Behaviorally-relevant features of observed actions dominate cortical representational geometry in natural vision.

ABSTRACT: We effortlessly extract behaviorally relevant information from dynamic visual input in order to understand the actions of others. In the current study, we develop and test a number of models to better understand the neural representational geometries supporting action understanding. Using fMRI, we measured brain activity as participants viewed a diverse set of 90 different video clips depicting social and nonsocial actions in real-world contexts. We developed five behavioral models using arrangement tasks: two models reflecting behavioral judgments of the purpose (transitivity) and the social content (sociality) of the actions depicted in the video stimuli; and three models reflecting behavioral judgments of the visual content (people, objects, and scene) depicted in still frames of the st

SUBMITTER: Han J 

PROVIDER: S-EPMC11623629 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature