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Topography of Visual Features in the Human Ventral Visual Pathway / 神经科学通报·英文版
Neuroscience Bulletin ; (6): 1454-1468, 2021.
Artículo en Inglés | WPRIM | ID: wpr-922640
ABSTRACT
Visual object recognition in humans and nonhuman primates is achieved by the ventral visual pathway (ventral occipital-temporal cortex, VOTC), which shows a well-documented object domain structure. An on-going question is what type of information is processed in the higher-order VOTC that underlies such observations, with recent evidence suggesting effects of certain visual features. Combining computational vision models, fMRI experiment using a parametric-modulation approach, and natural image statistics of common objects, we depicted the neural distribution of a comprehensive set of visual features in the VOTC, identifying voxel sensitivities with specific feature sets across geometry/shape, Fourier power, and color. The visual feature combination pattern in the VOTC is significantly explained by their relationships to different types of response-action computation (fight-or-flight, navigation, and manipulation), as derived from behavioral ratings and natural image statistics. These results offer a comprehensive visual feature map in the VOTC and a plausible theoretical explanation as a mapping onto different types of downstream response-action systems.
Asunto(s)

Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Asunto principal: Reconocimiento Visual de Modelos / Estimulación Luminosa / Lóbulo Temporal / Vías Visuales / Percepción Visual / Mapeo Encefálico / Imagen por Resonancia Magnética / Lóbulo Occipital Límite: Animales / Humanos Idioma: Inglés Revista: Neuroscience Bulletin Año: 2021 Tipo del documento: Artículo

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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Asunto principal: Reconocimiento Visual de Modelos / Estimulación Luminosa / Lóbulo Temporal / Vías Visuales / Percepción Visual / Mapeo Encefálico / Imagen por Resonancia Magnética / Lóbulo Occipital Límite: Animales / Humanos Idioma: Inglés Revista: Neuroscience Bulletin Año: 2021 Tipo del documento: Artículo