Autocorrelation and fourier analysis for detecting periodic cell potentials in a simulated inhibitory neural network
Robert Rohrkemper · Journal of computing sciences in colleges · 2004
The field of Computational Neuroscience is best described as a mathematical approach to the study of neural systems, reducing them to a set of computational tasks. Computer models are an important part of this analysis for their insight into the phenomenon. In order to begin a meaningful study, one has to find a pattern that exists throughout the brain. Experimental studies have shown that isolated neurons can be naturally periodic - repeating almost clock-like. However, due to inter-neuron interactions, signals from cells in networks are neither perfectly periodic nor completely random. The goal of my analysis was to characterize periodic behavior of inhibitory neurons.