Current approaches to model extracellular electrical neural microstimulation
Open accessAbstract
Nowadays, high-density microelectrode arrays provide unprecedented possibilities to precisely activate spatially well-controlled central nervous system (CNS) areas. However, this requires optimizing stimulating devices, which in turn requires a good understanding of the effects of microstimulation on cells and tissues. In this context, modeling approaches provide flexible ways to predict the outcome of electrical stimulation in terms of CNS activation. In this paper, we present state-of-the-art modeling methods with sufficient details to allow the reader to rapidly build numerical models of neuronal extracellular microstimulation. These include (1) the computation of the electrical potential field created by the stimulation in the tissue, and (2) the response of a target neuron to this field. Two main approaches are described: First we describe the classical hybrid approach that combines the finite element modeling of the potential field with the calculation of the neuron's response in a cable equation framework (compartmentalized neuron models). Then, we present a "whole finite element" approach allowing the simultaneous calculation of the extracellular and intracellular potentials, by representing the neuronal membrane with a thin-film approximation. This approach was previously introduced in the frame of neural recording, but has never been implemented to determine the effect of extracellular stimulation on the neural response at a sub-compartment level. Here, we show on an example that the latter modeling scheme can reveal important sub-compartment behavior of the neural membrane that cannot be resolved using the hybrid approach. The goal of this paper is also to describe in detail the practical implementation of these methods to allow the reader to easily build new models using standard software packages. These modeling paradigms, depending on the situation, should help build more efficient high-density neural prostheses for CNS rehabilitation.
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The ground plane configuration provides focalisation of the currents.
“A second option is the ground plane configuration, where a highly conductive local ground plane provides focalisation of the currents [28, 29].”
From Three-dimensional multilayer concentric bipolar electrodes restrict spatial activation in optic nerve stimulation (2022) · cites this paper as [29]
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Hodgkin, A. L., & Huxley, A. F. (1952) · The Journal of Physiology · doi:10.1113/jphysiol.1952.sp004764 · Cited by 23,191 · see citing works
The NEURON Simulation Environment
Hines, M. L., & Carnevale, N. T. (1997) · Neural Computation · doi:10.1162/neco.1997.9.6.1179 · Cited by 2,630 · see citing works
Long-term suppression of tremor by chronic stimulation of the ventral intermediate thalamic nucleus
Benabid, A. L., Pollak, P., Hoffmann, D., Gervason, C., Hommel, M., Perret, J. E., de Rougemont, J., & Gao, D. M. (1991) · The Lancet · doi:10.1016/0140-6736(91)91175-t · Cited by 1,787 · see citing works
Geddes, L. A., & Baker, L. E. (1967) · Medical & Biological Engineering & Computing · doi:10.1007/bf02474537 · Cited by 1,612 · see citing works
Carnevale, N. T., & Hines, M. L. (2006) · Cambridge University Press eBooks · doi:10.1017/cbo9780511541612 · Cited by 1,199 · see citing works
Perlmutter, J. S., & Mink, J. W. (2006) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.112824 · Cited by 1,073 · see citing works
Carnevale, N. T., & Hines, M. L. (2006) · Cited by 885 · see citing works
Analysis of a Model for Excitation of Myelinated Nerve
McNeal, D. R. (1976) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1976.324593 · Cited by 833 · see citing works
The Book of GENESIS: Exploring Realistic Neural Models with the GEneral NEural SImulation System
Bower, J. M., & Beeman, D. (1994) · Medical Entomology and Zoology · Cited by 750 · 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
