STATISTICAL ANALYSIS OF ONGOING ACTIVITY OF NEURONES IN THE SUBSTANTIA GELATINOSA AND IN LAMINA III OF CAT SPINAL CORD

¹ Department of Veterinary Physiology, University of Edinburgh, Edinburgh EH9 1QH
² Department of Experimental Physics, Dniepropetrovsk State University, U.S.S.R.
³ Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Riccarton, Edinburgh, EH14

Intracellular recordings from substantia gelatinosa (s.g.) neurones in chloralose-anaesthetized cats and in decerebrate preparations revealed the existence of ongoing synaptic activity. 59% of s.g. neurones showed ongoing spiking activity at rates of more than one per second. The ongoing activity of twenty s.g. neurones was subjected to statistical analysis. Stationarity was established for the activity of each neurone, the interspike interval (i.s.i.) distributions were bell-shaped, and no evidence of dependency of the length of an interval on the one preceding it was found. The mechanism of spike generation in these neurones is therefore an example of a renewal stochastic process. The pattern of ongoing discharge of twelve neurones recorded in lamina III was markedly different, and generated in each case a unimodal asymmetric i.s.i. histogram with a sharp rise to mode after a short dead time and a slow decay. The activity was stationary only in the long term, and there was strong evidence of dependency of intervals. The spike generating mechanism was therefore an example of a non-renewal stochastic process. The different patterns of activity are discussed in relation to differences in cutaneous input, and it is suggested that the pattern of activity in the s.g. neurones is the result of convergence on the neurones of a large number of small independent excitatory influences, whereas that of the neurones in lamina III is the result of excitation by powerful synchronous synaptic inputs. It is re-emphasized that statistical analysis of neural impulse sequences is a valuable technique in investigation of the function of a neurone within its network.