[PDF] A saliency map in primary visual cortex | Semantic Scholar

Perceptual learning of tasks to detect targets among uniform background items involves changing intra-cortical interactions in the primary visual cortex (V1), and suppression between V1 neurons responding to background, rather than target, visual items is predicted to increase over the course of such learning.

This work studies the feature integration problem and proposes two improved strategies: first, a weighted linear combination of features using the constraint linear regression algorithm, and second, an AdaBoost based algorithm to approach the feature selection, thresholding, weight assignment, and nonlinear integration in a single principled framework.

Evidence for mechanisms in the primate brain that integrate bottom-up saliency with internal goals for flexible orienting towards behaviorally relevant stimuli is reviewed and novel issues and insights are raised that challenge current views about the neural basis of saliency, attention, and orienting.