Hodgkin, A. L., & Huxley, A. F. (1990) · Bulletin of Mathematical Biology · doi:10.1016/s0092-8240(05)80004-7 · Cited by 646 · see citing works
Bower, J. M., & Beeman, D. (1998) · Springer eBooks · doi:10.1007/978-1-4612-1634-6 · Cited by 518 · see citing works
Analysis of models for extracellular fiber stimulation
Rattay, F. (1989) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.32099 · Cited by 421 · see citing works
Plonsey, R. (1999) · Wiley Encyclopedia of Electrical and Electronics Engineering · doi:10.1002/047134608x.w1403 · Cited by 336 · see citing works
Modeling the effects of electric fields on nerve fibers: Determination of excitation thresholds
Warman, E., Grill, W. M., & Durand, D. M. (1992) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.184700 · Cited by 328 · see citing works
Role of electrode design on the volume of tissue activated during deep brain stimulation
Butson, C. R., & McIntyre, C. C. (2005) · Journal of Neural Engineering · doi:10.1088/1741-2560/3/1/001 · Cited by 312 · see citing works
Miocinovic, S., Parent, M., Butson, C. R., Hahn, P. J., Russo, G. S., Vitek, J. L., & McIntyre, C. C. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00305.2006 · Cited by 304 · see citing works
Selective Microstimulation of Central Nervous System Neurons
McIntyre, C. C., & Grill, W. M. (2000) · Annals of Biomedical Engineering · doi:10.1114/1.262 · Cited by 259 · see citing works
Specific impedance of rabbit cerebral cortex
Ranck, J. B. (1963) · Experimental Neurology · doi:10.1016/s0014-4886(63)80005-9 · Cited by 256 · see citing works
Bossetti, C. A., Birdno, M. J., & Grill, W. M. (2007) · Journal of Neural Engineering · doi:10.1088/1741-2560/5/1/005 · Cited by 237 · see citing works
Excitation of dorsal root fibers in spinal cord stimulation: a theoretical study
Struijk, J. J., Holsheimer, J., & Boom, H. B. K. (1993) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.237693 · Cited by 204 · see citing works
Deep brain stimulation mechanisms: beyond the concept of local functional inhibition
Deniau, J., Degos, B., Bosch‐Bouju, C., & Maurice, N. (2010) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2010.07413.x · Cited by 203 · see citing works
The specific impedance of the dorsal columns of cat: An anisotropic medium
Ranck, J. B., & BeMent, S. L. (1965) · Experimental Neurology · doi:10.1016/0014-4886(65)90059-2 · Cited by 191 · see citing works
A computational model of electrical stimulation of the retinal ganglion cell
Greenberg, R. J., Velte, T. J., Humayun, M. S., Scarlatis, G. N., & de Juan, E. (1999) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.759051 · Cited by 185 · see citing works
Recruitment of dorsal column fibers in spinal cord stimulation: influence of collateral branching
Struijk, J. J., Holsheimer, J., van der Heide, G. G., & Boom, H. B. K. (1992) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.256423 · Cited by 153 · see citing works
A multiple electrode cochlear implant
Clark, G. M., Tong, Y. C., Black, R. C., Forster, I. C., Patrick, J. F., & DEWHURST, D. J. (1977) · The Journal of Laryngology & Otology · doi:10.1017/s0022215100084607 · Cited by 149 · see citing works
Optimum electrode geometry for spinal cord stimulation: The narrow bipole and tripole
Holsheimer, J., & Wesselink, W. A. (1997) · Medical & Biological Engineering & Computing · doi:10.1007/bf02525529 · Cited by 125 · see citing works
Electrical stimulation of cardiac tissue: a bidomain model with active membrane properties
Roth, B. J., & Wikswo, J. P. (1994) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.284941 · Cited by 112 · see citing works
Joucla, S., & Yvert, B. (2011) · Journal of Physiology-Paris · doi:10.1016/j.jphysparis.2011.10.003 · Cited by 88 · see citing works
Self-citationShah, S. A., & Schiff, N. D. (2010) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2010.07420.x · Cited by 71 · see citing works
Effective Electrode Configuration for Selective Stimulation With Inner Eye Prostheses
Rattay, F., & Resatz, S. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.828044 · Cited by 70 · see citing works
Axon termination conditions for electrical stimulation
