Analysis of a Model for Excitation of Myelinated Nerve
Abstract
Excellent models have been presented in the literature which relate membrane potential to transverse membrane current and which describe the propagation of action potentials along the axon, for both myelinated and nonmyelinated fibers. There is not, however, an adequate model for nerve excitation which allows one to compute the threshold of a nerve fiber for pulses of finite duration using electrodes that are not in direct contact with the fiber. This paper considers this problem and presents a model of the electrical properties of myelinated nerve which describes the time course of events following stimulus application up to the initiation of the action potential. The time-varying current and potential at all nodes can be computed from the model, and the strength-duration curve can be determined for arbitrary electrode geometries, although only the case of a monopolar electrode is considered in this paper. It is shown that even when the stimulus is a constant-current pulse, the membrane current at the nodes varies considerably with time. The strength-duration curve calculated from the model is consistent with previously published experimental data, and the model provides a quantitative relationship between threshold and fiber diameter which shows there is less selectivity among fibers of large diameter than those of small diameter.
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The theoretical basis of electrode surface and usable characteristics and testable models of electrode design have been optimized.
“The theoretical basis of electrode surface and usable characteristics and testable models of electrode design have been optimized”
From A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems (2005) · cites this paper as McNeal, 1976
Cites
The sensations produced by electrical stimulation of the visual cortex
Brindley, G. S., & Lewin, W. S. (1968) · The Journal of Physiology · doi:10.1113/jphysiol.1968.sp008519 · Cited by 1,170 · see citing works
Crago, P. E., Peckham, P. H., Mortimer, J. T., & Van Der Meulen, J. P. (1974) · Annals of Biomedical Engineering · doi:10.1007/bf02368496 · Cited by 133 · see citing works
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Electrical stimulation of excitable tissue: design of efficacious and safe protocols
Merrill, D. R., Bikson, M., & Jefferys, J. G. R. (2005) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2004.10.020 · Cited by 2,078 · see citing works
Committee report: Guidelines for human startle eyeblink electromyographic studies
Blumenthal, T. D., Cuthbert, B. N., Filion, D. L., Hackley, S., Lipp, O. V., & Van Boxtel, A. (2005) · Psychophysiology · doi:10.1111/j.1469-8986.2005.00271.x · Cited by 1,169 · see citing works
Navarro, X., Krueger, T. B., Lago, N., Micera, S., Stieglitz, T., & Dario, P. (2005) · Journal of the Peripheral Nervous System · doi:10.1111/j.1085-9489.2005.10303.x · Cited by 845 · see citing works
Analysis of Models for External Stimulation of Axons
Rattay, F. (1986) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1986.325670 · Cited by 681 · see citing works
Neuromuscular electrical stimulation in neurorehabilitation
Sheffler, L. R., & Chae, J. (2007) · Muscle & Nerve · doi:10.1002/mus.20758 · Cited by 529 · see citing works
Implanted Neural Interfaces: Biochallenges and Engineered Solutions
Grill, W. M., Norman, S. E., & Bellamkonda, R. V. (2009) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-061008-124927 · Cited by 488 · see citing works
The Effect of Stimulus Parameters on the Recruitment Characteristics of Direct Nerve Stimulation
Gorman, P. H., & Mortimer, J. T. (1983) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1983.325041 · Cited by 313 · see citing works
Selective Electrical Interfaces with the Nervous System
Rutten, W. L. C. (2002) · Annual Review of Biomedical Engineering · doi:10.1146/annurev.bioeng.4.020702.153427 · Cited by 276 · see citing works
Selective activation of small motor axons by quasitrapezoidal current pulses
Fang, Z.-P., & Mortimer, J. T. (1991) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.76383 · Cited by 222 · see citing works
The effect of stimulus pulse duration on selectivity of neural stimulation
Grill, W. M., & Mortimer, J. T. (1996) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.481985 · Cited by 215 · see citing works
