Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance.

ABSTRACT: Although avoidance is a prevalent feature of anxiety-related psychopathology, differences in the measurement of avoidance between humans and non-human animals hinder our progress in its theoretical understanding and treatment. To address this, we developed a novel translational measure of anxiety-related avoidance in the form of an approach-avoidance reinforcement learning task, by adapting a paradigm from the non-human animal literature to study the same cognitive processes in human participants. We used computational modelling to probe the putative cognitive mechanisms underlying approach-avoidance behaviour in this task and investigated how they relate to subjective task-induced anxiety. In a large online study (n = 372), participants who experienced greater task-induced anxiety avoided

SUBMITTER: Yamamori Y 

PROVIDER: S-EPMC10645421 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature