Detecting long-range correlations in time series of dorsal horn neuron discharges

Abstract

We have studied the discharge dynamics of dorsal horn neurons by applying the detrended fluctuation analysis and the wavelet transform technique. We have adopted that the neuronal discharge dynamics is manifested by the random time series of interspike intervals. In all cases studied, we found two different power-law type behaviors across interspike intervals enumeration scale, that are separated by crossover regions (which implies existence of two different types of neuronal noise). Our results reveal that complex neuronal dynamics may change in the presence of external stimulation, manifested by changing of the noise characteristics that appear before crossover.