Abstract
Miniaturized and wireless near-infrared (NIR)- based neural recorders with optical powering and data telemetry have been introduced as a promising approach for safe long-term monitoring with the smallest physical dimension among state- of-the-art standalone recorders. However, the main challenge for the NIR-based neural recording integrated circuits (ICs) is to maintain robust operation in the presence of light-induced parasitic short-circuit current from junction diodes. This is especially true when the signal currents are kept small to reduce power consumption. In this work, we present a light-tolerant and low-power neural recording IC for motor prediction that can fully function in up to 300 µW/mm 2 of light exposure. It achieves the best-in-class power consumption of 0.57 µWa t3 8 ◦Cw i t ha 4.1 noise efficiency factor (NEF) pseudo-resistor-less amplifier, an on-chip neural feature extractor, and individual mote-level gain control. Applying the 20-channel pre-recorded neural signals of a monkey, the IC predicts finger position and velocity with Manuscript received August 21, 2021; revised November 19, 2021; accepted December 23, 2021. Date of publication January 25, 2022; date of current version March 28, 2022. This article was approved by Associate Editor Borivoje Nikoli´c. This work was supported by the National Institutes of Health under Grant 5R21EY029452-02. (Corresponding author: Jongyup Lim.) This work involved human subjects or animals in its research. Approval of al