Fibre-selective recording from the peripheral nerves of frogs using a multi-electrode cuff
Open accessAbstract
OBJECTIVE: We investigate the ability of the method of velocity selective recording (VSR) to determine the fibre types that contribute to a compound action potential (CAP) propagating along a peripheral nerve. Real-time identification of the active fibre types by determining the direction of action potential propagation (afferent or efferent) and velocity might allow future neural prostheses to make better use of biological sensor signals and provide a new and simple tool for use in fundamental neuroscience. APPROACH: Fibre activity was recorded from explanted Xenopus Laevis frog sciatic nerve using a single multi-electrode cuff that records whole nerve activity with 11 equidistant ring-shaped electrodes. The recorded signals were amplified, delayed against each other with variable delay times, added and band-pass filtered. Finally, the resulting amplitudes were measured. MAIN RESULT: Our experiments showed that electrically evoked frog CAP was dominated by two fibre populations, propagating at around 20 and 40 m/s, respectively. The velocity selectivity, i.e. the ability of the system to discriminate between individual populations was increased by applying band-pass filtering. The method extracted an entire velocity spectrum from a 10 ms CAP recording sample in real time. SIGNIFICANCE: Unlike the techniques introduced in the 1970s and subsequently, VSR requires only a single nerve cuff and does not require averaging to provide velocity spectral information. This makes it potentially suitable for the generation of highly-selective real-time control-signals for future neural prostheses. In our study, electrically evoked CAPs were analysed and it remains to be proven whether the method can reliably classify physiological nerve traffic.
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The ability of velocity selection recording to discriminate recorded activity by fiber type has been validated in several acute in vivo studies.
“The ability of VSR to discriminate recorded activity based on fiber type has been validated in several acute in vivo studies [123, 124, 153]; demonstrating this technique in a chronically implanted model would represent a major advancement.”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [124]
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Cites
A theory of the effects of fibre size in medullated nerve
Rushton, W. A. H. (1951) · The Journal of Physiology · doi:10.1113/jphysiol.1951.sp004655 · Cited by 1,075 · see citing works
CONDUCTION VELOCITY AND DIAMETER OF NERVE FIBERS
Hursh, J. B. (1939) · American Journal of Physiology-Legacy Content · doi:10.1152/ajplegacy.1939.127.1.131 · Cited by 916 · see citing works
Micromachined, Polyimide-Based Devices for Flexible Neural Interfaces
Stieglitz, T., Beutel, H., Schuettler, M., & Meyer, J.-U. (2000) · Biomedical Microdevices · doi:10.1023/a:1009955222114 · Cited by 343 · see citing works
Self-citationElectrical Signs of Nervous Activity
Erlanger, J., & Gasser, H. S. (1937) · University of Pennsylvania Press eBooks · doi:10.9783/9781512819441 · Cited by 309 · see citing works
Principles Underlying New Methods for Chronic Neural Recording
Stein, R. B., Charles, D., DAVIS, L. A., Jhamandas, J. H., Mannard, A., & Nichols, T. R. (1975) · Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · doi:10.1017/s0317167100020333 · Cited by 211 · see citing works
High density interconnects and flexible hybrid assemblies for active biomedical implants
Meyer, J.-U., Stieglitz, T., Scholz, O., Haberer, W., & Beutel, H. (2001) · IEEE Transactions on Advanced Packaging · doi:10.1109/6040.938305 · Cited by 145 · see citing works
Neural signals for command control and feedback in functional neuromuscular stimulation: a review.
Hoffer, J. A., Rb, S., Haugland, M. K., Sinkjær, T., Durfee, W. K., Schwartz, A., Loeb, G. E., & Kantor, C. (1996) · PubMed · Cited by 122 · see citing works
Implantable electrical and mechanical interfaces with nerve and muscle
Hoffer, J. A., & Loeb, G. E. (1980) · Annals of Biomedical Engineering · doi:10.1007/bf02363438 · Cited by 121 · see citing works
Biopotentials as command and feedback signals in functional electrical stimulation systems.
