Online decoding of object-based attention using real-time fMRI.
Eur J Neurosci
; 39(2): 319-29, 2014 Jan.
Article
en En
| MEDLINE
| ID: mdl-24438492
ABSTRACT
Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Reconocimiento Visual de Modelos
/
Atención
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Encéfalo
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Mapeo Encefálico
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Imagen por Resonancia Magnética
Tipo de estudio:
Prognostic_studies
Límite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Eur J Neurosci
Asunto de la revista:
NEUROLOGIA
Año:
2014
Tipo del documento:
Article
País de afiliación:
Países Bajos