Lateralized representations of cause and effect in action observation

Poster Presentation 53.360: Tuesday, May 21, 2024, 8:30 am – 12:30 pm, Banyan Breezeway
Session: Action: Representation

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Moritz Wurm1 (), Philipp Flieger1,2; 1CIMeC, University of Trento, Italy, 2Justus-Liebig-University Gießen, Germany

Understanding object-directed actions requires the visual analysis of how body parts interact with objects and how these interactions lead to changes in the objects. However, whether, and if so, how interaction (as cause) and object change (as effect) are distinctively processed in the brain remains unexplored. Based on previous findings, we hypothesized that interaction and change are represented in a lateralized manner in left vs. right nodes of the action observation network, respectively. In four fMRI sessions, 30 right-handed participants observed videos of object-directed actions (e.g., breaking a stick), corresponding abstract animations (e.g., a triangle hitting a rectangle, causing it to break in half), and animations of interaction (triangle hits rectangle) and object change (rectangle breaks in half) in isolation. Using cross-decoding, we isolated either the interaction or change in the actions (train classifier to discriminate actions, test on interaction-only or change-only animations, respectively). As hypothesized, we found that cross-decoding between actions and interaction-only animations was stronger in left vs, right anterior inferior parietal lobe (aIPL) and lateral occipitotemporal cortex (LOTC), whereas the opposite pattern of results was found for cross-decoding between actions and change-only animations. In addition, in bilateral aIPL, cross-decoding between actions and animations depicting both interaction and change was stronger than the sum of cross-decoding between actions and interaction-only or change-only animations. This super-additive effect points toward a higher-level representation of cause-effect structures beyond representations of interaction and change as isolated components. These findings demonstrate that left and right hemispheres have distinct roles in representing the interaction between entities and the induced change, respectively, and that interaction and change are integrated to cause-effect structures in aIPL. Together, these findings shed new light on the interplay of left and right LOTC and aIPL in the physical understanding of observed actions.