Sinkjær, T., Haugland, M., Inmann, A., Hansen, M., & Nielsen, K. D. (2003) · Medical Engineering and Physics · doi:10.1016/s1350-4533(02)00178-9 · Cited by 118 · see citing works
Struijk, J. J. (1997) · Biophysical Journal · doi:10.1016/s0006-3495(97)78890-8 · Cited by 93 · see citing works
Multiple-electrode nerve cuffs for low-velocity and velocity-selective neural recording
Taylor, J. T., Donaldson, N., & Winter, J. (2004) · Medical & Biological Engineering & Computing · doi:10.1007/bf02347545 · Cited by 79 · see citing works
Self-citationSeparation of multi-unit nerve impulse trains by a multi-channel linear filter algorithm
Roberts, W. M., & Hartline, D. K. (1975) · Brain Research · doi:10.1016/0006-8993(75)90883-5 · Cited by 74 · see citing works
Single unit conduction velocities from averaged nerve cuff electrode records in freely moving cats
Hoffer, J. A., Loeb, G. E., & Pratt, C. A. (1981) · Journal of Neuroscience Methods · doi:10.1016/0165-0270(81)90033-9 · Cited by 73 · see citing works
Conduction velocity in myelinated nerve fibres of Xenopus laevis
Hutchinson, N., Koles, Z. J., & Smith, R. S. (1970) · The Journal of Physiology · doi:10.1113/jphysiol.1970.sp009119 · Cited by 71 · see citing works
Hoffer, J. A., Loeb, G. E., Marks, W. B., O'Donovan, M. J., Pratt, C. A., & Sugano, N. (1987) · Journal of Neurophysiology · doi:10.1152/jn.1987.57.2.510 · Cited by 71 · see citing works
Krarup, C., Loeb, G. E., & Pezeshkpour, G. H. (1988) · Muscle & Nerve · doi:10.1002/mus.880110906 · Cited by 66 · see citing works
Performance of alternative amplifier configurations for tripolar nerve cuff recorded ENG
Pflaum, C., Riso, R. R., & Wießpeiner, G. (2002) · Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/iembs.1996.657000 · Cited by 63 · see citing works
Very Low-Noise ENG Amplifier System Using CMOS Technology
Rieger, R., Schuettler, M., Pal, D., Clarke, C., Langlois, P., Taylor, J., & Donaldson, N. (2006) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2006.886731 · Cited by 57 · see citing works
Self-citationNoise and selectivity of velocity-selective multi-electrode nerve cuffs
Donaldson, N., Rieger, R., Schuettler, M., & Taylor, J. (2008) · Medical and Biological Engineering and Computing · doi:10.1007/s11517-008-0365-4 · Cited by 49 · see citing works
Self-citationKrarup, C., & Loeb, G. E. (1988) · Muscle & Nerve · doi:10.1002/mus.880110905 · Cited by 46 · 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
Inmann, A., & Haugland, M. (2004) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2004.03.003 · Cited by 40 · see citing works
The theory of velocity selective neural recording: a study based on simulation
Taylor, J. T., Schüettler, M., Clarke, C., et al. (2012) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-012-0874-z · Cited by 32 · see citing works
Self-citationThe effect of nerve cuff geometry on interference reduction: a study by computer modeling
Rahal, M., Taylor, J. T., & Donaldson, N. (2000) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.817629 · Cited by 32 · see citing works
Self-citationPartition of Gross Peripheral Nerve Activity into Single Unit Responses by Correlation Techniques
Heetderks, W. J., & Williams, W. J. (1975) · Science · doi:10.1126/science.1118732 · Cited by 25 · see citing works
Conduction velocity changes along lumbar primary afferent fibers in cats
Rindos, A. J., Loeb, G. E., & Levitan, H. (1984) · Experimental Neurology · doi:10.1016/0014-4886(84)90182-1 · Cited by 25 · see citing works
Application of optimal multichannel filtering to simulated nerve signals
Andreassen, S., Stein, R. B., & Oguztöreli, M. N. (1979) · Biological Cybernetics · doi:10.1007/bf00337448 · Cited by 25 · see citing works
Schuettler, M., Seetohul, V., Rijkhoff, N. J. M., Moeller, F. V., Donaldson, N., & Taylor, J. (2011) · 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/iembs.2011.6090847 · Cited by 19 · see citing works
Self-citationHistochemistry and role of nitric oxide synthase in the amphibian (Ambystoma tigrinum) inner ear
