Two distinct networks containing position-tolerant representations of actions in the human brain

Abstract

Humans can recognize other peoples actions in the social environment. This action recognition ability is rarely hindered by the movement of people in the environment. The neural basis of this tolerance to changes in the position of observed actions is not fully understood. Here, we aimed to identify brain regions capable of generalizing representations of actions across different positions and investigate the representational content of these regions. fMRI data were recorded from twenty-two subjects while they were watching video clips of ten different human actions in Point Light Display format. Each stimulus was presented in either the upper or the lower visual fields. Multivoxel pattern analysis and a searchlight technique were employed to identify brain regions that contain position-tolerant action representation: linear support vector machine classifiers were trained with fMRI patterns in response to stimuli presented in one position and tested with stimuli presented in another position. Results of this generalization test showed above-chance classification in the left and right lateral occipitotemporal cortex, right intraparietal sulcus, and right post-central gyrus. To explore the representational content of these regions, we constructed models based on the objective measures of movements and human subjective judgments about actions. We then evaluated the brain similarity matrix from the cross-position classification analysis based on these models. Results showed cross-position classifications in the lateral occipito-temporal ROIs were more strongly related to the subjective judgments, while those in the dorsal parietal ROIs were more strongly related to the objective movements. An ROI representational similarity analysis further confirmed the separation of the dorsal and lateral regions. These results provide evidence for two networks that contain abstract representations of human actions with distinct representational content.