An algorithm for simulating neuronal networks

Tagged as: neuroscience, algorithm
written on 2013-06-04

The simulation of a neuronal network model with N neurons can be represented as a sequence of transformations. We assume the constant matrix W of size N by N contains the synaptic weights of each connection in the network. We further assume that the global delay of synaptic events is represented by a delay matrix D of dimensions N by T, where T is the global delay as number of time steps.

The algorithm outlined above assumes a single type of synaptic connection. This restriction can be lifted by extending W to be of dimensions N by N by K, where K is the number of synaptic connection types, and extending I to be of dimensions N by K. The assumption that W is constant can be lifted by introducing a function that computesthe new value of W for each time step.