Abstract
A framework within which to generate and characterize populations of correlated spike trains is presented. Spike trains are generated using integrate to threshold and fire type encoders. Spectral analysis techniques form the basis for specifying the strength of correlation within the population. To accurately specify weak correlation, a combined coherence estimate is formed between several independent pairs of spike trains from a population. The aim is to produce populations of spike trains which have a realistic stochastic correlation structure and which can be used to explore the role of correlated neuronal discharge in information processing in neuronal systems.
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