Image statistics underlying natural texture selectivity of neurons in macaque V4.

ABSTRACT: Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron's preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for

SUBMITTER: Okazawa G 

PROVIDER: S-EPMC4313822 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature