as a numerical optimization algorithm, an inverse finite-element analysis and the 3D model, heel pad hyperelastic (long-term) material parameters were determined. Applying the same methodology, based on the dynamic experimental data from the impact test and obtained long-term parameters, linear viscoelastic parameters were established with a Prony series. Model validation was performed employing quasi-static and dynamic force-displacement data. Coefficients of determination when comparing model to experimental data during quasi-static and dynamic (initial velocity: 1480mm/s) procedure were R(2) = 0.999 and R(2) = 0.990, respectively. Knowledge of these heel pad material parameters enables realistic numerical analysis to evaluate internal stress and strain in the heel pad during different quasi-static or dynamic load conditions.