ArticleJournal of neural engineering2019
On the parameters used in finite element modeling of compound peripheral nerves.
Article in Journal of neural engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Sacral Neuromodulation for Refractory Overactive Bladder: Closing the Gaps in Anatomy, Mechanisms, and Parameter Selection.Advances in therapy · 2026Review
- The optimization of neuroprosthetic interfaces relying on biophysical and surrogate digital twins.npj biomedical innovations · 2026Review
- Computational modeling of human vagus nerve stimulation with three-dimensional fascicular morphology.APL bioengineering · 2026Article
- PyFibers: An open-source NEURON-Python package to simulate responses of model nerve fibers to electrical stimulation.PLoS computational biology · 2025Article
- The human vagal complex: from gross anatomy to single neurons, from brainstem to abdomen.Research square · 2025Article
- Scaling of vagus nerve stimulation parameters does not achieve equivalent nerve responses across species.Bioelectronic medicine · 2025Article
- Control of spatiotemporal activation of organ-specific fibers in the swine vagus nerve by intermittent interferential current stimulation.Nature communications · 2025Article
- Ramped kilohertz-frequency signals produce nerve conduction block without onset response.Journal of neural engineering · 2025Article
- Few-shot segmentation and fiber tractography of human vagus nerve using 3D-MUSE imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Characterization of Machine Learning-Based Surrogate Models of Neural Activation Under Electrical Stimulation.Bioelectromagnetics · 2025Article
- Computational modeling of autonomic nerve stimulation: Vagus et al.Current opinion in biomedical engineering · 2024Article
- A finite element model for biomechanical characterization of ex vivo peripheral nerve dysfunction during stretch.Physiological reports · 2024Article
- Quasistatic approximation in neuromodulation.Journal of neural engineering · 2024Review
- NRV: An open framework for in silico evaluation of peripheral nerve electrical stimulation strategies.PLoS computational biology · 2024Article
- AxoDetect: an automated nerve image segmentation and quantification workflow for computational nerve modeling.Journal of neural engineering · 2024Article
- Computational models of compound nerve action potentials: Efficient filter-based methods to quantify effects of tissue conductivities, conduction distance, and nerve fiber parameters.PLoS computational biology · 2024Article
- NRV: An open framework forbioRxiv : the preprint server for biology · 2024Article
- Validated computational models predict vagus nerve stimulation thresholds in preclinical animals and humans.Journal of neural engineering · 2023Article
- Design of an adaptable intrafascicular electrode (AIR) for selective nerve stimulation by model-based optimization.PLoS computational biology · 2023Article
- Fibers in smaller fascicles have lower activation thresholds with cuff electrodes due to thinner perineurium and smaller cross-sectional area.Journal of neural engineering · 2023Article
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3 authors.
Funding
Abstract
objectiveComputational modeling is an important tool for developing and optimizing implantable neural stimulation devices, but requires accurate electrical and geometrical parameter values to improve predictive value. We quantified the effects of perineurial (resistive sheath around each fascicle) and endoneurial (within each fascicle) parameter values for modeling peripheral nerve stimulation. APPROACH: We implemented 3D finite element models of compound peripheral nerves and cuff electrodes to quantify activation and block thresholds of model axons. We also implemented a 2D finite element model of a bundle of axons to estimate the bulk transverse endoneurial resistivity; we compared numerical estimates to an analytical solution. MAIN
resultsSince the perineurium is highly resistive, potentials were approximately constant over the cross section of a fascicle, and the perineurium resistivity, longitudinal endoneurial resistivity, and fascicle diameter had important effects on thresholds. Activation thresholds increased up to ~130% for higher perineurium resistivity (~400 versus 2200 Ω m) and by ~35%-250% for lower longitudinal endoneurial resistivity (3.5 versus 0.75 Ω m), with larger increases for smaller diameter axons and for axons in larger fascicles. Further, thresholds increased by ~30%-180% for larger fascicle radii, yielding a larger increase with higher perineurium resistivity. Thresholds were largely insensitive to the transverse endoneurial resistivity, but estimates of the bulk resistivity increased with extracellular resistivity and axonal area fraction; the numerical and analytical estimates were in strong agreement except at high axonal area fractions, where structured axon placements that achieved tighter packing produced electric field inhomogeneities. SIGNIFICANCE: We performed a systematic investigation of the effects of values and methods for modeling the perineurium and endoneurium on thresholds for neural stimulation and block. These results provide guidance for future modeling studies, including parameter selection, data interpretation, and comparison to experimental results.
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