CorrectCoxVramp---a-Python-function-for-correcting-space-clamp-errors-in-voltage-ramp-experiments

Successful modeling of how neurons integrate their synaptic inputs requires, among other things, knowledge of the voltage-dependence of ion-channel specific conductances. In attempting to develop such a model, the natural experimental methodology of choice is the voltage ramp. Unfortunately, when applied to neurons, whole-cell voltage-ramp suffers from the problem of poor space clamp. That is, the intracellular voltage is accurately controlled only at the recording/current-injection site. The use of membrane patches (inside-out, outside-out or even, for sufficiently low currents, cell attached) obviates this problem but presents its own difficulties. Therefore whole-cell recording - with an appropriate correction for space-clamp error - is still an invaluable tool for obtaining the data needed for accurate description and modeling of intrinsic signaling processes in neurons. The Python function CorrectCoxVramp, together with a neuron model implemented in the simulator NEURON, allows for the correction of space-clamp errors in voltage-ramp experiments. Details of the algorithm and an application can be found in: Murphy R., Alle H., Geiger J.R.P. and Storm J. (2024) "Estimation of persistent sodium-current density in rat hippocampal mossy fiber boutons: correction of space-clamp errors", The Journal of Physiology 602, 1703-1732; http://doi.org/10.1113/JP284657. V-ramp data from their study are provided as a .ZIP file.