Neural representations of observed actions generalize across static and dynamic visual input

Abstract

People interact with entities in the environment in distinct and categorizable ways (e.g., kicking is making contact with foot). We can recognize these action categories across variations in actors, objects, and settings; moreover, we can recognize them from both dynamic and static visual input. However, the neural systems that support action recognition across these perceptual differences are unclear. Here, we used multivoxel pattern analysis of fMRI data to identify brain regions that support visual action categorization in a formatindependent way. Human participants were scanned while viewing eight categories of interactions (e.g., pulling) depicted in two visual formats: (1) visually controlled videos of two interacting actors and (2) visually varied photographs selected from the internet involving different actors, objects, and settings. Action category was decodable across visual formats in bilateral inferior parietal, bilateral occipitotemporal, left premotor, and left middle frontal cortex. In most of these regions, the representational similarity of action categories was consistent across subjects and visual formats, a property that can contribute to a common understanding of actions among individuals. These results suggest that the identified brain regions support action category codes that are important for action recognition and action understanding.