Flores, A., León‐Olea, M., Vega, R., et al. (1996) · Neuroscience Letters · doi:10.1016/0304-3940(96)12398-3 · Cited by 15 · see citing works
Implantable electronic devices technology challenges for long‐term human implantation
Vanhoestenberghe, A. (2009) · Sensor Review · doi:10.1108/02602280910986593 · Cited by 10 · see citing works
Signal processing for velocity selective recording systems using analogue delay lines
Rieger, R., Taylor, J. T., & Clarke, C. (2012) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2012.6271725 · Cited by 4 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 3
- Meyer-Waarden K 1985a Der Ursprung Bioelektrischer Signale (Bioelektrische Signale und ihre Ableitverfahren) (New York: Schattauer) pp 5-48, chapter 1
- Meyer-Waarden K 1985b Die Ableittechnik (Bioelektrische Signale und ihre Ableitverfahren) (New York: Schattauer) pp 5-48, chapter 2
- Schuettler M, Doerge T, Wien S L, Becker S, Staiger A, Hanauer M, Kammer S and Stieglitz T 2005 Cytotoxicity of platinum black IFESS: Proc. Annu. Conf. of Int. Functional Electrical Stimulation Society pp 343-8
Cited by
Sorted by citations
Implantable neurotechnologies: a review of micro- and nanoelectrodes for neural recording
Patil, A. C., & Thakor, N. V. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-015-1430-4 · Cited by 175 · see citing works
A review for the peripheral nerve interface designer
Larson, C. E., & Meng, E. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108523 · Cited by 133 · see citing works
Implantable neurotechnologies: a review of integrated circuit neural amplifiers
Ng, K. A., Greenwald, E., Xu, Y. P., & Thakor, N. V. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-015-1431-3 · Cited by 83 · see citing works
Gribi, S., du Bois de Dunilac, S., Ghezzi, D., & Lacour, S. P. (2018) · Nature Communications · doi:10.1038/s41467-018-06895-7 · Cited by 72 · see citing works
Chronic multichannel neural recordings from soft regenerative microchannel electrodes during gait
Musick, K. M., Rigosa, J., Narasimhan, S., Wurth, S., Capogrosso, M., Chew, D. J., Fawcett, J. W., Micera, S., & Lacour, S. P. (2015) · Scientific Reports · doi:10.1038/srep14363 · Cited by 70 · see citing works
Compliant peripheral nerve interfaces.
Paggi, V., Akouissi, O., Micera, S., & Lacour, S. P. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abcdbe · Cited by 60 · see citing works
“For example, the velocity of a signal can be extrapolated from multiple electrodes along the length of the nerve and can then be used to discriminate the different source fibers [69, 70].”
BackgroundHwang, Y.-C. E., Long, L., Filho, J. S., Genov, R., & Zariffa, J. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3355063 · Cited by 15 · see citing works
- Authors
- Schuettler, M., Donaldson, N., Seetohul, V., & Taylor, J.
- Affiliations
- University College London (GB)
- University of Warwick (GB)
- University of Bath (GB)
- Venue
- Journal of Neural Engineering
- Publisher
- IOP Publishing
- Published
- 2013-05-03
- Volume
- 10
- Issue
- 3
- Pages
- 036016
- ISSN
- 1741-2552 (ISSN-L)
- 1741-2560
- OpenAlex
- W2005485113
- Cited by
- 50
- References
- 31
- Citations by year
- 2025: 2 · 2024: 5 · 2022: 4 · 2021: 4 · 2020: 5 · 2019: 7 · 2018: 3 · 2017: 3 · 2016: 7 · 2015: 4 · 2014: 5 · 2013: 1
- FWCI
- 2.78
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Neural Engineering (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Deutscher Akademischer Austauschdienst
- Engineering and Physical Sciences Research Council
- 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 › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- compound action potential, sciatic nerve, Xenopus laevis, action potential propagation velocity, bandpass filtering, neural prostheses, peripheral nerve recording, real-time signal processing
- MeSH terms
- Action Potentials, Algorithms, Animals, Axons, Electrodes, Implanted, Equipment Design, Neural Conduction, Sciatic Nerve, Sensitivity and Specificity, Xenopus laevis, Reproducibility of Results, Equipment Failure Analysis
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