The Argo: a high channel count recording system for neural recording in vivo
Open accessAbstract
Objective. Decoding neural activity has been limited by the lack of tools available to record from large numbers of neurons across multiple cortical regions simultaneously with high temporal fidelity. To this end, we developed the Argo system to record cortical neural activity at high data rates. Approach. Here we demonstrate a massively parallel neural recording system based on platinum-iridium microwire electrode arrays bonded to a CMOS voltage amplifier array. The Argo system is the highest channel count in vivo neural recording system, supporting simultaneous recording from 65 536 channels, sampled at 32 kHz and 12-bit resolution. This system was designed for cortical recordings, compatible with both penetrating and surface microelectrodes. Main results. We validated this system through initial bench testing to determine specific gain and noise characteristics of bonded microwires, followed by in-vivo experiments in both rat and sheep cortex. We recorded spiking activity from 791 neurons in rats and surface local field potential activity from over 30 000 channels in sheep. Significance. These are the largest channel count microwire-based recordings in both rat and sheep. While currently adapted for head-fixed recording, the microwire-CMOS architecture is well suited for clinical translation. Thus, this demonstration helps pave the way for a future high data rate intracortical implant.
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Approaches are being developed to improve throughput, sampling, biocompatibility and stability of MEAs.
“Similarly, both in academic and industry settings, approaches are being developed to improve throughput, sampling, biocompatibility and stability of MEAs183–186.”
From The speech neuroprosthesis (2024) · cites this paper as [186]
Next-generation recording devices are under development.
“next-generation recording devices are under development35,36”
From A high-performance speech neuroprosthesis (2023) · cites this paper as [36]
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References 85 · Cited by 124
Research works printed but not linked: 2
- [39]Khan A, Sahasrabuddhe K, Pouzzner D, Nishimura K and Angle M 2018 Data pipeline for 65,536 channels of extracellular unit recordings 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, 2018, WeAT17.3.
- [74]Gierthmuehlen M, Wang X, Gkogkidis A, Henle C, Fischer J, Fehrenbacher T, Kohler F, Raab M, Mader I, Kuehn C, Foerster K, Haberstroh J, Freiman TM, Stieglitz T, Rickert J, Schuettler M and Ball T 2014 Mapping of sheep sensory cortex with a novel microelectrocorticography grid J. Comp. Neurol. 522 3590– 608 24851798
- Authors
- Sahasrabuddhe, K., Khan, A. A., Singh, A. P., Stern, T. M., Ng, Y., Tadić, A., Orel, P., LaReau, C., Pouzzner, D., Nishimura, K., Boergens, K. M., Shivakumar, S., Hopper, M. S., Kerr, B., Hanna, M.-E. S., Edgington, R. J., McNamara, I., Fell, D., Gao, P., Babaie-Fishani, A., Veijalainen, S., Klekachev, A. V., Stuckey, A. M., Luyssaert, B., Kozai, T. D. Y., Xie, C., Gilja, V., Dierickx, B., Kong, Y., Straka, M., Sohal, H. S., & Angle, M. R.
- Affiliations
- University of Pittsburgh (US)
- Rice University (US)
- University of California San Diego (US)
- Corresponding author
- Ng, Yeena
- Angle, Matthew R
- ORCID
- Sahasrabuddhe, Kunal
- Khan, Aamir A
- Singh, Aditya P
- Stern, Tyler M
- Ng, Yeena
- Tadić, Aleksandar
- Orel, Peter
- LaReau, Chris
- Pouzzner, Daniel
- Nishimura, Kurtis
- Boergens, Kevin M
- Shivakumar, Sashank
- Hopper, Matthew S
- Kerr, Bryan
- Hanna, Mina-Elraheb S
- Edgington, Robert J
- McNamara, Ingrid
- Fell, Devin
- Gao, Peng
- Babaie-Fishani, Amir
- Veijalainen, Sampsa
- Klekachev, Alexander V
- Stuckey, Alison M
- Luyssaert, Bert
- Kozai, Takashi D Y
- Xie, Chong
- Gilja, Vikash
- Dierickx, Bart
- Kong, Yifan
- Straka, Malgorzata
- Sohal, Harbaljit S
- Angle, Matthew R
- Venue
- Journal of Neural Engineering
- Publisher
- IOP Publishing
- Published
- 2021-02-01
- Volume
- 18
- Issue
- 1
- Pages
- 015002
- ISSN
- 1741-2552 (ISSN-L)
- 1741-2560
- PMC
- PMC8607496
- OpenAlex
- W3113043584
- Cited by
- 124
- References
- 85
- Citations by year
- 2026: 14 · 2025: 32 · 2024: 28 · 2023: 22 · 2022: 12 · 2021: 14 · 2020: 2
- FWCI
- 5.69
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Journal of Neural Engineering (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute of Mental Health (5R43MH110287-02)
- Defense Advanced Research Projects Agency (N66001-17-C-4005)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- local field potentials, neural decoding, rat cortex
- MeSH terms
- Amplifiers, Electronic, Animals, Electrodes, Implanted, Microelectrodes, Neurons, Sheep, Rats
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