On a method to infer quantitative information about the current driving action potential generation from neuronal spike train data

摘要

Synaptic input to a neuron evokes a current that drives the generation of action potentials. Changes of that current evoke changes of the observed action potential sequences. From this spike train data, the interspike interval superposition plot (IISP) and an interspike interval function (IIF) estimate can be obtained. If the neuronal response is semideterministic, such an output description contains the most information obtainable from spike train data alone (Awiszus 1989a). In this paper a method is introduced that allows a quantitative estimation of the time course of the current driving action potential generation from an experimentally observed IIF. A prerequisite to apply this method is the availability of a valid model for the action potential encoding site of the neuron investigated. The method approximates a current time course which, injected into the model, evokes an IIF almost indistinguishable from the one obtained experimentally and thus yields — assuming the model being valid — a quantitative estimate for the current at the spike initiating site of the investigated neuron. The validity of the method is demonstrated by reconstructing the time course of the input current at the Hodgkin-Huxley model from an IIF obtained from that model. An application of the method to experimental data is shown by estimating the time course of the current driving spike initiation at a human α-motoneuron that is exposed to a low-threshold afferent vo