The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Fascicular Perineurium Thickness, Size, and Position Affect Model Predictions of Neural Excitation
Open accessAbstract
The number of applications using neural prosthetic interfaces is expanding. Computer models are a valuable tool to evaluate stimulation techniques and electrode designs. Although our understanding of neural anatomy has improved, its impact on the effects of neural stimulation is not well understood. This study evaluated the effects of fascicle perineurial thickness, diameter, and position on axonal excitation thresholds and population recruitment using finite element models and NEURON simulations. The perineurial thickness of human fascicles was found to be 3.0% +/- 1.0% of the fascicle diameter. Increased perineurial thickness and fascicle diameter increased activation thresholds. The presence of a large neighboring fascicle caused a significant change in activation of a smaller target fascicle by as much as 80% +/- 11% of the total axon population. Smaller fascicles were recruited at lower amplitudes than neighboring larger fascicles. These effects were further illustrated in a realistic model of a human femoral nerve surrounded by a nerve cuff electrode. The data suggest that fascicular selectivity is strongly dependent upon the anatomy of the nerve being stimulated. Therefore, accurate representations of nerve anatomy are required to develop more accurate computer models to evaluate and optimize nerve electrode designs for neural prosthesis applications.
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“Since the electrodes and the nerve fibers are separated by the perineurium, higher stimulation currents are required to achieve sensations than the case of intra-fascicular interfaces (Grinberg et al., 2008).”
From Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review. (2017) · cites this paper as Grinberg et al., 2008
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, since the contacts are separated from the nerve fibers by the perineurium, higher stimulation currents are required to achieve sensation than for intra-fascicular electrodes (Grinberg et al., 2008).”
From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Grinberg et al., 2008
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In the citing paper
“This is because the size of the perineurium is directly proportional to the size of the fascicle.”
From Directed stimulation with interfascicular interfaces for peripheral nerve stimulation (2021) · cites this paper as [51]
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“This shunting can cause the current from an extraneural source to be directed away from a larger, more resistive fascicle toward a smaller, less resistive fascicle [51].”
From Directed stimulation with interfascicular interfaces for peripheral nerve stimulation (2021) · cites this paper as [51]
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“The threshold for activation of a smaller fascicle is generally lower than a larger fascicle [51].”
From Directed stimulation with interfascicular interfaces for peripheral nerve stimulation (2021) · cites this paper as [51]
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Citations
Cites
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“The MRG model was chosen because it accurately represents mammalian axon response to electrical stimulation [36, 37].”
InfluentialFunctionally selective peripheral nerve stimulation with a flat interface nerve electrode
Tyler, D. J., & Durand, D. M. (2002) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2002.806840 · Cited by 398 · cited 1×
“Implantable nerve cuff electrodes have the ability to selectively stimulate individual fascicles or fascicular groups, resulting in selective muscle activation [2-4].”
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“Fascicular diameters of 100, 500, and 1000 m were studied, based on the reported physiologic range for mammalian peripheral nerves [23], [25], [27].”
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“histological studies suggest that a relationship exists between fascicular size and perineurial thickness [23], [28], [29].”
Schiefer, M. A., Triolo, R. J., & Tyler, D. J. (2008) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2008.918425 · Cited by 148 · cited 9×
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Human nerve stimulation thresholds and selectivity using a multi-contact nerve cuff electrode
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Research works printed but not linked: 1
- gustafson, 2005, a comparative analysis of fundamental nerve fascicular anatomy: physiological limits and implications for nerve cuff electrode design, NIH NINDS Neural Interfaces Workshop
Cited by
Sorted by citations
Items 101–145 of 145
Schiefer, M. A. (2009) · OhioLink ETD Center (Ohio Library and Information Network) · Cited by 3
The stimulus router system: A novel neural prosthesis
Gan, L. S. (2010) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3c98d · Cited by 3
Human vagus nerve fascicular anatomy: a microCT segmentation and histological studyPreprint
Thompson, N., Mastitskaya, S., Iacoviello, F., Shearing, P. R., Aristovich, K. Y., & Holder, D. S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.04.547643 · Cited by 3
“Given that humans have three to five times less fascicles, that are larger, than pig vagus nerves their fibers are expected to have higher activation thresholds (37,38).”
