title: Optimizing synaptic conductance calculation for network simulations.
abstract: High computational requirements in realistic neuronal network simulations have led to attempts to realize implementation efficiencies while maintaining as much realism as possible. Since the number of synapses in a network will generally far exceed the number of neurons, simulation of synaptic activation may be a large proportion of total processing time. We present a consolidating algorithm based on a recent biophysically-inspired simplified Markov model of the synapse. Use of a single lumped state variable to represent a large number of converging synaptic inputs results in substantial speed-ups.
authors.affiliation: Department of Neurology, University of Wisconsin, Madison 53706, USA.
authors.forename: W W
authors.initials: WW
authors.lastname: Lytton
mesh_terms: D000465:Algorithms; D001369:Axons / Q000502:physiology; D003198:Computer Simulation; D008390:Markov Chains; D016571:Neural Networks, Computer; D013569:Synapses / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*