Greiner, N., Barra, B., Schiavone, G., Lorach, H., James, N., Conti, S., Kaeser, M., Fallegger, F., Borgognon, S., Lacour, S., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20703-1 · Cited by 199 · see citing works
Energy-efficient waveform shapes for neural stimulation revealed with a genetic algorithm
Wongsarnpigoon, A., & Grill, W. M. (2010) · Journal of Neural Engineering · doi:10.1088/1741-2560/7/4/046009 · Cited by 166 · see citing works
Bourne, S. K., Eckhardt, C. A., Sheth, S. A., & Eskandar, E. N. (2012) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2012.00029 · Cited by 146 · see citing works
Inversion of the current-distance relationship by transient depolarization
Grill, W. M., & Mortimer, J. T. (1997) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.553708 · Cited by 109 · see citing works
Efficiency Analysis of Waveform Shape for Electrical Excitation of Nerve Fibers
Wongsarnpigoon, A., Woock, J. P., & Grill, W. M. (2010) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2010.2047610 · Cited by 104 · see citing works
Tractography-activation models applied to subcallosal cingulate deep brain stimulation
Lujan, J. L., Chaturvedi, A., Choi, K. S., Holtzheimer, P. E., Gross, R. E., Mayberg, H. S., & McIntyre, C. C. (2013) · Brain stimulation · doi:10.1016/j.brs.2013.03.008 · Cited by 101 · see citing works
A modeling study of nerve fascicle stimulation
Veltink, P. H., van Veen, B. K., Struijk, J. J., Holsheimer, J., & Boom, H. B. K. (1989) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.32100 · Cited by 95 · see citing works
Current approaches to model extracellular electrical neural microstimulation
Joucla, S., Glière, A., & Yvert, B. (2014) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2014.00013 · Cited by 78 · see citing works
Microchannels as Axonal Amplifiers
FitzGerald, J. J., Lacour, S. P., McMahon, S. B., & Fawcett, J. W. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2007.909533 · Cited by 76 · see citing works
Neural Interface Devices: Spinal Cord Stimulation Technology
North, R. B. (2008) · Proceedings of the IEEE · doi:10.1109/jproc.2008.922558 · Cited by 59 · see citing works
Recruitment characteristics of nerve fascicles stimulated by a multigroove electrode
Koole, P., Holsheimer, J., Struijk, J. J., & Verloop, A. J. (1997) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.559348 · Cited by 56 · see citing works
Yoshida, K., Kurstjens, G. A. M., & Hennings, K. (2009) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2009.08.005 · Cited by 43 · see citing works
Multielectrode spiral cuff for ordered and reversed activation of nerve fibres
Rozman, J., Sovinec, B., Trlep, M., & Zorko, B. (1993) · Journal of Biomedical Engineering · doi:10.1016/0141-5425(93)90039-2 · Cited by 41 · see citing works
Effects of frequency-dependent membrane capacitance on neural excitability
Howell, B., Medina, L. E., & Grill, W. M. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/5/056015 · Cited by 39 · see citing works
Tahayori, B., Meffin, H., Sergeev, E. N., Mareels, I. M. Y., Burkitt, A. N., & Grayden, D. B. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/6/065005 · Cited by 24 · see citing works
A machine learning framework to optimize optic nerve electrical stimulation for vision restoration
Romeni, S., Zoccolan, D., & Micera, S. (2021) · Patterns · doi:10.1016/j.patter.2021.100286 · Cited by 17 · see citing works
- Authors
- McNeal, D. R.
- Affiliations
- University of Southern California (US)
- Corresponding author
- McNeal, Donald R.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 1976-07
- Volume
- BME-23
- Issue
- 4
- Pages
- 329-337
- ISSN
- 0018-9294 (ISSN-L)
- OpenAlex
- W2087129686
- Cited by
- 833
- References
- 2
- Citations by year
- 2026: 17 · 2025: 31 · 2024: 25 · 2023: 23 · 2022: 25 · 2021: 46 · 2020: 17 · 2019: 25 · 2018: 34 · 2017: 23 · 2016: 26 · 2015: 25 · 2014: 27 · 2013: 32 · 2012: 27
- FWCI
- 0.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ion channel regulation and function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- myelinated axons, nerve excitation, action potential generation, strength-duration curve, threshold, monopolar electrodes, nodes of Ranvier, membrane currents, fiber diameter
- MeSH terms
- Electric Stimulation, Humans, Membrane Potentials, Models, Biological, Nerve Fibers, Myelinated
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