Dataset Information

Learning to link visual contours.

ABSTRACT: In complex visual scenes, linking related contour elements is important for object recognition. This process, thought to be stimulus driven and hard wired, has substrates in primary visual cortex (V1). Here, however, we find contour integration in V1 to depend strongly on perceptual learning and top-down influences that are specific to contour detection. In naive monkeys, the information about contours embedded in complex backgrounds is absent in V1 neuronal responses and is independent of the locus of spatial attention. Training animals to find embedded contours induces strong contour-related responses specific to the trained retinotopic region. These responses are most robust when animals perform the contour detection task but disappear under anesthesia. Our findings suggest that top-down influences dynamically adapt neural circuits according to specific perceptual tasks. This may serve as a general neuronal mechanism of perceptual learning and reflect top-down mediated changes in cortical states.

SUBMITTER: Li W

PROVIDER: S-EPMC2409109 | biostudies-literature | 2008 Feb

REPOSITORIES: biostudies-literature

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Learning to link visual contours.

Li Wu W Piëch Valentin V Gilbert Charles D CD

Neuron 20080201 3

In complex visual scenes, linking related contour elements is important for object recognition. This process, thought to be stimulus driven and hard wired, has substrates in primary visual cortex (V1). Here, however, we find contour integration in V1 to depend strongly on perceptual learning and top-down influences that are specific to contour detection. In naive monkeys, the information about contours embedded in complex backgrounds is absent in V1 neuronal responses and is independent of the l ...[more]

PMID: 18255036

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Dataset Information

Learning to link visual contours.

Publications

Learning to link visual contours.

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