Positive and negative action-effects improve task-switching performance

Anticipation of one's own actions' effects drives goal-directed behavior. In multitasking environments, the learning of stable action-effect associations seems particularly important, because establishing reliable responseeffect associations for multiple competing tasks may help to differentiate between these tasks and thereby improve task-switching performance. Action-effects not only have cognitive, but also motivational aspects and often the consequences of our actions are hedonically marked. Thus, the anticipated hedonic quality of actioneffects may also become part of the task representation, and positive and negative affect may distinctly modulate task-switching performance. We report a pre-registered experiment (N = 120) designed to examine how positive, negative, and neutral valence of action-effects impact performance in a cued task-switching paradigm. Pictures from the IAPS database were used to manipulate the action-effects' valence. Affective valence determined reaction times: participants who learned positive or negative action-effects responded faster than participants in the control condition. In particular, task-switch trials were faster in both conditions than in the control condition, while task-repetition trials were comparable across valence conditions. Our results further suggest that performance improvements in the positive and negative valence conditions occurred for different reasons. Negative action-effects expedited responses specifically for the task that produced the unpleasant outcome, while positive affect more generally promoted performance of both tasks. These findings point toward distinct roles of positive and negative valence of action-effects in regulating multitasking performance.

Automated summary

Anticipation of one's own actions' effects drives goal-directed behavior, with positive and negative emotions having distinct roles in regulating task-switching performance, contributing to improved multitasking efficiency.