Learn More
Contour integration is an important intermediate stage of object recognition, in which line segments belonging to an object boundary are perceptually linked and segmented from complex backgrounds. Contextual influences observed in primary visual cortex (V1) suggest the involvement of V1 in contour integration. Here, we provide direct evidence that, in(More)
While recent studies of synaptic stability in adult cerebral cortex have focused on dendrites, how much axons change is unknown. We have used advances in axon labeling by viruses and in vivo two-photon microscopy to investigate axon branching and bouton dynamics in primary visual cortex (V1) of adult Macaque monkeys. A nonreplicative adeno-associated virus(More)
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(More)
Neuronal responses at early stages in visual cortical processing, including those in primary visual cortex (V1), are subject to the influences of visual context, experience and attention. Here we show that for monkeys trained in a shape discrimination task, V1 neurons took on novel functional properties related to the attributes of the trained shapes.(More)
Re-entrant or feedback pathways between cortical areas carry rich and varied information about behavioural context, including attention, expectation, perceptual tasks, working memory and motor commands. Neurons receiving such inputs effectively function as adaptive processors that are able to assume different functional states according to the task being(More)
The strong conical hull intersection property and bounded linear regularity are properties of a collection of nitely many closed convex intersecting sets in Euclidean space. These fundamental notions occur in various branches of convex optimization (constrained approximation, convex feasibility problems, linear inequalities, for instance). It is shown that(More)