Online artifact cancelation in same-electrode neural stimulation and recording using a combined hardware and software architecture.
Open accessAbstract
Advancing studies of neural network dynamics and developments of closed-loop neural interfaces requires the ability to simultaneously stimulate and record the neural cells. Recording adjacent to or at the stimulation site produces artifact signals that are orders of magnitude larger than the neural responses of interest. These signals often saturate the recording amplifier causing distortion or loss of short-latency evoked responses. This paper proposes a method to cancel the artifact in simultaneous neural recording and stimulation on the same electrode. By combining a novel hardware architecture with concurrent software processing, the design achieves neural signal recovery in a wide range of conditions. The proposed system uniquely demonstrates same-electrode stimulation and recording, with neural signal recovery in presence of stimulation artifact 100 dB larger in magnitude than the underlying signals. The system is tested both in vitro and in vivo, during concurrent stimulation and recording on the same electrode. In vivo results in a rodent model are compared to recordings made by a commercial neural amplifier system connected in parallel.
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Culaclii et al. (2018) proposed improved schemes in which both hardware and software are implemented to optimize the system.
“Some improved schemes have been proposed in Culaclii et al. (2018), in which both hardware and software are implemented to optimize the system.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Culaclii et al., 2018
The amplitude of artifacts is reduced by iterative hardware loops instead of filtering them completely.
“As shown in Figure 4C, the amplitude of artifacts is reduced by iterative hardware loops instead of filtering them completely.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Culaclii et al., 2018
The hardware loop stores the artifact as a template and iteratively updates the template according to the recording difference until the template converges within the resolution range of the hardware component.
“The hardware loop stores the artifact as the template and then iteratively updates the template according to the recording difference, until the template converges within the resolution range of the hardware component.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Culaclii et al., 2018
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- Authors
- Culaclii, S., Kim, B., Lo, Y.-K., Li, L., & Liu, W.
- Affiliations
- University of California, Los Angeles (US)
- Venue
- IEEE Transactions on Biomedical Circuits and Systems
- Published
- 2018-06
- Volume
- 12
- Issue
- 3
- Pages
- 601-613
- ISSN
- 1932-4545 (ISSN-L)
- 1940-9990
- PMC
- PMC6299268
- OpenAlex
- W2795647952
- Cited by
- 34
- References
- 36
- Citations by year
- 2026: 6 · 2025: 3 · 2024: 6 · 2023: 4 · 2022: 5 · 2021: 6 · 2020: 2 · 2018: 2
- FWCI
- 1.14
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- IEEE Transactions on Biomedical Circuits and Systems (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Endowment for the Chan Soon-Shiong Bionic Engineering Research Center at University of California
- Los Angeles by California Capital Equity LLC (NIH BRP U01 EB007615, SPARC #1OT2OD024899)
- 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 › Undergraduate Neuroscience Education and Research
- Keywords
- hardware-software co-design
- MeSH terms
- Animals, Electrodes, Male, Signal Processing, Computer-Assisted, Software, Rats, Sprague-Dawley, Rats, Brain Waves, Transcranial Direct Current Stimulation
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