By the same authors

From the same journal

From the same journal

A functional dissociation of face-, body- and scene-selective brain areas based on their response to moving and static stimuli

Research output: Contribution to journalArticle

Full text download(s)

Author(s)

Department/unit(s)

Publication details

JournalScientific Reports
DateAccepted/In press - 7 May 2019
DatePublished (current) - 3 Jun 2019
Issue number8242
Volume9
Number of pages9
Pages (from-to)1-9
Original languageEnglish

Abstract

the human brain contains areas that respond selectively to faces, bodies and scenes. Neuroimaging studies have shown that a subset of these areas preferentially respond more to moving than static stimuli, but the reasons for this functional dissociation remain unclear. In the present study, we simultaneously mapped the responses to motion in face-, body- and scene-selective areas in the right hemisphere using moving and static stimuli. participants (N = 22) were scanned using functional magnetic resonance imaging (fMRI) while viewing videos containing bodies, faces, objects, scenes or scrambled objects, and static pictures from the beginning, middle and end of each video. Results demonstrated that lateral areas, including face-selective areas in the posterior and anterior superior temporal sulcus (STS), the extrastriate body area (EBA) and the occipital place area (OPA) responded more to moving than static stimuli. By contrast, there was no difference between the response to moving and static stimuli in ventral and medial category-selective areas, including the fusiform face area (FFA), occipital face area (OFA), amygdala, fusiform body area (FBA), retrosplenial complex (RSC) and parahippocampal place area (PPA). This functional dissociation between lateral and ventral/medial brain areas that respond selectively to different visual categories suggests that face-, body- and scene- selective networks may be functionally organized along a common dimension.

Bibliographical note

© The Author(s) 2019

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations