title: 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.
authors.affiliation: LORIA Laboratory, Campus Scientifique, B.P. 239, 54506, Vandoeuvre-lès-Nancy Cedex, France. Nicolas.Rougier@loria.fr
authors.forename: Nicolas P
authors.initials: NP
authors.lastname: Rougier
mesh_terms: D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology*; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics