Metalearning and neuromodulation
Neural Networks - Computational models of neuromodulation
Control of exploitation-exploration meta-parameter in reinforcement learning
Neural Networks - Computational models of neuromodulation
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When predicting where a target or reward will be, participants tend to choose each location commensurate with the true underlying probability i.e., probability match. The strategy of probability matching involves independent sampling of high and low probability locations on separate trials. In contrast, models of probabilistic spatial attention hypothesize that on any given trial attention will either be weighted toward the high probability location or be distributed equally across all locations. Thus, the strategies of probabilistic sampling by choice decisions and spatial attention appear to differ with regard to low-probability events. This distinction is somewhat surprising because similar brain mechanisms e.g., pFC-mediated cognitive control are thought to be important in both functions. Thus, the goal of the current study was to examine the relationship between choice decisions and attentional selection within single trials to test for any strategic differences, then to determine whether that relationship is malleable to manipulations of catecholamine-modulated cognitive control with the drug modafinil. Our results demonstrate that spatial attention and choice decisions followed different strategies of probabilistic information selection on placebo, but that modafinil brought the pattern of spatial attention into alignment with that of predictive choices. Modafinil also produced earlier learning of the probability distribution. Together, these results suggest that enhancing cognitive control mechanisms e.g., through prefrontal cortical function leads spatial attention to follow choice decisions in selecting information according to rule-based expectations.