title: Membrane capacitance measurements revisited: dependence of capacitance value on measurement method in nonisopotential neurons.
abstract: During growth or degeneration neuronal surface area can change dramatically. Measurements of membrane protein concentration, as in ion channel or ionic conductance density, are often normalized by membrane capacitance, which is proportional to the surface area, to express changes independently from cell surface variations. Several electrophysiological protocols are used to measure cell capacitance, all based on the assumption of membrane isopotentiality. Yet, most neurons violate this assumption because of their complex anatomical structure, raising the question of which protocol yields measurements that are closest to the actual total membrane capacitance. We measured the capacitance of identified neurons from crab stomatogastric ganglia using three different protocols: the current-clamp step, the voltage-clamp step, and the voltage-clamp ramp protocols. We observed that the current-clamp protocol produced significantly higher capacitance values than those of either voltage-clamp protocol. Computational models of various anatomical complexities suggest that the current-clamp protocol can yield accurate capacitance estimates. In contrast, the voltage-clamp protocol estimates rapidly deteriorate as isopotentiality is reduced. We provide a mathematical description of these results by analyzing a simple two-compartment model neuron to facilitate an intuitive understanding of these methods. Together, the experiments, modeling, and mathematical analysis indicate that accurate total membrane capacitance measurements cannot be obtained with voltage-clamp protocols in nonisopotential neurons. Furthermore, although current-clamp steps can theoretically yield accurate measurements, experimentalists should be aware of limitations imposed by step duration and numerical errors during fitting procedures to obtain the membrane time constant.
authors: Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, New Jersey 07102, USA. Jorge.P.Golowasch@njit.edu
authors: Jorge
authors: J
authors: Golowasch
authors: Gladis
authors: G
authors: Thomas
authors: Adam L
authors: AL
authors: Taylor
authors: Arif
authors: A
authors: Patel
authors: Arlene
authors: A
authors: Pineda
authors: Christopher
authors: C
authors: Khalil
authors: Farzan
authors: F
authors: Nadim
mesh_terms: D000465:Algorithms; D000818:Animals; D001369:Axons / Q000502:physiology; D003386:Brachyura; D002462:Cell Membrane / Q000502:physiology*; D003198:Computer Simulation; D003712:Dendrites / Q000502:physiology; D025802:Electric Capacitance; D017952:Ganglia, Invertebrate / Q000166:cytology / Q000502:physiology; D008839:Microelectrodes; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology / Q000502:physiology*; D018408:Patch-Clamp Techniques / Q000379:methods*