A Comparison of Rapid Rule-Learning Strategies in Humans and Monkeys

Vishwa Goudar, Jeong Woo Kim, Yue Liu, Adam J.O. Dede, Michael J. Jutras, Ivan Skelin, Michael Ruvalcaba, William Chang, Bhargavi Ram, Adrienne L. Fairhall, Jack J. Lin, Robert T. Knight, Elizabeth A. Buffalo, Xiao Jing Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Interspecies comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of the strategies of female macaque monkeys to male and female humans on a variant of the Wisconsin Card Sorting Test (WCST), a widely studied and applied task that provides a multiattribute measure of cognitive function and depends on the frontal lobe. WCST performance requires the inference of a rule change given ambiguous feedback. We found that well-trained monkeys infer new rules three times more slowly than minimally instructed humans. Input-dependent hidden Markov model–generalized linear models were fit to their choices, revealing hidden states akin to feature-based attention in both species. Decision processes resembled a win–stay, lose–shift strategy with interspecies similarities as well as key differences. Monkeys and humans both test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidate choice options. We quantitatively show that perseveration, random exploration, and poor sensitivity to negative feedback account for the slower task-switching performance in monkeys.

Original languageEnglish (US)
Article numbere0231232024
JournalJournal of Neuroscience
Volume44
Issue number28
DOIs
StatePublished - Jul 10 2024

ASJC Scopus subject areas

  • General Neuroscience

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