title: Neural network dynamics.
abstract: Neural network modeling is often concerned with stimulus-driven responses, but most of the activity in the brain is internally generated. Here, we review network models of internally generated activity, focusing on three types of network dynamics: (a) sustained responses to transient stimuli, which provide a model of working memory; (b) oscillatory network activity; and (c) chaotic activity, which models complex patterns of background spiking in cortical and other circuits. We also review propagation of stimulus-driven activity through spontaneously active networks. Exploring these aspects of neural network dynamics is critical for understanding how neural circuits produce cognitive function.
authors: Volen Center for Complex Systems and Department of Biology, Brandeis University, Waltham, MA 02454-9110, USA. vogels@brandeis.edu
authors: Tim P
authors: TP
authors: Vogels
authors: Kanaka
authors: K
authors: Rajan
authors: L F
authors: LF
authors: Abbott
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D006801:Humans; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors