A 64-Channel Inverter-Based Neural Signal Recording Amplifier With a Novel Differential-Like OTA Achieving an NEF of 0.84
Qiuzhen Xu, Gen Li, Yanyan Liu, Feng Luo, Zhiming Xiao
Abstract
This article presents an inverter-based multichannel low-power low-noise neural signal recording amplifier with a novel differential-like operational transconductance amplifier (OTA). The differential-like OTA consists of two asymmetric branches. The inverting branch used for multichannel inputs has more inverters in parallel than that of the noninverting branch used for reference. Two virtual rails with very low impedance are designed in the differential-like OTA to effectively reduce the noise-efficiency-factor (NEF) and crosstalk in input channels. The NEF and the effective average current per channel decreases as the number of channels increases. Furthermore, by optimizing the current ratio of the inverting and the noninverting branches of the OTA, the NEF of the proposed amplifier is minimized and approaches the NEF of an ideal inverter of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sqrt 2/2$</tex-math> </inline-formula> as the channel counts increase to infinity. The area per channel is reduced even more significantly as the channel counts increase. The proposed amplifier architecture with 4-channel, 16-channel, and 64-channel configurations were fabricated and measured. The results show that the noise, power, and area performance were all improved by integrating more channels in parallel. For the 64-channel amplifier, the measured NEF is 0.84, the effective average current per channel is 422 nA and the area per channel is only 0.044 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{2}$</tex-math> </inline-formula> .