Using High-Density Electroencephalography to Explore Spatiotemporal Representations of Object Categories in Visual Cortex.
J Cogn Neurosci
; 34(6): 967-987, 2022 05 02.
Article
em En
| MEDLINE
| ID: mdl-35286384
ABSTRACT
Visual object perception involves neural processes that unfold over time and recruit multiple regions of the brain. Here, we use high-density EEG to investigate the spatiotemporal representations of object categories across the dorsal and ventral pathways. In , human participants were presented with images from two animate object categories (birds and insects) and two inanimate categories (tools and graspable objects). In , participants viewed images of tools and graspable objects from a different stimulus set, one in which a shape confound that often exists between these categories (elongation) was controlled for. To explore the temporal dynamics of object representations, we employed time-resolved multivariate pattern analysis on the EEG time series data. This was performed at the electrode level as well as in source space of two regions of interest one encompassing the ventral pathway and another encompassing the dorsal pathway. Our results demonstrate shape, exemplar, and category information can be decoded from the EEG signal. Multivariate pattern analysis within source space revealed that both dorsal and ventral pathways contain information pertaining to shape, inanimate object categories, and animate object categories. Of particular interest, we note striking similarities obtained in both ventral stream and dorsal stream regions of interest. These findings provide insight into the spatio-temporal dynamics of object representation and contribute to a growing literature that has begun to redefine the traditional role of the dorsal pathway.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Reconhecimento Visual de Modelos
/
Córtex Visual
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
J Cogn Neurosci
Assunto da revista:
NEUROLOGIA
Ano de publicação:
2022
Tipo de documento:
Article