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Errors in persistent inward currents generated by space-clamp errors: a modeling study
Journal article   Peer reviewed

Errors in persistent inward currents generated by space-clamp errors: a modeling study

John A White, N S Sekar and A R Kay
Journal of neurophysiology, Vol.73(6), pp.2369-2377
06/1995
DOI: 10.1152/jn.1995.73.6.2369
PMID: 7666145

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Abstract

1. The effects of imperfect space clamp on inactivating inward currents were examined with the use of a "ball-and-stick" neuronal model with uniform active and passive membrane properties. With poor space clamp, both transient and steady-state (persistent) components were distorted. The ratio of steady-state to peak current (i(s)/p), measured at the soma, was sometimes smaller but usually larger than would be the case with uniform space clamp. For a fast Na+ current, the anomalous persistent component was largest for large electrotonic lengths, low-conductance densities, and voltage-clamp potentials near the threshold of the current. Under some conditions, steady-state current could take one of two values, depending on the holding potential. 2. Membrane potential as a function of distance was examined, revealing a steady-state voltage gradient in which distal portions of the neuron were more positive than in the passive case, and often more positive than the command potential itself. These reversed voltage gradients, caused by the uncontrolled "window" Na+ current at remote electrotonic distances, produced steady-state axial current flow into the soma, thereby increasing the persistent current measured somatically. 3. The time at which the current peaked (tp) was sensitive to imperfections in the space clamp. This phenomenon made somatic membrane current and axial current at tp sensitive to the fidelity of space clamp as well. The ratio of steady-state axial current to that at t = tp was a good predictor of the degree of distortion of i(s)/p.
 Mathematics Time Factors Neurons - physiology Kinetics Models, Neurological Membrane Potentials - physiology Patch-Clamp Techniques - statistics & numerical data

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