Abstract
Electrical stimulation of neuronal tissue is a promising strategy to treat a variety of neurological disorders. The mechanism of neuronal activation by external electrical stimulation is governed by voltage-gated ion channels. This stimulus, typically brief in nature, leads to membrane potential depolarization, which increases ion flow across the membrane by increasing the open probability of these voltage-gated channels. In spiking neurons, it is activation of voltage-gated sodium channels (NaV channels) that leads to action potential generation. However, several other types of voltage-gated channels are expressed that also respond to electrical stimulation. In this study, we examine the response of voltage-gated potassium channels (KV channels) to brief electrical stimulation by whole cell patch-clamp electrophysiology and computational modeling. We show that nonspiking amacrine neurons of the retina exhibit a large variety of responses to stimulation, driven by different KV-channel subtypes. Computational modeling reveals substantial differences in the response of specific KV-channel subtypes that is dependent on channel kinetics. This suggests that the expression levels of different KV-channel subtypes in retinal neurons are a crucial predictor of the response that can be obtained. These data expand our knowledge of the mechanisms of neuronal activation and suggest that KV-channel expression is an important determinant of the sensitivity of neurons to electrical stimulation.NEW & NOTEWORTHY This paper describes the response of various voltage-gated potassium channels (KV channels) to brief electrical stimulation, such as is applied during prosthetic electrical stimulation. We show that the pattern of response greatly varies between KV channel subtypes depending on activation and inactivation kinetics of each channel. Our data suggest that problems encountered when artificially stimulating neurons such as cessation in firing at high frequencies, or "fading," may be attributed to KV-channel activation.
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