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

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.

Dynamic expectations: Behavioral and electrophysiological evidence of sub-second updates in reward predictions.

Expectations are often dynamic: sports fans know that expectations are rapidly updated as games unfold. Yet expectations have traditionally been studied as static. Here we present behavioral and electrophysiological evidence of sub-second changes in expectations using slot machines as a case study. In Study 1, we demonstrate that EEG signal before the slot machine stops varies based on proximity to winning. Study 2 introduces a behavioral paradigm to measure dynamic expectations via betting, and shows that expectation trajectories vary as a function of winning proximity. Notably, these expectation trajectories parallel Study 1's EEG activity. Studies 3 (EEG) and 4 (behavioral) replicate these findings in the loss domain. These four studies provide compelling evidence that dynamic sub-second updates in expectations can be behaviorally and electrophysiologically measured. Our research opens promising avenues for understanding the dynamic nature of reward expectations and their impact on cognitive processes.

Dynamic expectations: Behavioral and electrophysiological evidence of sub-second updates in reward predictions.

Expectations are often dynamic: any sports fan knows that expectations are rapidly updated as games unfold. Yet expectations have traditionally been studied as static. Here, using slot machines as a case study, we provide parallel behavioral and electrophysiological evidence of sub-second moment-to-moment changes in expectations. In Study 1, we show that the dynamics of the EEG signal before the slot machine stopped differed depending on the nature of the outcome, including not only whether the participant won or lost, but also how close they came to winning. In line with our predictions, Near Win Before outcomes (the slot machine stops one item before a match) were similar to Wins, but different than Near Win After (the machine stops one item after a match) and Full Miss (the machine stops two or three items from a match). In Study 2, we designed a novel behavioral paradigm to measure moment-to-moment changes in expectations via dynamic betting. We found that different outcomes also elicited unique expectation trajectories in the deceleration phase. Notably, these behavioral expectation trajectories paralleled Study 1's EEG activity in the last second prior to the machine's stop. In Studies 3 (EEG) and 4 (behavior) we replicated these findings in the loss domain where a match entails a loss. Again, we found a significant correlation between behavioral and EEG results. These four studies provide the first evidence that dynamic sub-second updates in expectations can be behaviorally and electrophysiologically measured. Our findings open up new avenues for studying the ongoing dynamics of reward expectations and their role in healthy and unhealthy cognition.

Comparing rapid rule-learning strategies in humans and monkeys.

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.