An Integrated Neural Framework for Dynamic and Static Face Processing

Abstract Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable...

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Autores principales:	Michal Bernstein, Yaara Erez, Idan Blank, Galit Yovel
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/841e456192304780b8660cf4ffac3f91
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spelling	oai:doaj.org-article:841e456192304780b8660cf4ffac3f912021-12-02T11:40:15ZAn Integrated Neural Framework for Dynamic and Static Face Processing10.1038/s41598-018-25405-92045-2322https://doaj.org/article/841e456192304780b8660cf4ffac3f912018-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-25405-9https://doaj.org/toc/2045-2322Abstract Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable aspects, such as expression and eye gaze, that engage the posterior superior temporal sulcus face area (pSTS-FA). Recent studies report a second dissociation within this network such that the pSTS-FA, but not the FFA, shows much stronger response to dynamic than static faces. The aim of the current study was to test a unified model that accounts for these two functional characteristics of the neural face network. In an fMRI experiment, we presented static and dynamic faces while subjects judged an invariant (gender) or a changeable facial aspect (expression). We found that the pSTS-FA was more engaged in processing dynamic than static faces and changeable than invariant aspects, whereas the OFA and FFA showed similar response across all four conditions. These findings support an integrated neural model of face processing in which the ventral areas extract form information from both invariant and changeable facial aspects whereas the dorsal face areas are sensitive to dynamic and changeable facial aspects.Michal BernsteinYaara ErezIdan BlankGalit YovelNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Michal Bernstein Yaara Erez Idan Blank Galit Yovel An Integrated Neural Framework for Dynamic and Static Face Processing
description	Abstract Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable aspects, such as expression and eye gaze, that engage the posterior superior temporal sulcus face area (pSTS-FA). Recent studies report a second dissociation within this network such that the pSTS-FA, but not the FFA, shows much stronger response to dynamic than static faces. The aim of the current study was to test a unified model that accounts for these two functional characteristics of the neural face network. In an fMRI experiment, we presented static and dynamic faces while subjects judged an invariant (gender) or a changeable facial aspect (expression). We found that the pSTS-FA was more engaged in processing dynamic than static faces and changeable than invariant aspects, whereas the OFA and FFA showed similar response across all four conditions. These findings support an integrated neural model of face processing in which the ventral areas extract form information from both invariant and changeable facial aspects whereas the dorsal face areas are sensitive to dynamic and changeable facial aspects.
format	article
author	Michal Bernstein Yaara Erez Idan Blank Galit Yovel
author_facet	Michal Bernstein Yaara Erez Idan Blank Galit Yovel
author_sort	Michal Bernstein
title	An Integrated Neural Framework for Dynamic and Static Face Processing
title_short	An Integrated Neural Framework for Dynamic and Static Face Processing
title_full	An Integrated Neural Framework for Dynamic and Static Face Processing
title_fullStr	An Integrated Neural Framework for Dynamic and Static Face Processing
title_full_unstemmed	An Integrated Neural Framework for Dynamic and Static Face Processing
title_sort	integrated neural framework for dynamic and static face processing
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/841e456192304780b8660cf4ffac3f91
work_keys_str_mv	AT michalbernstein anintegratedneuralframeworkfordynamicandstaticfaceprocessing AT yaaraerez anintegratedneuralframeworkfordynamicandstaticfaceprocessing AT idanblank anintegratedneuralframeworkfordynamicandstaticfaceprocessing AT galityovel anintegratedneuralframeworkfordynamicandstaticfaceprocessing AT michalbernstein integratedneuralframeworkfordynamicandstaticfaceprocessing AT yaaraerez integratedneuralframeworkfordynamicandstaticfaceprocessing AT idanblank integratedneuralframeworkfordynamicandstaticfaceprocessing AT galityovel integratedneuralframeworkfordynamicandstaticfaceprocessing
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An Integrated Neural Framework for Dynamic and Static Face Processing

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