Rubinstein, J. T. (1993) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.237695 · Cited by 69 · see citing works
Wongsarnpigoon, A., & Grill, W. M. (2011) · Clinical Neurophysiology · doi:10.1016/j.clinph.2011.06.005 · Cited by 69 · see citing works
Improved focalization of electrical microstimulation using microelectrode arrays: a modeling study
Joucla, S., & Yvert, B. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004828 · Cited by 68 · see citing works
Self-citationAnalysis of current density and related parameters in spinal cord stimulation
Wesselink, W. A., Holsheimer, J., & Boom, H. B. K. (1998) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.681186 · Cited by 64 · see citing works
Ying, W., & Henriquez, C. S. (2007) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2006.889172 · Cited by 63 · see citing works
Grant, P. F., & Lowery, M. M. (2010) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2010.2055054 · Cited by 59 · see citing works
Point source nerve bundle stimulation: effects of fiber diameter and depth on simulated excitation
Altman, K. W., & Plonsey, R. (1990) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.55679 · Cited by 58 · see citing works
Rubinstein, J. T. (1991) · Biophysical Journal · doi:10.1016/s0006-3495(91)82084-7 · Cited by 57 · see citing works
Joucla, S., & Yvert, B. (2009) · Biophysical Journal · doi:10.1016/j.bpj.2008.12.3961 · Cited by 53 · see citing works
Self-citationMoulin, C., Glière, A., Barbier, D., Joucla, S., Yvert, B., Mailley, P., & Guillemaud, R. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2007.903522 · Cited by 52 · see citing works
Self-citationA bidomain model of epiretinal stimulation
Dokos, S., Suaning, G. J., & Lovell, N. H. (2005) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2005.847390 · Cited by 49 · see citing works
Electric field distribution in a finite-volume head model of deep brain stimulation
Grant, P. F., & Lowery, M. M. (2009) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2009.07.006 · Cited by 43 · see citing works
Evaluation of the cable model for electrical stimulation of unmyelinated nerve fibers
Schnabel, V., & Struijk, J. J. (2001) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.942593 · Cited by 37 · see citing works
A Novel Electrode Array for Diameter-Dependent Control of Axonal Excitability: A Simulation Study
Lertmanorat, Z., & Durand, D. M. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.827347 · Cited by 30 · see citing works
Bourbeau, D. J., Hokanson, J., Rubin, J. E., & Weber, D. J. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/5/056009 · Cited by 23 · see citing works
Thresholds for Transverse Stimulation: Fiber Bundles in a Uniform Field
Pourtaheri, N., Ying, W., Kim, J., & Henriquez, C. S. (2009) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2009.2033424 · Cited by 19 · see citing works
Joucla, S., Branchereau, P., Cattaert, D., & Yvert, B. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041324 · Cited by 19 · see citing works
Self-citationElectric field stimulation of excitable tissue
Plonsey, R., & Burr, R. C. (1998) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/51.715497 · Cited by 18 · see citing works
Asymptotic model of electrical stimulation of nerve fibers
Cranford, J. P., Kim, B., & Neu, W. K. (2012) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-012-0870-3 · Cited by 14 · see citing works
Dipole Distance for Minimum Threshold Current to Stimulate Unmyelinated Axons With Microelectrodes
Rattay, F., & Resatz, S. (2006) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2006.883730 · Cited by 12 · see citing works
Spinal Cord Stimulation for the Relief of Chronic Pain
Christopher, J., & Winfree (2005) · Current Surgery · doi:10.1016/j.cursur.2004.12.013 · Cited by 8 · see citing works
Focalizing electrical neural stimulation with penetrating microelectrode arrays: A modeling study
Joucla, S., Rousseau, L., & Yvert, B. (2012) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.05.006 · Cited by 8 · see citing works
