TY - JOUR
T1 - Frequency-dependent responses of neuronal models to oscillatory inputs in current versus voltage clamp
AU - Rotstein, Horacio G.
AU - Nadim, Farzan
N1 - Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - Action potential generation in neurons depends on a membrane potential threshold and therefore on how subthreshold inputs influence this voltage. In oscillatory networks, for example, many neuron types have been shown to produce membrane potential (Vm) resonance: a maximum subthreshold response to oscillatory inputs at a nonzero frequency. Resonance is usually measured by recording Vm in response to a sinusoidal current (Iapp), applied at different frequencies (f), an experimental setting known as current clamp (I-clamp). Several recent studies, however, use the voltage clamp (V-clamp) method to control Vm with a sinusoidal input at different frequencies [Vapp(f) ] and measure the total membrane current (Im). The two methods obey systems of differential equations of different dimensionality, and while I-clamp provides a measure of electrical impedance [Z(f) = Vm(f) / Iapp(f) ], V-clamp measures admittance [Y(f) = Im(f) / Vapp(f) ]. We analyze the relationship between these two measurement techniques. We show that, despite different dimensionality, in linear systems the two measures are equivalent: Z= Y- 1. However, nonlinear model neurons produce different values for Z and Y- 1. In particular, nonlinearities in the voltage equation produce a much larger difference between these two quantities than those in equations of recovery variables that describe activation and inactivation kinetics. Neurons are inherently nonlinear, and notably, with ionic currents that amplify resonance, the voltage clamp technique severely underestimates the current clamp response. We demonstrate this difference experimentally using the PD neurons in the crab stomatogastric ganglion. These findings are instructive for researchers who explore cellular mechanisms of neuronal oscillations.
AB - Action potential generation in neurons depends on a membrane potential threshold and therefore on how subthreshold inputs influence this voltage. In oscillatory networks, for example, many neuron types have been shown to produce membrane potential (Vm) resonance: a maximum subthreshold response to oscillatory inputs at a nonzero frequency. Resonance is usually measured by recording Vm in response to a sinusoidal current (Iapp), applied at different frequencies (f), an experimental setting known as current clamp (I-clamp). Several recent studies, however, use the voltage clamp (V-clamp) method to control Vm with a sinusoidal input at different frequencies [Vapp(f) ] and measure the total membrane current (Im). The two methods obey systems of differential equations of different dimensionality, and while I-clamp provides a measure of electrical impedance [Z(f) = Vm(f) / Iapp(f) ], V-clamp measures admittance [Y(f) = Im(f) / Vapp(f) ]. We analyze the relationship between these two measurement techniques. We show that, despite different dimensionality, in linear systems the two measures are equivalent: Z= Y- 1. However, nonlinear model neurons produce different values for Z and Y- 1. In particular, nonlinearities in the voltage equation produce a much larger difference between these two quantities than those in equations of recovery variables that describe activation and inactivation kinetics. Neurons are inherently nonlinear, and notably, with ionic currents that amplify resonance, the voltage clamp technique severely underestimates the current clamp response. We demonstrate this difference experimentally using the PD neurons in the crab stomatogastric ganglion. These findings are instructive for researchers who explore cellular mechanisms of neuronal oscillations.
KW - Impedance profile
KW - Neural oscillations
KW - Resonance
KW - Sub-threshold resonance
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U2 - 10.1007/s00422-019-00802-z
DO - 10.1007/s00422-019-00802-z
M3 - Article
C2 - 31286211
AN - SCOPUS:85069622359
SN - 0340-1200
VL - 113
SP - 373
EP - 395
JO - Biological Cybernetics
JF - Biological Cybernetics
IS - 4
ER -