The speed of human social interaction perception.
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
15 07 2020
15 07 2020
Historique:
received:
04
12
2019
revised:
27
02
2020
accepted:
08
04
2020
pubmed:
18
4
2020
medline:
20
2
2021
entrez:
18
4
2020
Statut:
ppublish
Résumé
The ability to perceive others' social interactions, here defined as the directed contingent actions between two or more people, is a fundamental part of human experience that develops early in infancy and is shared with other primates. However, the neural computations underlying this ability remain largely unknown. Is social interaction recognition a rapid feedforward process or a slower post-perceptual inference? Here we used magnetoencephalography (MEG) decoding to address this question. Subjects in the MEG viewed snapshots of visually matched real-world scenes containing a pair of people who were either engaged in a social interaction or acting independently. The presence versus absence of a social interaction could be read out from subjects' MEG data spontaneously, even while subjects performed an orthogonal task. This readout generalized across different people and scenes, revealing abstract representations of social interactions in the human brain. These representations, however, did not come online until quite late, at 300 ms after image onset, well after feedforward visual processes. In a second experiment, we found that social interaction readout still occurred at this same late latency even when subjects performed an explicit task detecting social interactions. We further showed that MEG responses distinguished between different types of social interactions (mutual gaze vs joint attention) even later, around 500 ms after image onset. Taken together, these results suggest that the human brain spontaneously extracts information about others' social interactions, but does so slowly, likely relying on iterative top-down computations.
Identifiants
pubmed: 32302763
pii: S1053-8119(20)30331-1
doi: 10.1016/j.neuroimage.2020.116844
pii:
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
116844Informations de copyright
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.