Elucidating the Neural Representation and the Processing Dynamics of Face Ensembles.
face perception
multivariate analysis
neural decoding
visual ensembles
Journal
The Journal of neuroscience : the official journal of the Society for Neuroscience
ISSN: 1529-2401
Titre abrégé: J Neurosci
Pays: United States
ID NLM: 8102140
Informations de publication
Date de publication:
25 09 2019
25 09 2019
Historique:
received:
01
03
2019
revised:
02
08
2019
accepted:
06
08
2019
pubmed:
16
8
2019
medline:
7
7
2020
entrez:
16
8
2019
Statut:
ppublish
Résumé
Extensive behavioral work has documented the ability of the human visual system to extract summary representations from face ensembles (e.g., the average identity of a crowd of faces). Yet, the nature of such representations, their underlying neural mechanisms, and their temporal dynamics await elucidation. Here, we examine summary representations of facial identity in human adults (of both sexes) with the aid of pattern analyses, as applied to EEG data, along with behavioral testing. Our findings confirm the ability of the visual system to form such representations both explicitly and implicitly (i.e., with or without the use of specific instructions). We show that summary representations, rather than individual ensemble constituents, can be decoded from neural signals elicited by ensemble perception, we describe the properties of such representations by appeal to multidimensional face space constructs, and we visualize their content through neural-based image reconstruction. Further, we show that the temporal profile of ensemble processing diverges systematically from that of single faces consistent with a slower, more gradual accumulation of perceptual information. Thus, our findings reveal the representational basis of ensemble processing, its fine-grained visual content, and its neural dynamics.
Identifiants
pubmed: 31413074
pii: JNEUROSCI.0471-19.2019
doi: 10.1523/JNEUROSCI.0471-19.2019
pmc: PMC6764198
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
7737-7747Informations de copyright
Copyright © 2019 the authors.
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