Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces

Dima, Diana C.; Perry, Gavin; Messaritaki, Eirini; Zhang, Jiaxiang; Singh, Krish D.

doi:10.1002/hbm.24226

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Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces

Diana C. Dima

, Gavin Perry, Eirini Messaritaki, Jiaxiang Zhang

, Krish D. Singh

Human Brain Mapping, Volume: 39, Issue: 10, Pages: 3993 - 4006

Swansea University Author: Jiaxiang Zhang

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DOI (Published version): 10.1002/hbm.24226

Abstract

Recognizing emotion in faces is important in human interaction and survival, yet existing studies do not paint a consistent picture of the neural representation supporting this task. To address this, we collected magnetoencephalography (MEG) data while participants passively viewed happy, angry and...

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Published in:	Human Brain Mapping
ISSN:	1065-9471
Published:	Wiley 2018
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa61341
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first_indexed	2022-10-11T11:41:54Z
last_indexed	2023-01-13T19:22:03Z
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spelling	2022-10-11T12:46:18.2919331 v2 61341 2022-09-26 Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces 555e06e0ed9a87608f2d035b3bde3a87 0000-0002-4758-0394 Jiaxiang Zhang Jiaxiang Zhang true false 2022-09-26 SCS Recognizing emotion in faces is important in human interaction and survival, yet existing studies do not paint a consistent picture of the neural representation supporting this task. To address this, we collected magnetoencephalography (MEG) data while participants passively viewed happy, angry and neutral faces. Using time-resolved decoding of sensor-level data, we show that responses to angry faces can be discriminated from happy and neutral faces as early as 90 ms after stimulus onset and only 10 ms later than faces can be discriminated from scrambled stimuli, even in the absence of differences in evoked responses. Time-resolved relevance patterns in source space track expression-related information from the visual cortex (100 ms) to higher-level temporal and frontal areas (200–500 ms). Together, our results point to a system optimised for rapid processing of emotional faces and preferentially tuned to threat, consistent with the important evolutionary role that such a system must have played in the development of human social interactions. Journal Article Human Brain Mapping 39 10 3993 4006 Wiley 1065-9471 face perception, magnetoencephalography (MEG), multivariate pattern analysis (MVPA), threat bias 1 10 2018 2018-10-01 10.1002/hbm.24226 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University Medical Research Council and Engineeringand Physical Sciences Research Council,Grant/Award Number: MR/K00546/ 2022-10-11T12:46:18.2919331 2022-09-26T11:36:09.9693616 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Diana C. Dima 0000-0002-9612-5574 1 Gavin Perry 2 Eirini Messaritaki 3 Jiaxiang Zhang 0000-0002-4758-0394 4 Krish D. Singh 5 61341__25409__9bebac6a73a54b89b1032f6c4b057fbc.pdf 61341_VoR.pdf 2022-10-11T12:44:34.2535162 Output 14045571 application/pdf Version of Record true Copyright: 2018 The Authors. This is an open access article under the terms of the Creative Commons Attribution License true eng http://creativecommons.org/licenses/by/4.0/
title	Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces
spellingShingle	Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces Jiaxiang Zhang
title_short	Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces
title_full	Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces
title_fullStr	Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces
title_full_unstemmed	Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces
title_sort	Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces
author_id_str_mv	555e06e0ed9a87608f2d035b3bde3a87
author_id_fullname_str_mv	555e06e0ed9a87608f2d035b3bde3a87_***_Jiaxiang Zhang
author	Jiaxiang Zhang
author2	Diana C. Dima Gavin Perry Eirini Messaritaki Jiaxiang Zhang Krish D. Singh
format	Journal article
container_title	Human Brain Mapping
container_volume	39
container_issue	10
container_start_page	3993
publishDate	2018
institution	Swansea University
issn	1065-9471
doi_str_mv	10.1002/hbm.24226
publisher	Wiley
college_str	Faculty of Science and Engineering
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hierarchy_top_id	facultyofscienceandengineering
hierarchy_top_title	Faculty of Science and Engineering
hierarchy_parent_id	facultyofscienceandengineering
hierarchy_parent_title	Faculty of Science and Engineering
department_str	School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
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description	Recognizing emotion in faces is important in human interaction and survival, yet existing studies do not paint a consistent picture of the neural representation supporting this task. To address this, we collected magnetoencephalography (MEG) data while participants passively viewed happy, angry and neutral faces. Using time-resolved decoding of sensor-level data, we show that responses to angry faces can be discriminated from happy and neutral faces as early as 90 ms after stimulus onset and only 10 ms later than faces can be discriminated from scrambled stimuli, even in the absence of differences in evoked responses. Time-resolved relevance patterns in source space track expression-related information from the visual cortex (100 ms) to higher-level temporal and frontal areas (200–500 ms). Together, our results point to a system optimised for rapid processing of emotional faces and preferentially tuned to threat, consistent with the important evolutionary role that such a system must have played in the development of human social interactions.
published_date	2018-10-01T04:20:07Z
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Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces

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