Discrete simulation of large aggregates of neurons

Realistic simulation of aggregates of neurons often utilises compartmental models which limit the scope of the simulations with single processor architectures to small or medium size networks (typically hundreds of neurons), An alternative approach, based on cell automata models, allows efficient simulation of nervous tissue by modelling neurons as finite state automata. In this paper, data structures and algorithms appropriate for efficient simulation of message-based event-driven models of neurons in single processor architectures are presented. With these techniques, the simulation of large networks (of the order of 10(5) neurons with 10(2) synapses per neuron) becomes feasible. (C) 2002 Elsevier Science B.V. All rights reserved.