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

Abstract

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: 1993). Golowasch et al. (Golowasch J, Thomas G, Taylor AL, Patel A, Pineda A, Khalil C, Nadim F. J Neurophysiol 102: [2161][2162][2163][2164][2165][2166][2167][2168][2169][2170][2171][2172][2173][2174][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 (Ϫ95 to Ϫ35 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. stomatogastric neurons; lobster; Panulirus interruptus CAPACITANCE is a defining characteristic of neuron electrical properties. Because membrane-specific capacitance varies little across neurons, typically being 0.9 F/cm 2 (Gentet et al . 2000), neuron capacitance also estimates neuron surface area. Accurately measuring capacitance is therefore important in studying neuron development and morphology, characterizing neuron conductances, and neuron modeling. With respect to modeling, membrane currents change membrane voltage by acting through membrane capacitance. Model membrane potential dynamics thus critically depend on capacitance. Simply stated, no matter how accurate the description of neuron currents, without an accurate value of capacitance, neuron models give incorrect activity. In a bursting pyloric model neuron (Fig. 1A), increasing capacitance twofold increased interburst interval and decreased burst duration (Fig. 1B) and a ...

Non-linear leak currents affect mammalian neuron physiology

“…In somato-gastric neurons, White and Hooper ( 2013 ) reported a non-linear relationship between input resistance and input capacitance with membrane potential similar to that observed here. They speculated that it is caused by various voltage-gated ionic currents (A-type K + , persistent Na + , Ca 2+ , Ca 2+ -activated K + ) that activate at potentials more negative than −75 mV (Turrigiano et al, 1995 ; Prinz et al, 2003 ; White and Hooper, 2013 ). Although our study does not rule out this possibility, it provides a simpler explanation for the non-linear properties they reported.…”

“…The non-linear relationship between R n /tau and membrane potential, affect many routine electrophysiological measurements. If observed, they may be interpreted as evidence for the activation of voltage-gated channels by depolarization as the non-linearity has a similar potential-dependent effect on R n and tau (Figure 2B ; Rall, 1969 ; Koch, 1999a , b ; White and Hooper, 2013 ). If present, the non-linearity will greatly affect voltage-clamp experiments (Figure 5A ).…”

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“…Input resistance was calculated based on the current amplitude required to hyperpolarize the cell to 10 mV below the resting membrane potential. The relaxing phase of voltage traces after hyperpolarizing current injections were fitted with double exponentials using fmincon in MATLAB’s optimization toolbox and the slowest time constant was used to calculate the capacitance of the cell ( White and Hooper, 2013 ). Putative spiking threshold was estimated from phase plots (dVm/dt vs Vm) of intracellular voltage (Vm) ( Bean, 2007 ).…”

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“…However, consistent with Tompkins et aland our finding of rheobase being increased in DB21, we found that median input resistance (Figure 4B) was significantly reduced in DB21 (Mdn = 42.5, IQR = 51.8-37.3, MΩ) (Dunn’s test; p < 0.004) but not in DB10 (Mdn = 51.0, IQR = 89.0-38.0, MΩ) (Dunn’s test, p > 0.05) neurons vs WT (Mdn = 68, IQR = 89.0-44.0, MΩ) neurons [Kruskal-Wallis ANOVA on ranks, H (2) = 10.641, p =0.005]. We next estimated time constant by a 2-exponential fit (Golowasch et al 2009; White and Hooper 2013). Median time constant (Figure 4C) showed a similar pattern, showing a significant reduction in DB21 (Mdn = 1.8, IQR = 2.5-1.5, ms) compared to WT (Mdn = 2.3, IQR = 3.2-1.6, ms) (Dunn’s test, p < 0.01), but not compared to DB10 (Mdn = 2.5, IQR = 4.2-1.7, ms)(Dunn’s test, p > 0.05 [Kruskal-Wallis one way ANOVA on ranks, H (2) = 6.805, p =0.033].…”

“…A paired t-test showed that hyperpolarization duration did not significantly affect these measurements, the closest measurement to being affected was AHP (t (11) = 2.090, p = 0.061) while all other properties were unaffected (p > 0.1). Due to the contamination of slow activating currents and membranes being non-isopotential in real neurons, time was estimated by the 2 exponential fit; ; the larger A (IR) and time constant term were taken to be the time constant (Golowasch et al 2009; White and Hooper 2013). Capacitance was estimated from this time constant and input resistance.…”