Comparing 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 K. Chang, Adrienne L. Fairhall, Jack J. Lin, Robert Thomas Knight, Elizabeth A. Buffalo, Xiao‐Jing Wang · bioRxiv (Cold Spring Harbor Laboratory) · 2023
Inter-species 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 macaque monkey and human strategies on an analogue of the Wisconsin Card Sort Test, a widely studied and applied multi-attribute measure of cognitive function, wherein performance requires the inference of a changing rule given ambiguous feedback. We found that well-trained monkeys rapidly infer rules but are three times slower than humans. Model fits to their choices revealed hidden states akin to feature-based attention in both species, and decision processes that resembled a Win-stay lose-shift strategy with key differences. Monkeys and humans test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidates. An attention-set based learning stage categorization revealed that perseveration, random exploration and poor sensitivity to negative feedback explain the under-performance in monkeys.