Dynamics of networks of randomly connected excitatory and inhibitory spiking neurons

Recent advances in the understanding of the dynamics of populations of spik ing neurones are reviewed. These studies shed Light on how a population of neurones can follow arbitrary Variations in input stimuli, how the dynamics of the population depends on the type of noise, and how recurrent connecti ons influence the dynamics. The importance of inhibitory feedback for the g eneration of irregularity in single cell behaviour is emphasized. Examples of computation that recurrent networks with excitatory and inhibitory cells can perform are then discussed. Maintenance of a network state as an attra ctor of the system is discussed as a model for working memory function, in both object and spatial modalities. These models can be used to interpret a nd make predictions about electrophysiological data in the awake monkey. (C ) 2000 Elsevier Science Ltd. Published by Editions scientifiques et medical es Elsevier SAS.