4.7 Article

Categorization learning induced changes in action representations in the macaque STS

Journal

NEUROIMAGE
Volume 265, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2022.119780

Keywords

Action observation; Category learning; Rhesus macaque; fMRI; MVPA

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Neuroimaging and single cell recordings have shown the existence of STS body category-selective regions (body patches) that respond to static bodies and body parts. However, it is still uncertain if these body patches and other STS regions respond to different categories of dynamic actions and how categorization learning influences observed action representations in the STS.
Neuroimaging and single cell recordings have demonstrated the presence of STS body category-selective regions (body patches) containing neurons responding to presentation of static bodies and body parts. To date, it remains unclear if these body patches and additional STS regions respond during observation of different categories of dynamic actions and to what extent categorization learning influences representations of observed actions in the STS. In the present study, we trained monkeys to discriminate videos depicting three different actions categories (grasping, touching and reaching) with a forced-choice action categorization task. Before and after categoriza-tion training, we performed fMRI recordings while monkeys passively observed the same action videos. At the behavioral level, after categorization training, monkeys generalized to untrained action exemplars, in particular for grasping actions. Before training, uni-and/or multivariate fMRI analyses suggest a broad representation of dynamic action categories in particular in posterior and middle STS. Univariate analysis further suggested action category specific training effects in middle and anterior body patches, face patch ML and posterior STS region MT and FST. Overall, our fMRI experiments suggest a widespread representation of observed dynamic bodily actions in the STS that can be modulated by visual learning, supporting its proposed role in action recognition.

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