A ±50-mV linear-input-range VCO-based neural-recording front-end with digital nonlinearity correction.
Abstract
Closed-loop neuromodulation is an essential function in future neural implants for delivering efficient and effective therapy. However, a closed-loop system requires the neural-recording front-end to handle large stimulation artifacts-a feature not supported by most state-of-the-art designs. In this paper, we present a neural-recording front-end that has an input range of ±50 mV and can be used in closed-loop systems. The proposed front-end avoids the saturation due to stimulation artifacts by employing a voltage-controlled oscillator (VCO) to directly convert the input signal into the frequency domain. The VCO nonlinearity is corrected using area-efficient foreground polynomial correction. Implemented in a 40-nm CMOS process, the design occupies 0.135 mm2with an analog power of 3 μW and a digital switching power of 4 μW. It achieves ten times higher linear input range than prior art, and 79-dB spurious-free dynamic range at peak input, with an input-referred noise of 5.2 μVrmsacross the local-field-potential band of 1-200 Hz. With on-chip subhertz high-pass filters realized by duty-cycled resistors, the front-end also eliminates the need of off-chip dc-blocking capacitors.
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In another method, the recording amplifier is replaced by a VCO.
“In another innovative method, the recording amplifier is replaced by VCO (Jiang et al., 2017; Jeon et al., 2019).”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Jiang et al., 2017
Applying this method, neural signal recording can be done in the frequency domain.
“Applying this method, the neural signals recording can be done in the frequency domain.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Jiang et al., 2017
VCOs can keep good linearity in a large input range of neural recording.
“Thus, VCOs can keep good linearity in a large input range of neural recording.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Jiang et al., 2017
The proposed circuit in this method quantizes the frequency of the sample by counting the phase increment.
“As shown in Figure 3B, the proposed circuit in this method quantizes the frequency of the sample by counting the phase increment.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Jiang et al., 2017
The feedback DACs compensate the nonlinearity of Gm,in.
“The feedback DACs compensate the nonlinearity of Gm,in.”
From Advances in Neural Recording and Stimulation Integrated Circuits (2021) · cites this paper as Jiang et al., 2017
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- Authors
- Jiang, W., Hokhikyan, V., Chandrakumar, H., Karkare, V., & Markovic, D.
- Affiliations
- University of California, Los Angeles (US)
- Venue
- IEEE Journal of Solid-State Circuits
- Published
- 2017-01
- Volume
- 52
- Issue
- 1
- Pages
- 173-184
- ISSN
- 0018-9200 (ISSN-L)
- 1558-173X
- OpenAlex
- W2567171447
- Cited by
- 140
- References
- 37
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 16 · 2023: 18 · 2022: 18 · 2021: 24 · 2020: 10 · 2019: 14 · 2018: 14 · 2017: 9 · 2016: 3
- FWCI
- 6.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal of Solid-State Circuits (publishedVersion)
- Funders
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Analog and Mixed-Signal Circuit Design
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Radio Frequency Integrated Circuit Design
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Keywords
- voltage-controlled oscillator, closed-loop neuromodulation, neural implants, stimulation artifacts, polynomial correction, spurious-free dynamic range, input-referred noise, 40-nm CMOS, low-power analog circuits
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