Dynamic neural field with local inhibition

Abstract A lateral-inhibition type neural field model with restricted connections is presented here and represents an experimental extension of the Continuum Neural Field Theory (CNFT) by suppression of the global inhibition. A modified CNFT equation is introduced and allows for a locally defined inhibition to spatially expand within the network and results in a global competition extending far beyond the range of local connections by virtue of diffusion of inhibition. The resulting model is able to attend to a moving stimulus in the presence of a very high level of noise, several distractors or a mixture of both. Key words Dynamic Neural Field

• Type: Journal
• Year: 2006
• Where: BC
• Authors: Nicolas P. Rougier
• Keywords: BC 2006, Continuum Neural Field, Neural Field, Neural Field Model