The Design of Integrated Circuits to Observe Brain Activity
Abstract
The ability to monitor the simultaneous electrical activity of multiple neurons in the brain enables a wide range of scientific and clinical endeavors. Recent efforts to merge miniature multielectrode neural recording arrays with integrated electronics have revealed significant circuit design challenges. Weak neural signals must be amplified and filtered using low-noise circuits placed close to the electrodes themselves, but power dissipation must strictly be limited to prevent tissue damage due to local heating. In modern recording systems with 100 or more electrodes, raw data rates of 15 Mb/s or more are easily produced. Micropower wireless telemetry circuits cannot transmit information at such high rates, so data reduction must be performed in the implanted device. In this paper, we present integrated circuits and design techniques that address the twin problems of neural signal amplification and data reduction for this severely size- and power-limited application.
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The front-end amplifier should have the lowest input-referred noise and higher gain than later stages because the input-referred noise of later stages is referred back to the electrodes through this amplifier's gain.
“This amplifier should have the lowest input-referred noise and higher gain than the subsequent stages, as the RTI noise of all subsequent stages are referred back to the electrodes through the gain of this amplifier [52].”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [52]
The most common front-end amplifier for IC neural recordings was first proposed by Najafi and Wise and later refined by Harrison to its present circuit.
“The most common front-end amplifier for IC neural recordings was first proposed by Najafi and Wise [89] and then further refined by Harrison [52] to its present circuit shown in Fig. 4.”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [52]
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References 53 · Cited by 330
- Authors
- Harrison, R. R.
- Affiliations
- University of Utah (US)
- Corresponding author
- Harrison, R.R.
- Venue
- Proceedings of the IEEE
- Published
- 2008-07
- Volume
- 96
- Issue
- 7
- Pages
- 1203-1216
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2153636199
- Cited by
- 330
- References
- 53
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 11 · 2023: 12 · 2022: 17 · 2021: 21 · 2020: 24 · 2019: 17 · 2018: 19 · 2017: 15 · 2016: 22 · 2015: 32 · 2014: 19 · 2013: 20 · 2012: 23
- FWCI
- 13.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Proceedings of the IEEE (publishedVersion)
- Proceedings of the IEEE
- Funders
- University of Utah
- 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
- neural signal amplification, low-noise circuits, low power design, data reduction, wireless telemetry, high-speed data transmission, brain activity monitoring
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