A 0.00426 mm 2 77.6-dB Dynamic Range VCO-Based CTDSM for Multi-Channel Neural Recording.

Autor: Wang, Shiwei, Yang, Xiaolin, Wang, Chaohan, Vilouras, Anastasios, Lopez, Carolina Mora
Předmět:
Zdroj: Electronics (2079-9292); Nov2022, Vol. 11 Issue 21, p3477, 11p
Abstrakt: Driven by needs in neuroscientific research, future neural interface technologies demand integrated circuits that can record a large number of channels of neural signals in parallel while maintaining a miniaturized physical form factor. Using conventional methods, it is challenging to reduce circuit area while maintaining the high dynamic range, low noise, and low power consumption required in the neural application. This paper proposes to address this challenge using a VCO-based continuous-time delta-sigma modulator (CTDSM) circuit, which can record and digitize neural signals directly without the need for front-end instrumentation amplifiers and anti-aliasing filters, which are limited by the abovementioned circuit-area performance tradeoff. Thanks to the multi-level quantization and intrinsic mismatch-shaping capabilities of the VCO-based approach, the proposed first-order CTDSM can achieve comparable electrical performance to a higher-order CTDSM while offering further area and power reductions. We prototyped the circuit in a 22-channel test chip and demonstrate, based on the chip measurement results, that the proposed modulator occupies an area of 0.00426 mm2 while achieving input-referred noise levels of 6.26 and 3.54 µVrms in the action potential (AP) and local field potential (LFP) bands, respectively. With a 77.6 dB wide-dynamic range, the noise and total harmonic distortion meet the requirements of a neural interface with up to 149 mVpp input AC amplitude or up to ±68 mV DC offsets. We also validated the feasibility of the circuit for multi-channel recording applications by examining the impact of cross-channel VCO oscillation interferences on the circuit noise performance. The experimental results demonstrate the proposed architecture is an excellent candidate to implement future multi-channel neural-recording interfaces. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index