Computational modelling of nerve stimulation and recording with peripheral visceral neural interfaces

Abstract

Objective. Neuromodulation of visceral nerves is being intensively studied for treating a wide range of conditions, but effective translation requires increasing the efficacy and predictability of neural interface performance. Here we use computational models of rat visceral nerve to predict how neuroanatomical variability could affect both electrical stimulation and recording with an experimental planar neural interface. Approach. We developed a hybrid computational pipeline, Visceral Nerve Ensemble Recording and Stimulation (ViNERS), to couple finite-element modelling of extracellular electrical fields with biophysical simulations of individual axons. Anatomical properties of fascicles and axons in rat pelvic and vagus nerves were measured or obtained from public datasets. To validate ViNERS, we simulated pelvic nerve stimulation and recording with an experimental four-electrode planar array. Main results. Axon diameters measured from pelvic nerve were used to model a population of myelinated and unmyelinated axons and simulate recordings of electrically evoked single-unit field potentials (SUFPs). Across visceral nerve fascicles of increasing size, our simulations predicted an increase in stimulation threshold and a decrease in SUFP amplitude. Simulated threshold changes were dominated by changes in perineurium thickness, which correlates with fascicle diameter. We also demonstrated that ViNERS could simulate recordings of electrically-evoked compound action potentials (ECAPs) that were qualitatively similar to pelvic nerve recording made with the array used for simulation. Significance. We introduce ViNERS as a new open-source computational tool for modelling large-scale stimulation and recording from visceral nerves. ViNERS predicts how neuroanatomical variation in rat pelvic nerve affects stimulation and recording with an experimental planar electrode array. We show ViNERS can simulate ECAPS that capture features of our recordings, but our results suggest the underlying NEURON models need to be further refined and specifically adapted to accurately simulate visceral nerve axons.

Spinal Evoked Compound Action Potentials in Rats With Clinically Relevant Stimulation Modalities

“…These more atypical morphologies are potentially explainable by effects likely of limited translatability to clinically acquired ECAPs, such as saturation effects and the superposition of ECAPs originating from morphologically diverse fiber populations with high stimulation amplitudes. 31,32 Other explanations include variability in lead placement among rats: the distribution of fiber thicknesses changes mediolaterally, for instance, which could in turn affect the ECAP. 33 Given the unique responses of growth curves across animals, we include the complete set of growth curves (Fig.…”

A novel statistical methodology for quantifying the spatial arrangements of axons in peripheral nerves

“…In this report, we examined one of the key research problems in neuroanatomy, the fundamental description, measurement, and quantification of the spatial arrangement of axons in peripheral nerves such as the vagus and pelvic nerves (Hulsebosch and Coggeshall, 1982 ; Prechtl and Powley, 1990 ). This topic is significant not only from the basic neuroanatomical standpoint, but also due to the growing importance of peripheral nerve electrostimulation approaches, which rely on a precise understanding of the peripheral nerve architecture during the modeling and development phases (Pelot et al, 2020 ; Eiber et al, 2021 ). We believe that quantitative analysis, comparisons, and visualization of spatial arrangement can provide valuable insight to neuroanatomists, computational neuroscientists, and engineers working in the field of electrostimulation.…”

A simple model considering spiking probability during extracellular axon stimulation

“…Most of recent modeling work on extracellular nerve stimulation uses a two-step procedure: (i) determination of the electric potential induced by a stimulating electrode in a biological structure and (ii) prediction of its consequences for single-neuron responses [ 43 , 44 ]. However, ignoring the stochastic current fluctuations across the cell membrane in this approach hinders the prediction of the spiking efficiency seen in experiments (Figs 1 and 3 ).…”