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Common spatiotemporal processing of visual features shapes object representation

Biological vision relies on representations of the physical world at different levels of complexity. Relevant features span from simple low-level properties, as contrast and spatial frequencies, to object-based attributes, as shape and category. However, how these features are integrated into cohere...

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Detalles Bibliográficos
Autores principales: Papale, Paolo, Betta, Monica, Handjaras, Giacomo, Malfatti, Giulia, Cecchetti, Luca, Rampinini, Alessandra, Pietrini, Pietro, Ricciardi, Emiliano, Turella, Luca, Leo, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6527710/
https://www.ncbi.nlm.nih.gov/pubmed/31110195
http://dx.doi.org/10.1038/s41598-019-43956-3
Descripción
Sumario:Biological vision relies on representations of the physical world at different levels of complexity. Relevant features span from simple low-level properties, as contrast and spatial frequencies, to object-based attributes, as shape and category. However, how these features are integrated into coherent percepts is still debated. Moreover, these dimensions often share common biases: for instance, stimuli from the same category (e.g., tools) may have similar shapes. Here, using magnetoencephalography, we revealed the temporal dynamics of feature processing in human subjects attending to objects from six semantic categories. By employing Relative Weights Analysis, we mitigated collinearity between model-based descriptions of stimuli and showed that low-level properties (contrast and spatial frequencies), shape (medial-axis) and category are represented within the same spatial locations early in time: 100–150 ms after stimulus onset. This fast and overlapping processing may result from independent parallel computations, with categorical representation emerging later than the onset of low-level feature processing, yet before shape coding. Categorical information is represented both before and after shape, suggesting a role for this feature in the refinement of categorical matching.