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.
Highlights
Artificial sensory feedback is becoming a viable way to substantially improve the life quality of amputees [1, 2]
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 on axon responses to stimulation as ephaptic coupling is normally assumed to play no significant role in bundles of myelinated axons
Summary
Artificial sensory feedback is becoming a viable way to substantially improve the life quality of amputees [1, 2]. The task of providing it through neural interfaces saw a first success with [3], and later, sensory feedback was provided in a stable form in [4,5,6], where it helped human subjects to improve their performance at using bidirectional limb prostheses. The quality of artificial sensory feedback greatly depends on the quality of the interface between the artificial sensory device and the patient’s peripheral nervous system (PNS). Such neural interface needs to accurately target specific axons in order to elicit the desired sensations. Optimising implant selectivity is not trivial and demands the use of in vivo experiments and/or computer simulations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
