NEUROFIT: software for fitting Hodgkin–Huxley models to voltage-clamp data

Abstract

I introduce publicly available software for accurate fitting of Hodgkin–Huxley models to voltage-clamp data. I describe the model and non-linear fitting procedure employed by the software and compare its results with the usual method of fitting such models using potassium A-current data from a pyloric dilator cell of the lobster Panulirus interruptus and sodium current data from an electrocyte cell of the electric fish Sternopygus macrurus. The set of parameter values for the model determined by this software yield current traces that are substantially closer to the observed data than those determined from the usual fitting method. This improvement is due to the fact that the software fits all of the parameters simultaneously utilizing all of the data rather than fitting steady-state and time constant parameters disjointly using peak currents and portions of the rising and falling phases. I analyze the convergence properties of the software's fitting algorithm using simulated data showing that accurate parameter values are obtained for most of the parameters using any reasonable initial values. The software also incorporates a linear pre-estimation procedure to help in determining reasonable initial values for the full non-linear algorithm. I illustrate and discuss some of the inadequacies of voltage-clamp data.