ArticleArtificial organs2023
Characterization of the electrical properties of mammalian peripheral nerve laminae.
Article in Artificial organs, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 12 citations in OpenAlex.
- Optimizing Transcutaneous Electrical Stimulation Based on Frequency-Dependent Tissue Modeling and Signal Analysis.Bioengineering (Basel, Switzerland) · 2026Article
- Impedance changes in chronic vagus nerve stimulator implantation in epileptic dogs.Veterinary research communications · 2026Article
- Carbon Nanodot-enabled Fluorescent Nerve Conduits for Peripheral Nerve Repair: A Systematic Review of Translational Readiness.Plastic and reconstructive surgery. Global open · 2026Article
- Experimental Analysis and Modeling Study of Impedance Changes in Decellularized and Recellularized Peripheral Nerves.Bioengineering (Basel, Switzerland) · 2026Article
- Subthreshold Effects of Low-Frequency Alternating Current on Nerve Conduction Delay.Biomedicines · 2025Article
- Fascicle-selective kilohertz-frequency neural conduction block with longitudinal intrafascicular electrodes.Journal of neural engineering · 2025Article
- Computational modeling of autonomic nerve stimulation: Vagus et al.Current opinion in biomedical engineering · 2024Article
- NRV: An open framework for in silico evaluation of peripheral nerve electrical stimulation strategies.PLoS computational biology · 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
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5 authors at 2 institutions in 1 country.
Funding
Abstract
BACKGROUND AND
objectiveThe intrinsic electrical material properties of the laminar components of the mammalian peripheral nerve bundle are important parameters necessary for the accurate simulation of the electrical interaction between nerve fibers and neural interfaces. Improvements in the accuracy of these parameters improve the realism of the simulation and enables realistic screening of novel devices used for extracellular recording and stimulation of mammalian peripheral nerves. This work aims to characterize these properties for mammalian peripheral nerves to build upon the resistive parameter set established by Weerasuriya et al. in 1984 for amphibian somatic peripheral nerves (frog sciatic nerve) that is currently used ubiquitously in the in-silico peripheral nerve modeling community.
methodsA custom designed characterization chamber was implemented and used to measure the radial and longitudinal impedance between 10 mHz and 50 kHz of freshly excised canine vagus nerves using four-point impedance spectroscopy. The impedance spectra were parametrically fitted to an equivalent circuit model to decompose and estimate the components of the various laminae. Histological sections of the electrically characterized nerves were then made to quantify the geometry and laminae thicknesses of the perineurium and epineurium. These measured values were then used to calculate the estimated intrinsic electrical properties, resistivity and permittivity, from the decomposed resistances and reactances. Finally, the estimated intrinsic electrical properties were used in a finite element method (FEM) model of the nerve characterization setup to evaluate the realism of the model.
resultsThe geometric measurements were as follows: nerve bundle (1.6 ± 0.6 mm), major nerve fascicle diameter (1.3 ± 0.23 mm), and perineurium thickness (13.8 ± 2.1 μm). The longitudinal resistivity of the endoneurium was estimated to be 0.97 ± 0.05 Ωm. The relative permittivity and resistivity of the perineurium were estimated to be 2018 ± 391 and 3.75 kΩm ± 981 Ωm, respectively. The relative permittivity and resistivity of the epineurium were found to be 9.4 × 10
conclusionAlthough the resistive values measured in the mammalian nerve are similar to those of the amphibian model, the relative permittivity of the laminae bring new information about the reactance and the corner frequency (frequency at peak reactance) of the peripheral nerve. The measured and estimated corner frequency are well within the range of most bioelectric signals, and are important to take into account when modeling the nerve and neural interfaces.
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