August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
Decoding the physics of actions in the dorsal visual pathway
Author Affiliations
  • Moritz Wurm
    University of Trento
  • Yiğit Erigüç
    University of Trento
Journal of Vision August 2023, Vol.23, 4893. doi:https://doi.org/10.1167/jov.23.9.4893
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      Moritz Wurm, Yiğit Erigüç; Decoding the physics of actions in the dorsal visual pathway. Journal of Vision 2023;23(9):4893. https://doi.org/10.1167/jov.23.9.4893.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Recognizing goal-directed actions is a computationally challenging task, requiring not only the visual analysis of body movements but also of how these movements causally impact, and thereby induce a change in, those objects targeted by an action. We tested the hypothesis that subregions of the dorsal pathway – superior and anterior inferior parietal lobe (SPL and aIPL) – are specialized for the processing of body movements and the effects they induce. In four fMRI sessions, 25 participants observed videos of actions (e.g. breaking a stick, squashing a plastic bottle) along with corresponding point-light-displays, pantomimes, and abstract animations of agent-object interactions (e.g. a circle dividing or compressing a rectangle). By decoding actions across different stimulus formats (e.g. training a classifier to discriminate activation patterns associated with actions, testing the classifier on activation patterns associated with animations), we isolated different action components: Cross-decoding between actions and animations revealed that aIPL encodes abstract representations of effect structures independent of motion and object identity (e.g. dividing or compressing object). By contrast, cross-decoding between actions and point-light-displays revealed that SPL represents body movements irrespective of visible interactions with objects (interaction: F(1,24)=35.1, p=4.9E-06). Moreover, cross-decoding between pantomimes and animations revealed that right aIPL represents action effects even in response to implied object interactions, whereas left aIPL represents action effects exclusively in response to visible interactions with objects. These results demonstrate that the dorsal pathway contains distinct subregions tuned to different physical action features, such as how body parts move in space relative to each other and how body parts interact with objects to induce a change (e.g. in position, shape, or state). The high level of abstraction revealed by cross-decoding suggests a general neural code supporting mechanical reasoning about movement kinematics of entities and about how entities interact with, and have effects on, each other.

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