A 1024-Channel Hybrid Voltage/Current-Clamp Neural Interface System-on-Chip With Dynamic Incremental SAR Acquisition

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Authors: Jun Wang, Omowuyi Olajide, Akshay Paul, Dinghong Zhang, Jiajia Wu, Yuchen Xu, Yimin Zou, Chul Kim, Gert Cauwenberghs
Cited by: 1
References: 40

Abstract

The demand for high-throughput, multi-modal recording and stimulation in neuroscience research has driven the development of neural interfaces that optimize area and energy efficiency without compromising noise performance. Simultaneously, the need for on-chip data compression to reduce data volume has become increasingly critical. This work presents a neural interface system-on-chip (NISoC) that incorporates 1,024 channels for simultaneous electrical recording and stimulation, enabling high-resolution, high-throughput electrophysiology with record noise-energy efficiency. The 2 mm $\boldsymbol{\times}$ 2 mm NISoC, fabricated using 65 nm CMOS technology, integrates a 32 $\boldsymbol{\times}$ 32 array of electrodes vertically coupled to analog front-ends. These front-ends support both voltage and current clamping through a programmable interface, providing a voltage range up to 100 dB and a current range of 120 dB. Each channel operates at a power consumption of 0.81 $\mu$W, achieving an input-referred voltage noise of 8.8 $\mu V_{rms}$ over a signal bandwidth from DC to 12.5 kHz. The NISoC also integrates on-chip data acquisition through a back-end array of 32 dynamic incremental SAR ADCs, achieving 25 Msps and 11 effective number of bits (ENOB) acquisition with an energy efficiency of 2 fJ/level. The dynamic incremental SAR ADC architecture further offers additional functionality of intrinsic spike detection for future on-chip neural data compression.

Fields of Study & Subjects

Neuroscience and Neural Engineering Analog and Mixed-Signal Circuit Design Neural dynamics and brain function

Publication details

Journal / source
IEEE Transactions on Biomedical Circuits and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
20
Issue
3
Pages
458–469
Publication date
21 January 2026
Language
EN