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Involvement of top-down networks in the perception of facial emotions: A magnetoencephalographic investigation

Authors :
Diljit Singh Kajal
Chiara Fioravanti
Adham Elshahabi
Sergio Ruiz
Ranganatha Sitaram
Christoph Braun
Source :
NeuroImage, Vol 222, Iss , Pp 117075- (2020)
Publication Year :
2020
Publisher :
Elsevier, 2020.

Abstract

Conscious perception of the emotional valence of faces has been proposed to involve top-down and bottom-up information processing. Yet, the underlying neuronal mechanisms of these two processes and the implementation of their cooperation is still unclear. According to the global workspace model, higher level cognitive processing of visual emotional stimuli relies on both bottom-up and top-down processing. Using masking stimuli in a visual backward masking paradigm with delays at the perceptual threshold, at which stimuli can only partly be detected, suggests that only top-down processing differs between correctly and incorrectly perceived stimuli, while bottom-up visual processing is not compromised and comparable for both conditions. Providing visual stimulation near the perceptual threshold in the backward masking paradigm thus enabled us to compare differences in top-down modulation of the visual information of correctly and incorrectly recognized facial emotions in 12 healthy individuals using magnetoencephalography (MEG). For correctly recognized facial emotions, we found a right-hemispheric fronto-parietal network oscillating in the high-beta and low-gamma band and exerting top-down control as determined by the causality measure of phase slope index (PSI). In contrast, incorrect recognition was associated with enhanced coupling in the gamma band between left frontal and right parietal regions. Our results indicate that the perception of emotional face stimuli relies on the right-hemispheric dominance of synchronized fronto-parietal gamma-band activity.

Details

Language :
English
ISSN :
10959572
Volume :
222
Issue :
117075-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.f7aa717345bd49e2948e8ca6b2409727
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2020.117075