Encoding multiple orientations in a recurrent network

Models containing recurrent connections amongst the cells within a population can account for a range of empirical data on orientation selectivity in striate cortex. However, existing recurrent models are unable to veridically encode more than one orientation at a time. Underlying this inability is an inherent limitation in the variety of activity pro"les that can be stably maintained. We propose a new recurrent model that can form a broader range of stable population activity patterns. We demonstrate that these patterns preserve information about multiple orientations present in the population inputs. This preservation has signi"cant computational consequences when information encoded in several populations must be integrated to perform behavioral tasks, such as visual discrimination. 2000 Elsevier Science B.V. All rights reserved.

• Type: Journal
• Year: 2000
• Where: IJON
• Authors: Richard S. Zemel, Jonathan Pillow
• Keywords: IJON 2000, Recurrent Connections, Recurrent Model, Stable Population Activity