Estimation of electrotonic parameters of neurons using an inverse Fourier transform technique.

Abstract

The objective of this paper is to estimate the passive electrotonic parameters of hippocampal granule cells. Accurate estimation of these parameters is important in understanding the information processing of neurons. A shunt cable model, where the somatic and dendritic time constants can be different, is used to describe the potential changes in the soma and along the dendritic tree. For this model, parameter values are estimated by nonlinear least-squares fitting of the model output to the voltage response of the stimulated cell to current pulses. The solutions are obtained in a two-step process: First, the sensitivity functions are derived from the Laplace transform solution of the theoretical model. Second, the time domain solutions are obtained numerically by an inverse FFT. A sensitivity analysis indicates that accurate estimates require the use of a short current pulse injected at the soma and the sampling of the voltage response close to the end of that pulse. This parameter estimation procedure has been tested on hippocampal granule cells. It yields accurate estimation of neural parameters and will be a useful tool for measuring passive properties of neurons.