In this paper we propose a model for the lateral connectivity of orientation-selective cells in the visual cortex based on informationtheoretic considerations. We study the properties of the input signal to the visual cortex and find new statistical structures which have not been processed in the retino-geniculate pathway. Applying the idea that the system optimizes the representation of incoming signals, we derive the lateral connectivity that will achieve this for a set of local orientation-selective patches, as well as the complete spatial structure of a layer of such patches. We compare the results with various physiological measurements.

In this paper we propose a model for the lateral connectivity of orientation-selective cells in the visual cortex based on informationtheoretic considerations. We study the properties of the input signal to the visual cortex and find new statistical structures which have not been processed in the retino-geniculate pathway. Applying the idea that the system optimizes the representation of incoming signals, we derive the lateral connectivity that will achieve this for a set of local orientation-selective patches, as well as the complete spatial structure of a layer of such patches. We compare the results with various physiological measurements.

In this paper we propose a model for the lateral connectivity of orientation-selective cells in the visual cortex based on informationtheoretic considerations.We study the properties of the input signal to the visual cortex and find new statistical structures which have not been processed in the retino-geniculate pathway. Applying the idea that the system optimizes the representation of incoming signals, we derive the lateral connectivity that will achieve this for a set of local orientation-selective patches, as well as the complete spatial structure of a layer of such patches. We compare the results with various physiological measurements.

A simple mathematical model for the large-scale circuitry of primary visualcortex is introduced. It is shown that a basic cortical architecture of recurrent local excitation and lateral inhibition canaccount quantitatively for such properties as orientation tuning.The model can also account for such local effects as cross-orientation suppression. It is also shown that nonlocal state-dependent coupling between similar orientation patches, when added to the model, can satisfactorily reproduce such effects asnon-local iso--orientation suppression, and non-local crossorientation enhancement.Following this an account is given of perceptual phenomena involving object segmentation, such as "popout", and the direct and indirect tilt illusions.

A simple mathematical model for the large-scale circuitry of primary visual cortex is introduced. It is shown that a basic cortical architecture of recurrent local excitation and lateral inhibition can account quantitatively for such properties as orientation tuning. The model can also account for such local effects as cross-orientation suppression. It is also shown that nonlocal state-dependent coupling between similar orientation patches, when added to the model, can satisfactorily reproduce such effects as non-local iso--orientation suppression, and non-local crossorientation enhancement. Following this an account is given of perceptual phenomena involving object segmentation, such as "popout", and the direct and indirect tilt illusions.