Reward predictions bias attentional selection

Abstract

Attention selects stimuli for perceptual and cognitive processing according to an adaptive selection schedule. It has long been known that attention selects stimuli that are task relevant or perceptually salient. Recent evidence has shown that stimuli previously associated with reward persistently capture attention involuntarily, even when they are no longer associated with reward. Here we examine whether the capture of attention by previously reward-associated stimuli is modulated by the processing of current but unrelated rewards. Participants learned to associate two color stimuli with different amounts of reward during a training phase. In a subsequent test phase, these previously rewarded color stimuli were occasionally presented as to-be-ignored distractors while participants performed visual search for each of two differentially rewarded shape-defined targets. The results reveal that attentional capture by formerly rewarded distractors was the largest when both recently received and currently expected reward were the highest in the test phase, even though such rewards were unrelated to the color distractors. Our findings support a model in which value-driven attentional biases acquired through reward learning are maintained via the cognitive mechanisms involved in predicting future rewards.

Keywords: attentional capture; incentive salience; reward learning; reward prediction; selective attention.

Figure 1

Experimental paradigm. Sequence of events and time course for a trial during the training phase (A) and test phase (B). Each trial was followed by a blank 1000 ms intertrial interval.

Figure 2

Behavioral results. (A) Value-driven attentional capture (defined as the mean difference in RT between distractor-present and distractor-absent trials) as a function of the value of the search context (defined as the mean reward obtained on the previous 5 trials in which the current shape singleton served as the target). (B) Value-driven attentional capture as a function of the reward-prediction error experienced on the previous trial. The error bars reflect the within-subjects SEM.