Gottlieb, J. P. | Search bioRxiv

bioRxiv2023

Covert attention for uncertainty reduction duringsequential inference

A major question in attention research is how the brain identifies task-relevant stimuli in the absence of exogenous instructions or cues. Recent studies propose that endogenous attention control expected information gains (EIG) or, equivalently, minimizes decision uncertainty, but the mechanisms of this process are not understood. We show that, in a task in which participants covertly attended to decision-relevant stimuli, their perceptual sensitivity (d) for discriminating the stimuli depended on the diagnosticity of the stimuli and the participants prior decision uncertainty, consistent with Bayesian EIG. The fronto-parietal network, in particular left areas V3A/B and IPS1/2, integrated uncertainty with diagnosticity in a manner correlating with behavioral effects on d, and uncertainty signals relied on interactions between this network and the medial prefrontal cortex (mPFC). The findings show that covert attention can be deployed based on EIG and reveal the neural mechanisms of this process.

neuroscience↗

bioRxiv2022

Superstitious learning of abstract order from random reinforcement

Survival depends on identifying learnable features of the environment that predict reward, and avoiding others that are random and unlearnable. However, humans and other animals often infer spurious associations among unrelated events, raising the question of how well they can distinguish learnable patterns from unlearnable events. Here, we tasked monkeys with discovering the serial order of two pictorial sets: a "learnable" set in which the stimuli were implicitly ordered and monkeys were rewarded for choosing the higher-rank stimulus and an "unlearnable" set in which stimuli were unordered and feedback was random regardless of the choice. We replicated prior results that monkeys reliably learned the implicit order of the learnable set. Surprisingly, the monkeys behaved as though some ordering also existed in the unlearnable set, showing consistent choice preference that transferred to novel untrained pairs in this set, even under a preference-discouraging reward schedule that gave rewards more frequently to the stimulus that was selected less often. In simulations, a model-free RL algorithm (Q-learning) displayed a degree of consistent ordering among the unlearnable set but, unlike the monkeys, failed to do so under the preference, discouraging reward schedule. Our results suggest that monkeys infer abstract structures from objectively random events using heuristics that extend beyond stimulus-outcome conditional learning to more cognitive model-based learning mechanisms.

animal behavior and cognition↗