Physical sensorimotor contingencies facilitate learning in monkeys
Abstract
Animal studies in neuroscience routinely use virtual tasks that deviate significantly from the animals' natural behavioral repertoire. This choice is often necessary for conducting careful and controlled experimentation. However, this approach raises a fundamental question: do virtual tasks expose neural computations and mechanisms associated with naturalistic tasks? In this study, we explore how naturalistic settings influence learning timescale and generalization behavior in rhesus monkeys. By training animals in a maze-solving task and comparing their behavior across two environments, we observe significant differences. Specifically, we found that a realistic setup using physical objects enabled learning that was orders of magnitude faster than the learning timescale observed in a comparable computerized virtual environment. Furthermore, we noted limited transfer of performance between the physical and virtual settings. These findings underscore the need for understanding how task environments shape learning and generalization, with potential implications for the design of future neuroscience and AI experiments.
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