A three-dimensional neural recording microsystem with implantable data compression circuitry
Abstract
A 256-site, fully implantable, 3-D neural recording microsystem has been developed. The microsystem incorporates four active neural probes with integrated circuitry for site selection, amplification, and multiplexing. The probes drive an embedded data-compression ASIC that successfully detects neural spikes in the presence of neural and circuit noise. The spike detection ASIC achieves a factor of 12 bandwidth reduction while preserving the key features of the action potential waveshape necessary for spike discrimination. This work extends the total number of neural channels that can be recorded across a transcutaneous inductively coupled wireless link from 25 to 312. When a spike is detected, this ASIC serially shifts the 5-bit amplitude and 5-bit address of the spike off of the chip over a single 2.5 Mb/s wired or wireless line. The spike detection ASIC occupies 6 mm/sup 2/ in 0.5 /spl mu/m features and consumes 2.6 mW while the entire microsystem consumes 5.4 mW of power from a 3-V supply.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Multiplexing a high-density electrode array to a smaller amplifier array is a widely used resource-sharing technique that relies on not all electrode sites providing useful information after implantation or on necessary information being obtainable from a small subset, although the useful subset is not known in advance.
“The first widely used technique consists of multiplexing a high-density electrode array to a much smaller amplifier array. This strategy leverages the fact that not all electrode sites may provide useful information after implantation [97, 101, 145] or that the necessary information can be obtained from a small subset of electrodes, although the useful electrode subset is not known a priori [118].”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [97]
Cites
Analog Integrated Circuit Design
Carusone, A. C., Johns, D. A., & Martin, K. W. (1996) · Cited by 2,509 · see citing works
Learning to control a brain–machine interface for reaching and grasping by primates
Carmena, J. M., Lebedev, M. A., Crist, R. E., O'Doherty, J. E., Santucci, D. M., Dimitrov, D. F., Patil, P. G., Henriquez, C. S., & Nicolelis, M. A. L. (2003) · PLoS Biology · doi:10.1371/journal.pbio.0000042 · Cited by 1,761 · see citing works
Analog integrated circuit design
Hurst, S. L. (1998) · Microelectronics Journal · doi:10.1016/s0026-2692(97)00051-7 · Cited by 1,734 · see citing works
Direct Cortical Control of 3D Neuroprosthetic Devices
Taylor, D. M., Tillery, S. I. H., & Schwartz, A. B. (2002) · Science · doi:10.1126/science.1070291 · Cited by 1,542 · see citing works
Instant neural control of a movement signal
Serruya, M. D., Hatsopoulos, N. G., Paninski, L., Fellows, M. R., & Donoghue, J. P. (2002) · Nature · doi:10.1038/416141a · Cited by 1,415 · see citing works
Electrophysiology of a Dendritic Neuron Model
Rall, W. (1962) · Biophysical Journal · doi:10.1016/s0006-3495(62)86953-7 · Cited by 495 · see citing works
The Motor Cortex and the Coding of Force
Georgopoulos, A. P., Ashe, J., Smyrnis, N., & Taira, M. (1992) · Science · doi:10.1126/science.256.5064.1692 · Cited by 461 · see citing works
Massively Parallel Recording of Unit and Local Field Potentials With Silicon-Based Electrodes
Csicsvari, J., Henze, D. A., Jamieson, B., Harris, K. D., Sirota, A., Barthó, P., Wise, K. D., & Buzsáki, G. (2003) · Journal of Neurophysiology · doi:10.1152/jn.00116.2003 · Cited by 402 · see citing works
Self-citationEvaluation of Spike-Detection Algorithms for a Brain-Machine Interface Application
Iyad Obeid, A., & Wolf, P. D. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.826683 · Cited by 262 · see citing works
A high-yield microassembly structure for three-dimensional microelectrode arrays
Bai, Q., Wise, K. D., & Anderson, D. J. (2000) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.827288 · Cited by 245 · see citing works
Self-citationSingle-unit neural recording with active microelectrode arrays
Bai, Q., & Wise, K. D. (2001) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.936367 · Cited by 214 · see citing works
Self-citationOlssonIII, R. H., Buhl, D. L., Sirota, A. M., Buzsaki, G., & Wise, K. D. (2005) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2005.847540 · Cited by 181 · see citing works
Self-citationA low-power integrated circuit for adaptive detection of action potentials in noisy signals
Harrison, R. R. (2004) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2003.1280856 · Cited by 138 · see citing works
Silicon neural recording arrays with on-chip electronics for in-vivo data acquisition
Olsson, R. H., Gulari, M. N., & Wise, K. D. (2003) · International IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine and Biology (MMB) · doi:10.1109/mmb.2002.1002321 · Cited by 56 · see citing works
Self-citationSpike separation in multiunit records: A multivariate analysis of spike descriptive parameters
Vibert, J. F., & Costa, J. D. S. (1979) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(79)90219-0 · Cited by 41 · see citing works
Dipole characteristics of pyramidal cell activity in cat postcruciate cortex.
Rosenthal, F., Woodbury, J. W., & Patton, H. D. (1966) · Journal of Neurophysiology · doi:10.1152/jn.1966.29.4.612 · Cited by 24 · see citing works
A WIRELESS MICROSYSTEM FOR MULTICHANNEL NEURAL RECORDING MICROPROBES
Yu, H., Olsson, R. H., Wise, K. D., & Najafi, K. (2004) · Solid-State Sensors, Actuators, and Microsystems Workshop (Hilton Head Workshop) · doi:10.31438/trf.hh2004.31 · Cited by 22 · see citing works
Self-citationA 1.5 V class AB output buffer
You, F., Embabi, S. H. K., & Sánchez‐Sinencio, E. (1996) · doi:10.5555/252493.252620 · Cited by 5 · see citing works
Performance characteristics of active silicon microelectrode arrays.
