Estimation of neuronal population activity changes in rat cerebellum using one electrode

Activity of neuronal populations is usually measured with multielectrode systems. In this paper a procedure is described for estimating population activity changes in rat cerebellar cortex, using one microelectrode. Signals consisted of simple, complex spikes and interspike recorded background activity (RBA). After their separation, simple spikes were averaged, forming a simple spike template (SST). The remaining RBA was simulated (SBA), by superimposing SST waveforms with random time delays and intensities. A series of SBA was formed, differing in the superposition frequency ( f sup) of individual SST. Mean amplitude spectra ( Amp SBA ) were calculated and Amp SBA = f( f sup) treated as a calibration line for estimating activity level of the surrounding neuronal population. Since the uniform probability distribution of SST intensities proved inadequate, we derived a new one, based on the power function for spike intensity vs. electrode distance attenuation. A family of new lines emerged, depending on the model parameters. Since all were linear in the log–log plots, with slopes not varying significantly, we proposed a method for estimating population activity changes in different experimental conditions, using two measured values of Amp RBA . Relative nature of the results makes this method suitable for comparative studies.