Moving and Static Faces, Bodies, Objects, and Scenes Are Differentially Represented across the Three Visual Pathways.


Journal

Journal of cognitive neuroscience
ISSN: 1530-8898
Titre abrégé: J Cogn Neurosci
Pays: United States
ID NLM: 8910747

Informations de publication

Date de publication:
22 Mar 2024
Historique:
medline: 25 3 2024
pubmed: 25 3 2024
entrez: 25 3 2024
Statut: aheadofprint

Résumé

Models of human cortex propose the existence of neuroanatomical pathways specialized for different behavioral functions. These pathways include a ventral pathway for object recognition, a dorsal pathway for performing visually guided physical actions, and a recently proposed third pathway for social perception. In the current study, we tested the hypothesis that different categories of moving stimuli are differentially processed across the dorsal and third pathways according to their behavioral implications. Human participants (n = 30) were scanned with fMRI while viewing moving and static stimuli from four categories (faces, bodies, scenes, and objects). A whole-brain group analysis showed that moving bodies and moving objects increased neural responses in the bilateral posterior parietal cortex, parts of the dorsal pathway. By contrast, moving faces and moving bodies increased neural responses, the superior temporal sulcus, part of the third pathway. This pattern of results was also supported by a separate ROI analysis showing that moving stimuli produced more robust neural responses for all visual object categories, particularly in lateral and dorsal brain areas. Our results suggest that dynamic naturalistic stimuli from different categories are routed in specific visual pathways that process dissociable behavioral functions.

Identifiants

pubmed: 38527070
pii: 120300
doi: 10.1162/jocn_a_02139
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-13

Subventions

Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/P006981/1
Pays : United Kingdom

Informations de copyright

© 2024 Massachusetts Institute of Technology.

Auteurs

Emel Küçük (E)

University of York.

Matthew Foxwell (M)

University of York.

Daniel Kaiser (D)

University of York.
Justus-Liebig-Universität Gießen.
Philipps-Universität Marburg, and Justus-Liebig-Universität Gießen.

David Pitcher (D)

University of York.

Classifications MeSH