Dynamical coding of sensory information with competitive networks

Based on experiments with the locust olfactory system, we demonstrate that model sensory neural networks with lateral inhibition can generate stimulus specific identity-temporal patterns in the form of stimulus-dependent swit ching among small and dynamically changing neural ensembles (each ensemble being a group of synchronized projection neurons). Networks produce this sw itching mode of dynamical activity when lateral inhibitory connections are strongly non-symmetric. Such coding uses 'winner-less competitive' (WLC) dy namics. In contrast to the well known winner-take-all competitive (WTA) net works and Hopfield nets, winner-less competition represents sensory informa tion dynamically. Such dynamics are reproducible, robust against intrinsic noise and sensitive to changes in the sensory input. We demonstrate the val idity of sensory coding with WLC networks using two different formulations of the dynamics, namely the average and spiking dynamics of projection neur ons (PN). (C) 2000 Elsevier Science Ltd. Published by Editions scientifique s et medicales Elsevier SAS.