A method to estimate the effects of parallel inputs on neuronal discharge probability

Abstract

Abstract. We here present a method to study the interaction of parallel neural input channels regarding their effects on a neurone. In particular, the method allows to disclose the effects of oligosynaptic pathways that may exist in parallel to direct monosynaptic connections to the cell. Two (or more) inputs (nerves) are stimulated with random patterns of stimuli. The response of the cell to these patterns is evaluated by the computation of peristimulus-time histograms (PSTHs). One of the two stimulus trains is selected as the one to yield reference events for the PSTH computation. From this stimulus train are selected those stimuli as reference events which are preceded, at defined mean intervals, by stimuli in the same or a parallel channel. These "conditioning" stimuli are determined (1) separately from each single stimulus train and (2) concomitantly from the two trains as events occurring simultaneously in both. The effects exerted by these various conditioning events on the effects of the "test" pulses on the cell response yield insights into the interactions between the two (or more) inputs. These methods are demonstrated on spinal Renshaw cells activated by independent random stimulation of two muscle nerves and on dorsal horn neurones responding to cutaneous nerve stimulation.

Modulation and transmission of peripheral inputs in monkey cuneate and external cuneate nuclei

“…A Poisson stimulus train has several advantages over using stimulus trains of fixed frequency. It has a flat (white) power spectrum, allowing responses to be measured over a broad frequency spectrum all at once, and it is much quicker to apply than multiple stimulus trains at different frequencies ( Windhorst et al 1989 ; Windhorst et al 1988 ). Coherence analysis can provide an estimate of the input-output relationship as a function of frequency.…”