Voxelwise encoding models of body stimuli reveal a representational gradient from low-level visual features to postural features in occipitotemporal cortex

DOI

Research on body representation in the brain has focused on category-specific representation, using fMRI to investigate the response pattern to body stimuli in occipitotemporal cortex without so far addressing the issue of the specific computations involved in body selective regions, only defined by higher order category selectivity. This study used ultra-high field fMRI and banded ridge regression to investigate the coding of body images, by comparing the performance of three encoding models in predicting brain activity in occipitotemporal cortex and specifically the extrastriate body area (EBA). Our results suggest that bodies are encoded in occipitotemporal cortex and in the EBA according to a combination of low-level visual features and postural features.

Identifier
DOI https://doi.org/10.34894/TZA9S8
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/TZA9S8
Provenance
Creator Marrazzo, Giuseppe ORCID logo; De Martino, Federico ORCID logo; Lage-Castellanos, Agustin ORCID logo; Vaessen, Maarten J. ORCID logo; De Gelder, Beatrice ORCID logo
Publisher DataverseNL
Contributor faculty data manager FPN; De Gelder, Beatrice
Publication Year 2023
Rights CC0-1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact faculty data manager FPN (Maastricht University); De Gelder, Beatrice (Maastricht University)
Representation
Resource Type fMRI data; Dataset
Format text/x-python; application/zip; application/octet-stream; text/x-matlab; application/vnd.openxmlformats-officedocument.wordprocessingml.document; application/matlab-mat; application/x-rar-compressed
Size 15054; 28856962; 5488; 5586; 16307; 200038087; 4578080875; 4797699169; 6649195792; 4879245559; 3807099094; 6409558273; 6380610092; 4905495594; 4293918720; 802524641; 4674399947; 3358407680; 3304488655; 4815801365; 3848610159; 4262469461; 3355648874; 4192114181; 3209846837; 8505726854; 5425918891; 2104
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences