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Volume 16
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10.3390/bios16070370
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Article

Distributed Wireless Neural Recording System for Multi-Region Brain Activity Monitoring

by
Liu Yang
1,2,†,
Changhua You
3,†,
Gang Wang
4,5,
Xuan Zhang
6,
Canyang Wang
7,
Bo Cheng
7,
Zhengtuo Zhao
8,
Ning Xue
2,* and
Lei Yao
2,*
1
School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 201100, China
2
Lingang Laboratory, Shanghai 201100, China
3
State Key Laboratory of Transducer Technology, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences, Beijing 100190, China
4
Institute of Flexible Electronics Technology of Tsinghua, Jiaxing 314000, China
5
School of Aerospace, Tsinghua University, Beijing 100084, China
6
Mtrix Technology Co., Ltd., Shanghai 201800, China
7
StairMed Technology Co., Ltd., Shanghai 200131, China
8
State Key Laboratory of Neuroscience, Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Biosensors 2026, 16(7), 370; https://doi.org/10.3390/bios16070370
Submission received: 2 June 2026 / Revised: 30 June 2026 / Accepted: 2 July 2026 / Published: 7 July 2026
(This article belongs to the Special Issue Implantable, Wireless Biosensors and Biodevices for Neuroscience Research, 2nd Edition)
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Abstract

Distributed neural interfaces for multi-region implantation require both scalable interconnects and robust telemetry, yet conventional centralized or fully distributed architectures often trade-off wiring complexity, resource reuse, and transmission stability. This work presents a distributed wireless neural recording system based on a parallel-link architecture and a custom 12-channel neural recording Application-Specific Integrated Circuit (ASIC). Each remote module is connected to a central hub through an independent four-wire link (VDD/GND/LVDS±). The ASIC integrates modular digital pixels (MDPs), an on-chip oscillator, a Manchester encoding, and a Low-Voltage Differential Signaling (LVDS) output to reduce interconnect count while maintaining reliable serial transmission. Fabricated in SMIC 0.18 μm CMOS, the chip occupies 4.84 mm × 0.36 mm and consumes 10.13 mW in total, with 48.5 μW/channel consumed by the recording channels excluding the LVDS driver. It achieves 5.6 μVrms input-referred noise and a measured per-channel sampling rate of 28.93 kSps. A compact 20 mm2 recording module and an FPGA-based central hub with real-time decoding and compression were implemented for validation. In vivo mouse experiments demonstrate clear action-potential recordings across 12 channels, confirming the feasibility of stable and scalable multi-region neural signal acquisition.
Keywords: wireless neural recording; multi-region brain monitoring; neural recording ASIC; parallel-link architecture; neural signal detection; compression wireless neural recording; multi-region brain monitoring; neural recording ASIC; parallel-link architecture; neural signal detection; compression

Share and Cite

MDPI and ACS Style

Yang, L.; You, C.; Wang, G.; Zhang, X.; Wang, C.; Cheng, B.; Zhao, Z.; Xue, N.; Yao, L. Distributed Wireless Neural Recording System for Multi-Region Brain Activity Monitoring. Biosensors 2026, 16, 370. https://doi.org/10.3390/bios16070370

AMA Style

Yang L, You C, Wang G, Zhang X, Wang C, Cheng B, Zhao Z, Xue N, Yao L. Distributed Wireless Neural Recording System for Multi-Region Brain Activity Monitoring. Biosensors. 2026; 16(7):370. https://doi.org/10.3390/bios16070370

Chicago/Turabian Style

Yang, Liu, Changhua You, Gang Wang, Xuan Zhang, Canyang Wang, Bo Cheng, Zhengtuo Zhao, Ning Xue, and Lei Yao. 2026. "Distributed Wireless Neural Recording System for Multi-Region Brain Activity Monitoring" Biosensors 16, no. 7: 370. https://doi.org/10.3390/bios16070370

APA Style

Yang, L., You, C., Wang, G., Zhang, X., Wang, C., Cheng, B., Zhao, Z., Xue, N., & Yao, L. (2026). Distributed Wireless Neural Recording System for Multi-Region Brain Activity Monitoring. Biosensors, 16(7), 370. https://doi.org/10.3390/bios16070370

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