Self-citationBellinger, S., Rho, J. M., & Steinmetz, P. N. (2010) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2010.03.003 · Cited by 3 · see citing works
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Research works printed but not linked: 1
- McIntyre C. C. Grill W. M. (2002). Extracellular stimulation of central neurons: influence of stimulus waveform and frequency on neuronal output. J. Neurophysiol. 88, 1592– 1604 10.1152/jn.00147.2002 12364490 · DOI
Cited by
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Tutorial: a computational framework for the design and optimization of peripheral neural interfaces
Romeni, S., Valle, G., Mazzoni, A., & Micera, S. (2020) · Nature Protocols · doi:10.1038/s41596-020-0377-6 · Cited by 76 · see citing works
Dynamic construction of a durable epitaxial catalytic layer for industrial alkaline water splitting
Chang, B., Liu, X., Zuo, S., Ren, Y., He, J., Wang, D., Lei, Y., Hu, M., Li, W., Khan, M. A., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63361-x · Cited by 85 · see citing works
Coupling Magnetically Induced Electric Fields to Neurons: Longitudinal and Transverse Activation
Wang, B., Grill, W. M., & Peterchev, A. V. (2018) · Biophysical Journal · doi:10.1016/j.bpj.2018.06.004 · Cited by 69 · see citing works
Implantable Direct Current Neural Modulation: Theory, Feasibility, and Efficacy
Aplin, F. P., & Fridman, G. Y. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00379 · Cited by 65 · see citing works
Modeling Current Sources for Neural Stimulation in COMSOL
Pelot, N. A., Thio, B. J., & Grill, W. M. (2018) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2018.00040 · Cited by 65 · see citing works
Ye, H., Hendee, J., Ruan, J., Zhirova, A., Ye, J., & Dima, M. (2022) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-022-01094-4 · Cited by 44 · see citing works
Wang, B., Aberra, A. S., Grill, W. M., & Peterchev, A. V. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa8b7c · Cited by 44 · see citing works
Quasistatic approximation in neuromodulation
Wang, B., Peterchev, A. V., Gaugain, G., Ilmoniemi, R. J., Grill, W. M., Bikson, M., & Nikolayev, D. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad625e · Cited by 35 · see citing works
A finite element method framework to model extracellular neural stimulation
Fellner, A., Heshmat, A., Werginz, P., & Rattay, F. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac6060 · Cited by 32 · see citing works
Hamish Meffin, A., Tahayori, B., Sergeev, E. N., Mareels, I., Grayden, D. B., & Burkitt, A. N. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/6/065004 · Cited by 31 · see citing works
Couto, J., & Grill, W. M. (2016) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2016.00022 · Cited by 28 · 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
ELFENN: A Generalized Platform for Modeling Ephaptic Coupling in Spiking Neuron Models
Shifman, A. R., & Lewis, J. E. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00035 · Cited by 24 · see citing works
Numerical characterization of intraoperative and chronic electrodes in deep brain stimulation
Paffi, A., Camera, F., Apollonio, F., dâ€TMInzeo, G., & Liberti, M. (2015) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2015.00002 · Cited by 24 · see citing works
Deep learning of material transport in complex neurite networks
Li, A., Farimani, A. B., & Zhang, Y. J. (2021) · Scientific Reports · doi:10.1038/s41598-021-90724-3 · Cited by 23 · see citing works
Design of Transcutaneous Stimulation Electrodes for Wearable Neuroprostheses
RaviChandran, N., Teo, M. Y., Aw, K. C., & McDaid, A. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.2994900 · Cited by 20 · see citing works
Toward Closed-Loop Electrical Stimulation of Neuronal Systems: A Review
Tanskanen, J. M. A., Ahtiainen, A., & Hyttinen, J. (2020) · Bioelectricity · doi:10.1089/bioe.2020.0028 · Cited by 19 · see citing works
Somatic inhibition by microscopic magnetic stimulation
Ye, H., & Barrett, L. (2021) · Scientific Reports · doi:10.1038/s41598-021-93114-x · Cited by 17 · see citing works
Cellular mechanisms underlying carry-over effects after magnetic stimulation
