Modelling the effects of ephaptic coupling on selectivity and response patterns during artificial stimulation of peripheral nerves

Miguel Capllonch-Juan and Francisco Sepulveda

PLOS Computational Biology, 2020, vol. 16, issue 6, 1-26

Abstract: Artificial electrical stimulation of peripheral nerves for sensory feedback restoration can greatly benefit from computational models for simulation-based neural implant design in order to reduce the trial-and-error approach usually taken, thus potentially significantly reducing research and development costs and time. To this end, we built a computational model of a peripheral nerve trunk in which the interstitial space between the fibers and the tissues was modelled using a resistor network, thus enabling distance-dependent ephaptic coupling between myelinated axons and between fascicles as well. We used the model to simulate a) the stimulation of a nerve trunk model with a cuff electrode, and b) the propagation of action potentials along the axons. Results were used to investigate the effect of ephaptic interactions on recruitment and selectivity stemming from artificial (i.e., neural implant) stimulation and on the relative timing between action potentials during propagation. Ephaptic coupling was found to increase the number of fibers that are activated by artificial stimulation, thus reducing the artificial currents required for axonal recruitment, and it was found to reduce and shift the range of optimal stimulation amplitudes for maximum inter-fascicular selectivity. During propagation, while fibers of similar diameters tended to lock their action potentials and reduce their conduction velocities, as expected from previous knowledge on bundles of identical axons, the presence of many other fibers of different diameters was found to make their interactions weaker and unstable.Author summary: The design of neural interfaces for artificial electrical stimulation in prostheses can greatly benefit from simulations using electrode-nerve interface models. Studies on electrical stimulation of nerves generally neglect the effects of ephaptic coupling (i.e., coupling between axon fibers and bundles due to their local electric fields) on axon responses to stimulation as ephaptic coupling is normally assumed to play no significant role in bundles of myelinated axons. However, studies have shown that ephaptic effects are non negligible in mammalian peripheral nerves. As such, we have built a resistor network model of a small peripheral nerve trunk for simulation of ephaptic interactions between axons under artificial electrical stimulation. Results show that ephaptic coupling clearly increases axon recruitment and, hence, influences selectivity. On the other hand, the ephaptic coupling effects during action potential propagation observed in this work are more complex than the known effects for ideal, homogeneous bundles. In this work, heterogeneity and variability of fiber diameters in a bundle were found to greatly diminish the strength of ephaptic interactions to the point where these interactions do not play a relevant role on action potential propagation.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1007826

DOI: 10.1371/journal.pcbi.1007826

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