Lund, J. L. (1996) · Deep Blue (University of Michigan) · Cited by 4 · see citing works
A 1.5 V class AB output buffer
You, F., Embabi, S. H. K., & Sinencio, E. S. (2002) · International Symposium on Low Power Electronics and Design (ISLPED) · doi:10.1109/lpe.1996.547524 · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Revealing neuronal function through microelectrode array recordings
Obien, M. E. J., Deligkaris, K., Bullmann, T., Bakkum, D. J., & Frey, U. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00423 · Cited by 705 · see citing works
A 128-Channel 6 mW Wireless Neural Recording IC With Spike Feature Extraction and UWB Transmitter
Chae, M. S., Yang, Z., Yuce, M. R., Hoang, L., & Liu, W. (2009) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2009.2021607 · Cited by 369 · see citing works
The Design of Integrated Circuits to Observe Brain Activity
Harrison, R. R. (2008) · Proceedings of the IEEE · doi:10.1109/jproc.2008.922581 · Cited by 330 · see citing works
An Implantable 455-Active-Electrode 52-Channel CMOS Neural Probe
Lopez, C. M., Andrei, A., Mitra, S., Welkenhuysen, M., Eberle, W., Bartic, C., Puers, R., Yazicioglu, R. F., & Gielen, G. G. E. (2014) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2013.2284347 · Cited by 264 · see citing works
An Implantable 64-Channel Wireless Microsystem for Single-Unit Neural Recording
Sodagar, A. M., Perlin, G. E., Yao, Y., Najafi, K., & Wise, K. D. (2009) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2009.2023159 · Cited by 218 · see citing works
Self-citationSilicon microsystems for neuroscience and neural prostheses
Wise, K. D. (2005) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2005.1511497 · Cited by 194 · see citing works
Self-citation256-Channel Neural Recording and Delta Compression Microsystem With 3D Electrodes
Aziz, J. N. Y., Abdelhalim, K., Shulyzki, R., Genov, R., Bardakjian, B. L., Derchansky, M., Serletis, D., & Carlen, P. L. (2009) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2008.2010997 · Cited by 184 · see citing works
Han, D., Zheng, Y., Rajkumar, R., Dawe, G. S., & Je, M. (2013) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2014.2298860 · Cited by 147 · see citing works
A Low-Power 32-Channel Digitally Programmable Neural Recording Integrated Circuit
Wattanapanitch, W., & Sarpeshkar, R. (2011) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2011.2163404 · Cited by 146 · see citing works
A 100-Channel 1-mW Implantable Neural Recording IC
Zou, X., Liu, L., Cheong, J. H., Yao, L., Li, P., Cheng, M.-Y., Goh, W. L., Rajkumar, R., Dawe, G. S., Cheng, K.-W., et al. (2013) · IEEE Transactions on Circuits and Systems I: Regular Papers · doi:10.1109/tcsi.2013.2249175 · Cited by 132 · see citing works
Low-Power Circuits for Brain–Machine Interfaces
Sarpeshkar, R., Wattanapanitch, W., Arfin, S. K., Rapoport, B. I., Mandal, S., Baker, M. W., Fee, M. S., Musallam, S., & Andersen, R. A. (2008) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2008.2003198 · Cited by 91 · 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
Seidl, K., Herwik, S., Torfs, T., Neves, H. P., Paul, O., & Ruther, P. (2011) · Journal of Microelectromechanical Systems · doi:10.1109/jmems.2011.2167661 · Cited by 68 · see citing works
32.9 nV/rt Hz ${-}$60.6 dB THD Dual-Band Micro-Electrode Array Signal Acquisition IC
Guo, J., Yuan, J., Huang, J., Law, J. K.-Y., Yeung, C.-K., & Chan, M. (2012) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2012.2185590 · Cited by 45 · see citing works
Al-Ashmouny, K. M., Chang, S.-I., & Yoon, E. (2012) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2012.2218105 · Cited by 28 · see citing works
Design Considerations for Implantable Neural Circuits and Systems
Hsu, W.-Y., Hsieh, P.-H., & Chen, H. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_19 · Cited by 1 · see citing works
- Authors
- Olsson, R. H., & Wise, K. D.
- Affiliations
- Sandia National Laboratories (US)
- University of Michigan (US)
- ORCID
- Olsson, R.H.
- Venue
- IEEE Journal of Solid-State Circuits
- Published
- 2005-12
- Volume
- 40
- Issue
- 12
- Pages
- 2796-2804
- ISSN
- 0018-9200 (ISSN-L)
- OpenAlex
- W1608291116
- Cited by
- 245
- References
- 20
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 3 · 2023: 4 · 2022: 3 · 2021: 4 · 2020: 5 · 2019: 8 · 2018: 7 · 2017: 12 · 2016: 13 · 2015: 17 · 2014: 11 · 2013: 20 · 2012: 14
- FWCI
- 11.59
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal of Solid-State Circuits (publishedVersion)
- Funders
- National Institute of Neurological Disorders and Stroke
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Keywords
- implantable neural recording, spike detection, neural spikes, wireless data transmission, inductive coupling, low power design
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