Ye, H., Dima, M., Hall, V., & Hendee, J. (2024) · Scientific Reports · doi:10.1038/s41598-024-55915-8 · Cited by 17 · see citing works
Axonal blockage with microscopic magnetic stimulation
Skach, J., Conway, C. M., Barrett, L., & Ye, H. (2020) · Scientific Reports · doi:10.1038/s41598-020-74891-3 · Cited by 16 · see citing works
Scalable Three-Dimensional Recording Electrodes for Probing Biological Tissues
Lee, J. M., Lin, D., Hong, G., Kim, K., Park, H., & Lieber, C. M. (2022) · Nano Letters · doi:10.1021/acs.nanolett.2c01444 · Cited by 15 · see citing works
Cellular mechanisms underlying state-dependent neural inhibition with magnetic stimulation
Ye, H., Chen, V., & Hendee, J. (2022) · Scientific Reports · doi:10.1038/s41598-022-16494-8 · Cited by 13 · see citing works
Bestel, R., Appali, R., van Rienen, U., & Thielemann, C. (2017) · Neural Computation · doi:10.1162/neco_a_01019 · Cited by 13 · see citing works
Bestel, R., van Rienen, U., Thielemann, C., & Appali, R. (2020) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2020.3026635 · Cited by 13 · see citing works
Borda, E., Gaillet, V., Airaghi Leccardi, M. J. I., Zollinger, E. G., Moreira, R. C., & Ghezzi, D. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac6d7e · Cited by 11 · see citing works
Czerwonky, D. M., Aberra, A. S., & Gomez, L. J. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad5704 · Cited by 11 · see citing works
Modeling the Impact of the Variation in Peripheral Nerve Anatomy on Stimulation
Mishra, L. N., Kulkarni, G., & Gadgil, M. (2022) · Journal of Pain Research · doi:10.2147/jpr.s380546 · Cited by 8 · see citing works
Agotici, S., Masani, K., & Yoo, P. B. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3133508 · Cited by 8 · see citing works
de Miguel, Á. R., Escobar, J. M., Greiner, D., Benítez, D., Rodríguez, E., Oliver, A., Hernández-Gil, M., & Macías, Á. R. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010134 · Cited by 7 · see citing works
Verardo, C., Mele, L. J., Selmi, L., & Palestri, P. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad2581 · Cited by 7 · see citing works
Henríquez, F., & Jerez-Hanckes, C. (2018) · ESAIM Mathematical Modelling and Numerical Analysis · doi:10.1051/m2an/2018019 · Cited by 7 · see citing works
Finding the Location of Axonal Activation by a Miniature Magnetic Coil
Ye, H. (2022) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2022.932615 · Cited by 7 · see citing works
Improving focality and consistency in micromagnetic stimulation
Ye, H., Hall, V., & Hendee, J. (2023) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2023.1105505 · Cited by 7 · see citing works
Minimum energy control for a two-compartment neuron to extracellular electric fields
Yi, G., Wang, J., Li, H., Wei, X., & Deng, B. (2016) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2016.03.017 · Cited by 7 · see citing works
González‐Losada, P., Rousseau, L., Grzeskowiak, M., Valet, M., Nguyen, D., Dégardin, J., Dubus, É., Picaud, S. A., & Lissorgues, G. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00885 · Cited by 7 · see citing works
Analytical solution for time-dependent potentials in a fiber stimulated by an external electrode
Neu, W. K. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-016-1459-z · Cited by 6 · see citing works
Makaroff, S. N., Nummenmaa, A. R., Noetscher, G. M., Qi, Z., McIntyre, C. C., & Bingham, C. S. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/ace5de · Cited by 5 · see citing works
Estimations of Charge Deposition Onto Convoluted Axon Surfaces Within Extracellular Electric Fields
Noetscher, G. M., Tang, D., Nummenmaa, A. R., Bingham, C. S., McIntyre, C. C., & Makaroff, S. N. (2023) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2023.3299734 · Cited by 5 · see citing works
Extracellular single neuron stimulation with high-density multi-electrode array
Buccino, A. P., Stöber, T. M., Solveig, N., Cauwenberghs, G., & Hafliger, P. D. (2016) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2016.7833846 · Cited by 5 · see citing works
A multiobjective optimization procedure for the electrode design of cochlear implants
