High-density neural recording system design
Open accessAbstract
Implantable medical devices capable of monitoring hundreds to thousands of electrodes have received great attention in biomedical applications for understanding of the brain function and to treat brain diseases such as epilepsy, dystonia, and Parkinson's disease. Non-invasive neural recording modalities such as fMRI and EEGs were widely used since the 1960s, but to acquire better information, invasive modalities gained popularity. Since such invasive neural recording system requires high efficiency and low power operation, they have been implemented as integrated circuits. Many techniques have been developed and applied when designing integrated high-density neural recording architecture for better performance, higher efficiency, and lower power consumption. This paper covers general knowledge of neural signals and frequently used neural recording architectures for monitoring neural activity. For neural recording architecture, various neural recording amplifier structures are covered. In addition, several neural processing techniques, which can optimize the neural recording system, are also discussed.
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Devices implemented using active structures have enabled channel counts orders of magnitude larger than passive interface structures, ranging up to tens of thousands of channels on a single probe.
“Devices implemented using active structures have enabled channel counts orders of magnitude larger than that of passive interface structures [37], ranging up to tens of thousands of channels on a single probe [38].”
From Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review (2024) · cites this paper as [37]
The Introduction (page unavailable) distinguishes active from passive probes and reports that recording-channel counts rose from single channels to thousands. It does not state that active structures achieved counts orders of magnitude greater than passive structures. The tens-of-thousands clause is attached to a different citation, so it is not judged here. (LLM, conf=0.76)
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References 95 · Cited by 17
Research works printed but not linked: 4
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- Authors
- Lee, H.-S., Eom, K., Park, M., Ku, S.-B., Lee, K., & Lee, H.-M.
- Affiliations
- Korea University (KR)
- Venue
- Biomedical Engineering Letters
- Published
- 2022-05-30
- Volume
- 12
- Issue
- 3
- Pages
- 251-261
- ISSN
- 2093-985X (ISSN-L)
- 2093-9868
- PMC
- PMC9308855
- OpenAlex
- W4281787652
- Cited by
- 17
- References
- 95
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 6 · 2023: 2
- FWCI
- 0.29
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Biomedical Engineering Letters (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Research Foundation of Korea (NRF-2020R1F1A1074719, NRF-2020M3F3A2A01081240)
- 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 › Radio Frequency Integrated Circuit Design
- Keywords
- high-density neural recording, low-power integrated circuits, neural signal processing, epilepsy, Parkinson's disease
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