An application of circular statistics is described which permits one to readily and efficiently describe neuronal discharge patterns recorded during locomotion. The method can be adapted to any data which are normally plotted as post-event histograms (PEHs) and can also be used to describe the pattern of electromyographic (EMG) activity during the step cycle. Data can be objectively classified with respect to both the mean direction and amplitude of their discharge, as well as to the variability (angular deviation) of that discharge. In addition, the Rayleigh test for directionality can be used to determine whether cells are modulated or unmodulated. Finally, the ability to describe each cell's discharge as a single vector allows the data from several different neurones to be displayed on a single figure and provides an efficient method for comparing the discharge of a population of cells under two or more different conditions.