de Miguel, Á. R., Escobar, J. M., Greiner, D., & Macías, Á. R. (2018) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.2992 · Cited by 5 · see citing works
Physics and biophysics fundamentals of transcranial stimulation
Wang, B., Aberra, A. S., Grill, W. M., & Peterchev, A. V. (2021) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780198832256.013.1 · Cited by 5 · see citing works
Reduced order models of myelinated axonal compartments
Ioan, D., Bărbulescu, R., Silveira, L. M., & Ciuprina, G. (2019) · Journal of Computational Neuroscience · doi:10.1007/s10827-019-00726-4 · Cited by 5 · see citing works
A Treatise of the Physical Aspects of Phosphenes and Single-Cell Selectivity in Retinal Stimulation
Villarreal, D. L., & Krautschneider, W. H. (2017) · International Journal of Computational & Neural Engineering · doi:10.19070/2572-7389-170008 · Cited by 5 · see citing works
Computational modeling to improve treatments for essential tremor
Lee, S., Asaad, W. F., & Jones, S. R. (2016) · Drug Discovery Today Disease Models · doi:10.1016/j.ddmod.2017.04.002 · Cited by 4 · see citing works
Analysis of upper threshold mechanisms of spherical neurons during extracellular stimulation
Fellner, A., Stiennon, I., & Rattay, F. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00700.2018 · Cited by 3 · see citing works
A new method of brain stimulation at ultra-high frequencyPreprint
Jamali, Y., Jamali, M. V., & Golshani, M. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/621771 · Cited by 3 · see citing works
Sabino, V., Murugesan, A., Hasan, N. I., Vaezi, S. S., Walenciak, A. J., Jayatissa, P., & Gomez, L. J. (2026) · IEEE Antennas and Propagation Magazine · doi:10.1109/map.2026.3655613 · Cited by 2 · see citing works
The 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 · see citing works
A varying‐radius cable equation for the modelling of impulse propagation in excitable fibres
Alqahtani, A., Abed, A. A., Alharbi, Y., Bakouri, M., Lovell, N. H., & Dokos, S. (2022) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.3616 · Cited by 2 · see citing works
Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
Pratiwi, A. M., Kékesi, O., & Suaning, G. J. (2022) · Journal of Visualized Experiments · doi:10.3791/63792 · Cited by 2 · see citing works
Kuznetsov, A. V. (2025) · International Journal of Heat and Mass Transfer · doi:10.1016/j.ijheatmasstransfer.2025.126790 · Cited by 2 · see citing works
Neural Signal Blocking Based on Spike Trapping Principle: Effect of Electrode and Pulse Parameters
Zhang, J., Feng, Y., Lü, X., & Wang, Z. (2020) · IEEE Access · doi:10.1109/access.2020.2983991 · Cited by 2 · see citing works
Biomimetic Stimulating Array for Single Localized Stimulation in Visual Prosthesis
Villarreal, D. L., & Schroeder, D. (2017) · International Journal of Computational & Neural Engineering · doi:10.19070/2572-7389-1700010 · Cited by 2 · see citing works
Spatial Visual Perceptions by Means of Simulated Prosthetic Vision
Villarreal, D. L., & Krautschneider, W. H. (2019) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-030-30648-9_100 · Cited by 2 · see citing works
On the use of time division multiplexing to improve electrical brain stimulation focality
Abouelseoud, G., Abouelseoud, Y., Shoukry, A., Ismail, N. E., & Mekky, J. F. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102048 · Cited by 2 · see citing works
Implantable Direct Current Neural Modulation
Aplin, F. P., & Fridman, G. Y. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_14 · Cited by 1 · see citing works
Salkım, E. (2023) · Konya Journal of Engineering Sciences · doi:10.36306/konjes.1240153 · Cited by 1 · see citing works
Opančar, A., Głowacki, E. D., & Đerek, V. (2026) · Advanced Electronic Materials · doi:10.1002/aelm.202500867 · Cited by 1 · see citing works
Modeling Pyramidal Neurons Using Bidomain BEM and Hierarchical Matrix Approximation
Hasan, N. I., Sabino, V., Walenciak, A. J., Liu, Y., & Gomez, L. J. (2026) · IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology · doi:10.1109/jerm.2026.3693176 · Cited by 1 · see citing works
