A wireless neural interface for chronic recording,
Abstract
A primary goal of the integrated neural interface project (INIP) is to develop a wireless, implantable device capable of recording neural activity from 100 micromachined electrodes. The heart of this recording system is a low-power integrated circuit that amplifies 100 weak neural signals, detects spikes with programmable threshold-crossing circuits, and returns these data via digital radio telemetry. The chip receives power, clock, and command signals through a coil-to-coil inductive link. Here we report that the isolated integrated circuit successfully recorded and wirelessly transmitted digitized electrical activity from peripheral nerve and cortex at 15.7 kS/s. The chip also simultaneously performed accurate on-chip spike detection and wirelessly transmitted the spike threshold-crossing data. We also present preliminary successful results from full system integration and packaging.
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A wireless neural interface could still accurately transmit recorded potentials in peripheral nerves with a USEA.
“Harrison et al. showed that a wireless neural interface could still accurately transmit recorded potentials in peripheral nerves with a USEA (Harrison et al., 2008).”
From Update on Peripheral Nerve Electrodes for Closed-Loop Neuroprosthetics (2018) · cites this paper as Harrison et al., 2008
Cites
A low-power integrated circuit for a wireless 100-electrode neural recording system.
Harrison, R. R., Watkins, P. T., Kier, R. J., Lovejoy, R. O., Black, D. J., Greger, B., & Solzbacher, F. (2007) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2006.886567 · Cited by 782 · see citing works
Self-citationA Low-Power Integrated Circuit for a Wireless 100-Electrode Neural Recording System
Harrison, R. R., Watkins, P., Kier, R. J., Lovejoy, R. O., Black, D., Normann, R. A., & Solzbacher, F. (2006) · Digest of technical papers/Digest of technical papers - IEEE International Solid-State Circuits Conference · doi:10.1109/isscc.2006.1696288 · Cited by 731 · see citing works
Self-citationEncapsulation of an Integrated Neural Interface Device With Parylene C
Jui-Mei, H., Rieth, L. W., Normann, R. A., Tathireddy, P., & Solzbacher, F. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.2002155 · Cited by 241 · see citing works
Self-citationHermesC: RF wireless low-power neural recording system for freely behaving primates
Chestek, C. A., Gilja, V., Nuyujukian, P., et al. (2008) · doi:10.1109/iscas.2008.4541777 · Cited by 25 · see citing works
Self-citationTopper, M. J., Klein, M., Buschick, K., Glaw, V., Orth, K., Ehrmann, O., Hütter, M., Oppermann, H. H., Becker, K.-F., Braun, T., et al. (2006) · IEEE Electronic Components and Technology Conference (ECTC) · doi:10.1109/ectc.2006.1645734 · Cited by 24 · see citing works
Self-citationWireless neural signal acquisition with single low-power integrated circuit
Harrison, R. R., Kier, R. J., Greger, B. E., et al. (2008) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas.2008.4541776 · Cited by 15 · see citing works
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A Materials Roadmap to Functional Neural Interface Design
Wellman, S. M., Eles, J. R., Ludwig, K. A., Seymour, J. P., Michelson, N. J., McFadden, W. E., Vazquez, A. L., & Kozai, T. D. Y. (2018) · Advanced Functional Materials · doi:10.1002/adfm.201701269 · Cited by 389 · see citing works
Xie, X., Rieth, L., Williams, L., Negi, S., Bhandari, R., Caldwell, R., Sharma, R., Tathireddy, P., & Solzbacher, F. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/2/026016 · Cited by 137 · see citing works
Self-citationHuman cortical prostheses: lost in translation?
Ryu, S. I., & Shenoy, K. V. (2009) · Neurosurgical Focus · doi:10.3171/2009.4.focus0987 · Cited by 104 · see citing works
Self-citationUpdate on Peripheral Nerve Electrodes for Closed-Loop Neuroprosthetics
Rijnbeek, E. H., Eleveld, N., & Olthuis, W. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00350 · Cited by 91 · see citing works
“Some USEAs show no or little chronic damage to the nerve up to 8 weeks (Wark et al., 2014) and 7 months (Branner et al., 2004) after implantation.”
BackgroundInfluentialSharma, A., Rieth, L., Tathireddy, P., Harrison, R., Oppermann, H., Klein, M., Töpper, M., Jung, E., Normann, R., Clark, G., et al. (2012) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2011.11.015 · Cited by 35 · see citing works
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- Authors
- Harrison, R. R., Kier, R. J., Kim, S., Rieth, L., Warren, D. J., Ledbetter, N. M., Clark, G. A., Solzbacher, F., Chestek, C. A., Gilja, V., Nuyujukian, P., Ryu, S. I., & Shenoy, K. V.
- Affiliations
- University of Utah (US)
- Stanford University (US)
- Stanford Medicine (US)
- ORCID
- Venue
- 2008 IEEE Biomedical Circuits and Systems Conference
- Publisher
- IEEE
- Published
- 2008
- Pages
- 125-128
- OpenAlex
- W2143799451
- Cited by
- 19
- References
- 6
- Citations by year
- 2024: 1 · 2022: 1 · 2021: 1 · 2020: 1 · 2019: 1 · 2018: 1 · 2017: 2 · 2014: 2 · 2013: 1
- FWCI
- 9.66
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Biomedical Circuits and Systems Conference (BioCAS) (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- wireless neural interface, implantable neural recording, low-power integrated circuits, neural signal amplification, spike detection, inductive power transfer, peripheral nerve recording, cortical recording
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