BackgroundThe optimization of neuroprosthetic interfaces relying on biophysical and surrogate digital twins
Verardo, C., Fossati, V., Toni, L., Pierantoni, L., Losanno, E., Agnesi, F., & Romeni, S. (2026) · npj Biomedical Innovations. · doi:10.1038/s44385-026-00076-8 · Cited by 4
Somatosensory Neuromodulation with a Focus Towards Clinical Systems
Graczyk, E. L., & Tyler, D. J. (2022) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_92-1 · Cited by 2
Modeling Peripheral Nerve Stimulation
Dali, M., & Guiraud, D. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_61 · Cited by 2
Bailey, Z., Nairac, Z., Cuttaz, E. A., M’Rad, I. B., Chapman, C. A. R., Rapeaux, A., Goding, J. A., Roche, A. D., Constandinou, T. G., & Green, R. A. (2026) · Journal of Neural Engineering · doi:10.1088/1741-2552/ae44d0 · Cited by 2
“There are many studies focused on the importance of modeling the perineurium accurately in peripheral nerve simulation experiments [35, 44, 45].”
Modeling Peripheral Nerve Stimulation
Dali, M., & Guiraud, D. (2021) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_61-1 · Cited by 2
VENTRAL ROOT OR DORSAL ROOT GANGLION MICROSTIMULATION TO EVOKE HINDLIMB MOTOR RESPONSES
Bourbeau, D. J. (2011) · D-Scholarship@Pitt (University of Pittsburgh) · Cited by 2
Ahmed, M., & Huntoon, M. A. (2018) · Elsevier eBooks · doi:10.1016/b978-0-323-40196-8.00074-7 · Cited by 2
Simulation insights on the compound action potential in multifascicular nerves
Tharayil, J., Zinno, C., Agnesi, F., Lloyd, B., Farcito, S., Cassara, A. M., Kuster, N., Reimann, M., Micera, S., & Neufeld, E. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013452 · Cited by 1
“Thin resistive layer settings were assigned to patches at the interfaces between fascicles and the interfascicular tissue with a thickness computed as 3 % of the fascicle’s equivalent diameter [42].”
Electrical anisotropy of fascicles in a realistic neck model for phrenic nerve stimulation
Wegert, L., Ziółkowski, M., Hunold, A., Lange, I., Kalla, T., & Haueisen, J. (2025) · COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering · doi:10.1108/compel-12-2024-0528 · Cited by 1
Perrault, J. L., Kozma, K. D., Zeng, W., Nkana, Z. H., Albano, N. J., Gunderson, K. A., Hurley, S. A., Lake, W. B., Williams, J. C., Poore, S. O., et al. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/ae1dae · Cited by 1
“Additionally, increasing fascicle size increases activation thresholds (Grinberg et al 2008, Davis et al 2023) due to the increased resistivity from correlated perineurial thicknesses.”
InfluentialLi, M., Ly, C. M., Wen, J., Rustogi, P., & Meng, E. F. (2026) · Bioelectronic Medicine · doi:10.1186/s42234-025-00199-0 · Cited by 1
“C-type C-type nerve fibers act as high-intensity nociceptors and affer-ents (Grinberg et al. 2008) and have been shown to play a significant role in regulating physiological functions such as glycemic control (Waataja et al. 2022), pain transduction (Rydevik et al. 1990) and interoception…”
Overstreet, C. K. (2013) · Cited by 1
Peters, K. M., Nguyen, L. N., & Sirls, L. T., II (2018) · Springer eBooks · doi:10.1007/978-3-319-73266-4_13 · Cited by 1
Tang, C.-W., Ju, M., & Lin, C. K. (2020) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2020.109974 · Cited by 1
Somatosensory Neuromodulation with a Focus Towards Clinical Systems
Graczyk, E. L., & Tyler, D. J. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_92 · Cited by 1
On the Relationship Between Fascicle Diameter and Perineurium Thickness in the Ulnar Nerve of Pigs
Andreis, F. R., Metcalfe, B., Janjua, T. A. M., Fazan, V. P. S., Jensen, W., Meijs, S., & Nielsen, T. N. (2023) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner52421.2023.10123782 · Cited by 2
“Several studies have demonstrated the impact of different neural structures on the activation patterns of peripheral nerve fibres [7], [20], resulting in modelling platforms that allow the control of several nerve parameters, with the main goal of improving the predictive values of computational models.”
