Mechanisms of value-learning in the guidance of spatial attention

Abstract

The role of associative reward learning in the guidance of feature-based attention is well established. The extent to which reward learning can modulate spatial attention has been much more controversial. At least one demonstration of a persistent spatial attention bias following space-based associative reward learning has been reported. At the same time, multiple other experiments have been published failing to demonstrate enduring attentional biases towards locations at which a target, if found, yields high reward. This is in spite of evidence that participants use reward structures to inform their decisions where to search, leading some to suggest that, unlike feature-based attention, spatial attention may be impervious to the influence of learning from reward structures. Here, we demonstrate a robust bias towards regions of a scene that participants were previously rewarded for selecting. This spatial bias relies on representations that are anchored to the configuration of objects within a scene. The observed bias appears to be driven specifically by reinforcement learning, and can be observed with equal strength following non-reward corrective feedback. The time course of the bias is consistent with a transient shift of attention, rather than a strategic search pattern, and is evident in eye movement patterns during free viewing. Taken together, our findings reconcile previously conflicting reports and offer an integrative account of how learning from feedback shapes the spatial attention system.

Keywords: Attentional capture; Real world scenes; Reward learning; Selective attention; Spatial attention.