Simulating the temporal evolution of neuronal discharge

doi:10.1016/S0925-2312(00)00148-X

Neurocomputing

Volumes 32–33, June 2000, Pages 91-96

https://doi.org/10.1016/S0925-2312(00)00148-X Get rights and content

Abstract

Computer simulation was employed to explore the discharge behavior of one- and two-compartment models of a cerebellar Purkinje cell in response to climbing fiber and current pulse stimulation. We could not find a unique parameter set for any model that replicated the full temporal detail of reported discharge patterns. However, simplified composite models gave a better match than those employing Hodgkin–Huxley (HH)-type conductances. The better match achieved by the simpler models suggests that the composite level of description is well suited to simulation of the temporal detail required for the realistic simulation of large-scale neuronal networks.

Introduction

It is just over half a century since Lashley observed that “… the problem of temporal integration seems … to be the most important and the most neglected of cerebral physiology”, then speculated that such integration must be a property of local circuits [3]. Clearly, however, the network properties underlying the ordering of behavioral acts must depend on the characteristics of the individual cells constituting these networks. Nonetheless, there are still few examples in the literature where simulation results are explicitly compared with reported patterns of cell discharge.

Consequently, our aim was to identify a simplified but realistic cell model based on known electrophysiological characteristics that exhibited appropriate temporal discharge patterns and was suitable for incorporation into a large scale neuronal network. The method was to choose representative data sets from the literature and determine which of the two different modelling approaches gave a better match to the temporal evolution of the empirical data.

Section snippets

Four model Purkinje cells

Four different Purkinje neuron models were developed. Parameter values were based on data published for the rat and guinea pig. Simulations were implemented with difference equations.

Climbing fiber activation

Climbing fiber activation in each of the four model PCs was described by a single alpha function of time. In the two-compartment cells this input was distributed equally between the soma and the dendrite. The model PCs were tuned to match target profiles given in Fig. 1 of [4]. The addition of g_sAHP to the one-compartment composite cell helped match the afterdepolarization period of the target profiles (Fig. 1A). The two-compartment composite cell did not employ this conductance (Fig. 1B). The

Conclusions

We could not find a single parameter set for any of our model cells that gave a detailed match to the required responses for both current injection and climbing fiber activation. However, the composite cells exhibited substantial functional realism with little increase in computational complexity over that of a leaky integrator model cell. We were very surprised to discover that overall the composite cells appeared to give a better match to the empirical data than the HH-based model cells,

References (5)

E De Schutter et al.
An active membrane model of the cerebellar Purkinje cell, I. Simulation of current clamps in slice
J. Neurophysiol.
(1994)
A.R Kay et al.
Kinetic and stochastic properties of a persistent sodium current in mature guinea pig cerebellar Purkinje cells
J. Neurophysiol.
(1998)

There are more references available in the full text version of this article.

Cited by (2)

Deciphering the neural code: Neuronal discharge variability is preferentially controlled by the temporal distribution of afferent impulses
2001, Neurocomputing
Neuronal discharge variability has typically been studied as a function of stimulus rate in the context of a Poisson point process. Here we report that novel discharge behavior is elicited in a model cerebellar Purkinje cell when the timing of afferent impulses follows a pulsed Gaussian stimulation paradigm. We show that under these circumstances effective convergence superseded frequency of activation as the independent variable controlling cell discharge. This provides strong evidence that firing rate alone is an insufficient foundation for the neural code.
The composite neuron: A realistic one-compartment Purkinje cell model suitable for large-scale neuronal network simulations
2001, Journal of Computational Neuroscience

^☆: This work was supported by Neurosciences Research Foundation.

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Simulating the temporal evolution of neuronal discharge☆