Innovative Methodology Contamination of current-clamp measurement of neuron capacitance by voltage-dependent phenomena

White WE, Hooper SL. Contamination of current-clamp measurement of neuron capacitance by voltage-dependent phenomena. J Neurophysiol 110: 257–268, 2013. First published April 10, 2013; doi:10.1152/jn.00993.2012.—Measuring neuron capacitance is important for morphological description, conductance characterization, and neuron modeling. One method to estimate capacitance is to inject current pulses into a neuron and fit the resulting changes in membrane potential with multiple exponentials; if the neuron is purely passive, the amplitude and time constant of the slowest exponential give neuron capacitance (Major G, Evans JD, Jack JJ. Biophys J 65: 423–449, 1993). Golowasch et al. (Golowasch J, Thomas G, Taylor AL, Patel A, Pineda A, Khalil C, Nadim F. J Neurophysiol 102: 2161–2175, 2009) have shown that this is the best method for measuring the capacitance of nonisopotential (i.e., most) neurons. However, prior work has not tested for, or examined how much error would be introduced by, slow voltage-dependent phenomena possibly present at the membrane potentials typically used in such work. We investigated this issue in lobster (Panulirus interruptus) stomatogastric neurons by performing current clamp-based capacitance measurements at multiple membrane potentials. A slow, voltage-dependent phenomenon consistent with residual voltage-dependent conductances was present at all tested membrane potentials ( 95 to 35 mV). This phenomenon was the slowest component of the neuron’s voltage response, and failure to recognize and exclude it would lead to capacitance overestimates of several hundredfold. Most methods of estimating capacitance depend on the absence of voltage-dependent phenomena. Our demonstration that such phenomena make nonnegligible contributions to neuron responses even at well-hyperpolarized membrane potentials highlights the critical importance of checking for such phenomena in all work measuring neuron capacitance. We show here how to identify such phenomena and minimize their contaminating influence.