BackgroundRamped kilohertz-frequency signals produce nerve conduction block without onset response
Peña, E., Pelot, N. A., & Grill, W. M. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/add20e · Cited by 1
TSENG, G.-H., Chang, C., Lin, C. K., Chen, T. Y.-F., & Ju, M. (2019) · Journal of Mechanics in Medicine and Biology · doi:10.1142/s0219519419500222 · Cited by 1
Qureshi, M. M., Allam, N., Peters, T., Demidov, V. V., & Vitkin, I. A. (2022) · Journal of Biomedical Optics · doi:10.1117/1.jbo.27.10.100501 · Cited by 1
“Fishing line was selected as a low-scattering object to represent peripheral nerves because it has a low-scattering coefficient, being highly transparent due to its homogeneous composition.(24) Thus, fishing line models optical properties of nerves well.”
BackgroundKatic, N., Valle, G., & Raspopović, S. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_100 · Cited by 1
Principles of Computational Neuroscience
Venugopal, S., Crook, S. M., Srivatsan, M., & Jung, R. (2011) · doi:10.1002/9783527639366.ch2 · Cited by 1
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Stimulation of the Peripheral Nerve and Peripheral Nerve Field
Pope, J. E., Deer, T. R., Grigsby, E. J., & Kim, P. S. (2012) · Springer eBooks · doi:10.1007/978-1-4614-1560-2_57
“The aforementioned nerve layers and inconsistent fascicular topographic arrangement provide an anatomic explanation not only for the impendence to overcome but also the cumulative effect of cathodal stimulation employed in peripheral neuromodulation [ 14 ] .”
BackgroundHokanson, J. (2014) · D-Scholarship@Pitt (University of Pittsburgh)
A Validated Peripheral Nerve Model for the Simulation of Multicontact Nerve Cuff Recordings
Garai, P. (2016) · TSpace (University of Toronto)
Neuroprostheses for Restoring Sensation
Tyler, D. J. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-805353-9.00103-0
Automatic Segmentation and Three-dimensional Reconstruction of Fascicles in Peripheral Nerves
Tovbis, D. (2019) · TSpace (University of Toronto)
Peripheral nervous system control for neuroprostheses
Buil, J. (2017) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-6491
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Ultrasound-Guided Peripheral Nerve Stimulation
Huntoon, M. A. (2018) · Springer eBooks · doi:10.1007/978-1-4939-7754-3_33
Qureshi, M. M., Peters, T., Allam, N., Demidov, V. V., & Vitkin, I. A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.09.491225
Bionic limb replacement: an evolving concept in lower extremity reconstruction
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BackgroundBartmeyer, P. M., Biscola, N. P., & Havton, L. A. (2024) · eNeuro · doi:10.1523/eneuro.0009-23.2024
“The likelihood of individual nerve fi ber activation by electrical stimulation is in fl uenced by, for instance, nerve fascicular size and organization, perineurium thickness, and distance from the stimulating electrode (Grinberg et al., 2008; Zellmer et al., 2018; Musselman et al., 2021).”
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Metadata
- Authors
- Grinberg, Y., Schiefer, M. A., Tyler, D. J., & Gustafson, K. J.
- Affiliations
- Case Western Reserve University (US)
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2008-12
- Volume
- 16
- Issue
- 6
- Pages
- 572-581
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- PMC
- PMC2918421
- OpenAlex
- W2097925212
- Cited by
- 145
- References
- 38
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 7 · 2023: 17 · 2022: 15 · 2021: 10 · 2020: 12 · 2019: 8 · 2018: 13 · 2017: 5 · 2016: 7 · 2015: 8 · 2014: 2 · 2013: 4 · 2012: 6
- FWCI
- 1.88
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- IEEE Transactions on Neural Systems and Rehabilitation Engineering (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- OhioLink ETD Center (Ohio Library and Information Network) (submittedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (DK 077089, R01DK077089)
- National Institute of Biomedical Imaging and Bioengineering (EB-001889, R01EB001889)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Life Sciences › Neuroscience › Neurology › Vagus Nerve Stimulation Research
- Keywords
- peripheral nerve stimulation, cuff electrodes, femoral nerve, finite element analysis, neural simulation, nerve anatomy
- MeSH terms
- Action Potentials, Animals, Computer Simulation, Differential Threshold, Electric Stimulation, Electrodes, Implanted, Electric Stimulation Therapy, Femoral Nerve, Humans, Models, Neurological, Peripheral Nerves
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