On the interpretation of voltage-clamp data using the Hodgkin-Huxley Model

• Published in: Mathematical biosciences 1993-05, Vol.115 (1), p.65-101
• Main Authors: Beaumont, J., Roberge, F.A., Leon, L.J.
• Format: Article
• Language: English
• Subjects: Algorithms; Animals; Biological and medical sciences; Cell physiology; Computer Simulation; Electrophysiology; Fundamental and applied biological sciences. Psychology; Ion Channels - physiology; Mathematics; Membrane and intracellular transports; Models, Biological; Molecular and cellular biology
• ISSN: 0025-5564; 1879-3134
• DOI: 10.1016/0025-5564(93)90047-E

This paper describes a method to extract membrane model parameters from experimental voltage-clamp records. The underlying theory is based on two premises: (1) the membrane dynamics can be described by a Hodgkin-Huxley (HH) model, and (2) the most reliable data provided by voltage clamp experiments are peak current ( I p) measurements. First, the steady-state characteristics of activation ( x ∞) and inactivation ( z ∞) must be estimated, and it is shown that I p data provided by standard voltage-clamp stimulation protocols are sufficient for this purpose for the case of well-separated activation (τ x) and inactivation (τ z) time constants, τ x ⪡ τ z. Next, we propose a test ( R test) to establish the suitability of the HH model to represent the data. When the HH model is applicable (successful R test), the procedure yields the degree of the gating variables, a range of maximum membrane conductance ( ḡ) values, and a τ x τ z ratio that relates x ∞ and z ∞ to the I p data. When additional information is available, such as the time of occurence of I p or an estimate of τ z> from the late portion of the ionic current response, one can narrow down the value of ḡ and estimate all the HH parameters and functions. Otherwise, when the R test is not successful, one can conclude that x ∞ and z ∞ have been incorrectly estimated because τ x and τ z are not sufficiently separated or that the HH model is not applicable to the data.