Relation between shapes of post‐synaptic potentials and changes in firing probability of cat motoneurones

Abstract

The shapes of post-synaptic potentials (PSP) in cat motoneurons were compared with the time course of changes in firing probability during repetitive firing. Excitatory and inhibitory post-synaptic potentials (EPSP and IPSP) were evoked by electrical stimulation of peripheral nerve filaments. With the motoneuron quiescent, the shape of each PSP was obtained by compiling post-stimulus averages of the membrane potential. Depolarizing current was then injected to evoke repetitive firing, and the post-stimulus time histogram of motoneuron spikes was obtained; this histogram reveals the primary features (peak and/or trough) of the cross-correlogram between stimulus and spike trains. The time course of the correlogram features produced by each PSP was compared with the PSP shape and its temporal derivative. EPSP of different sizes (0.15-3.1 mV, mean 0.75 mV) and shapes were investigated. The primary correlogram peak began, on the average, 0.48 ms after onset of the EPSP and reached a maximum 0.29 msec before th summit of the EPSP in many cases the correlogram peak was followed by a trough, in which firing rate fell below base-line rate. The height of the correlogram peak with respect to base-line firing rate increased in proportion to both the amplitude of the EPSP and the magnitude of their rising slope (in these data, amplitude and rising slope also covaried). The primary correlogram features produced by large IPSP did not resemble any linear combination of the shape of the IPSP and/or its temporal derivative. The integral of the correlogram did not resemble the IPSP. The major observations are consistent with a motoneuron model in which a membrane potential ramp approaches a voltage threshold for spike initiation. Near threshold EPSP superimposed on the ramp advance the occurrence of spikes to their rising phase, producing a correlogram peak resembling their temporal derivative. Synaptic noise would increase the probability of sampling the peak of the EPSP, leading to wider correlogram peaks. IPSP would delay the occurrence of spikes to their falling phase.