Stimulus-artifact elimination in a multi-electrode system.
Abstract
To fully exploit the recording capabilities provided by current and future generations of multi-electrode arrays, some means to eliminate the residual charge and subsequent artifacts generated by stimulation protocols is required. Custom electronics can be used to achieve such goals, and by making them scalable, a large number of electrodes can be accessed in an experiment. In this work, we present a system built around a custom 16-channel IC that can stimulate and record, within 3 ms of the stimulus, on the stimulating channel, and within 500 mus on adjacent channels. This effectiveness is achieved by directly discharging the electrode through a novel feedback scheme, and by shaping such feedback to optimize electrode behavior. We characterize the different features of the system that makes such performance possible and present biological data that show the system in operation. To enable this characterization, we present a framework for measuring, classifying, and understanding the multiple sources of stimulus artifacts. This framework facilitates comparisons between artifact elimination methodologies and enables future artifact studies.
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Rdischarge is a variable resistance and the impedance is very large under normal conditions.
“As shown in Figure 4B, Rdischarge is a variable resistance and the impedance is very large under normal conditions.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Brown et al., 2008
When a large artifact is detected, Rdischarge can be changed to a low-impedance value, reducing the RC time constant and making the electrode voltage quickly return to the reference voltage.
“When a large artifact is detected, Rdischarge can be changed to a value with low impedance, then the RC time constant of the path is reduced and thus it makes the electrode voltage quickly return to the reference voltage.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Brown et al., 2008
This method reduces the recovery time from 10 ms to approximately 200 μs, but the problem of artifact recording has not been solved.
“This method reduces the recovery time from 10 ms to approximately 200 μs, but the problem of artifact recording has not been solved.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Brown et al., 2008
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- Authors
- Brown, E. A., Ross, J. D., Blum, R. A., Nam, Y., Wheeler, B. C., & DeWeerth, S. P.
- Affiliations
- Georgia Institute of Technology (US)
- Korea Advanced Institute of Science and Technology (KR)
- University of Illinois Urbana-Champaign (US)
- Venue
- IEEE Transactions on Biomedical Circuits and Systems
- Published
- 2008-03
- Volume
- 2
- Issue
- 1
- Pages
- 10-21
- ISSN
- 1932-4545 (ISSN-L)
- 1940-9990
- OpenAlex
- W2104093558
- Cited by
- 95
- References
- 37
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 2 · 2023: 2 · 2022: 2 · 2021: 6 · 2020: 2 · 2019: 5 · 2018: 5 · 2017: 6 · 2016: 12 · 2015: 8 · 2014: 6 · 2013: 5 · 2012: 5
- FWCI
- 3.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Biomedical Circuits and Systems (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Universidad Simón Bolívar
- Wallace H. Coulter Department of Biomedical Engineering
- 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
- stimulus artifact, microelectrode arrays, electrode stimulation, artifact removal, custom integrated circuits, residual charge, artifact classification, neural recording
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