Uncertainty in 1D and 3D Models of a Fiber Stimulated by an External Electrode
Neu, W. K. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-31744-1_20 · Cited by 1 · see citing works
Restore axonal conductance in a locally demyelinated axon with electromagnetic stimulation
Ye, H., Chen, Y., Chen, J., & Hendee, J. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/adb213 · Cited by 1 · see citing works
Reduced Order Model of a Neuron-Electrode Interface Coupled to a Hodgkin-Huxley Model
Fitzer, U., Hohlfeld, D., & Bechtold, T. (2022) · Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science · doi:10.11159/icebs22.136 · Cited by 1 · see citing works
Makarov, S. N., Noetscher, G. M., & Sundaram, P. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/391060 · Cited by 1 · see citing works
A new method of brain stimulation at ultra-high frequencyPreprint
Jamali, Y., Jamali, M. V., & Golshani, M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.12456 · Cited by 1 · see citing works
Hutchings, F., Thornton, C., Zhang, C., Wang, Y., & Kaiser, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.10414 · Cited by 1 · see citing works
Measuring Neuronal Signals with Microelectrode Arrays: A Finite Element AnalysisPreprint
Bestel, R., van Rienen, U., Thielemann, C., & Appali, R. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.07.139014 · Cited by 1 · see citing works
Finite Element Modeling of Electrical Stimulation Using Microelectrodes
Joucla, S., & Yvert, B. (2013) · Encyclopedia of Computational Neuroscience · doi:10.1007/978-1-4614-7320-6_596-1
Self-citationBorda, E., Gaillet, V., Leccardi, M. J. I. A., Zollinger, E. G., Moreira, R. C., & Ghezzi, D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.21.485100
Finite Element Modeling of Electrical Stimulation Using Microelectrodes
Joucla, S., & Yvert, B. (2022) · Encyclopedia of Computational Neuroscience · doi:10.1007/978-1-0716-1006-0_596
Self-citationImplantable Direct Current Neural Modulation
Aplin, F. P., & Fridman, G. Y. (2022) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_14-1
Neuron-Electrode Interface with Hodgkin-Huxley Model in ANSYS
Fitzer, U., Hohlfeld, D., & Bechtold, T. (2023) · International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) · doi:10.1109/eurosime56861.2023.10100828
Effect of electric field direction on neuronal activity: an ex-vivo study*
Jain, V., Forssell, M., Chamanzar, M., & Grover, P. (2023) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc40787.2023.10340225
Spatially Localized Visual Perception Estimation by Means of Prosthetic Vision Simulation
Villarreal, D. L., & Krautschneider, W. H. (2024) · Journal of Imaging · doi:10.3390/jimaging10110294
Wang, R., & Fridman, G. Y. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.19.660597
Ca2+-Independent Short-Term Depression in the Hippocampal CA1 Region
Novikova, M. A., Jappy, D., Fedorov, D. A., Климанова, Е. А., Nikolaev, G. M., Korneeva, I. A., Lopina, O. D., Averina, O. A., Rozov, A. V., & Латанов, А. В. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27156908
- Authors
- Joucla, S., Glière, A., & Yvert, B.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Corresponding author
- Joucla, Sébastien
- Yvert, Blaise
- Venue
- Frontiers in Computational Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2014
- Volume
- 8
- Pages
- 13-13
- ISSN
- 1662-5188 (ISSN-L)
- PMC
- PMC3928616
- OpenAlex
- W2034891349
- Cited by
- 78
- References
- 53
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 5 · 2023: 7 · 2022: 14 · 2021: 5 · 2020: 9 · 2019: 8 · 2018: 7 · 2017: 4 · 2016: 6 · 2015: 1 · 2014: 2 · 2013: 1
- FWCI
- 1.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Computational Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- European Commission (280433)
- Agence Nationale de la Recherche (ANR-10-BLAN-0316, ANR-10)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Undergraduate Neuroscience Education and Research
- Keywords
- extracellular electrical stimulation, high-density microelectrode arrays, cable equation, neural prostheses
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