help button home button Biophys. J.
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH

Biophys. J. BioFAST: First Published March 28, 2008. doi:10.1529/biophysj.107.118190
© 2008 by the Biophysical Society.


A more recent version of this article appeared on July 1, 2008.
This Article
Right arrow Full Text (Rapid PDF)
Right arrow Supplement
Right arrow All Versions of this Article:
biophysj.107.118190v1
95/1/66    most recent
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Google Scholar
Right arrow Articles by Milescu, L. S
Right arrow Articles by Smith, J. C
PubMed
Right arrow PubMed Citation
Right arrow Articles by Milescu, L. S
Right arrow Articles by Smith, J. C

BIOPHYSICAL THEORY AND MODELING

Real-time kinetic modeling of voltage-gated ion channels using dynamic clamp

Lorin S Milescu 1*, Tadashi Yamanishi 1, Krzysztof Ptak 1, Murtaza Z Mogri 1 and Jeffrey C Smith 1

1 NINDS, NIH

* To whom correspondence should be addressed. E-mail: milescul{at}ninds.nih.gov.

Submitted on July 24, 2007
Revised on September 4, 2007
Accepted on 12 February 2008


   Abstract
We propose a new technique for modeling the kinetics of voltage-gated ion channels in a functional context, in neurons or other excitable cells. The principle is to pharmacologically block the studied channel type, and to functionally replace it with dynamic clamp, on the basis of a computational model. Then, the parameters of the model are modified in real-time (manually or automatically), with the objective of matching the dynamical behavior of the cell (e.g., action potential shape and spiking frequency), but also the transient and steady-state properties of the model (e.g., derived from voltage-clamp recordings). Through this approach, one may find a model and parameter values that explain both the observed cellular dynamics and the biophysical properties of the channel. We extensively tested the method, focusing on Nav models. Complex Markov models (10-12 states or more) could be accurately integrated in real-time at more than 50 kHz using the transition probability matrix, but not the explicit Euler method. The practicality of the technique was tested with experiments in raphé pacemaker neurons. Through automated real-time fitting, a Hodgkin-Huxley model could be found that reproduced well the action potential shape and the spiking frequency. Adding a virtual axonal compartment with a high density of Nav channels further improved the action potential shape. The computational procedure was implemented in the free QuB software, running under Microsoft Windows and featuring a friendly graphical user interface.

Key Words: Action potential, Hodgkin-Huxley model, Markov model, Na channel, QuB software, Raphé neurons







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH
Copyright © 2008 by the Biophysical Society.