Estimation of electronic parameters of neurons using an inverse Fourier transform technique

The authors estimate the passive electronic parameters of hippocampal granule cells. 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. 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 estimations of neural parameters and will be a useful tool for measuring passive properties of neurons.