Inverter-Based Pseudo-Differential Reconfigurable Pixel Circuit Array for Multimodal and High-Density Neural Recordings

Abstract

This paper presents the inverter-based pseudo-differential reconfigurable pixel array. For monitoring multimodal neural activity, the pixel array can change its recording configuration between voltage- and current-recording modes. During the voltage-recording mode, the pixel is configured in the capacitively-coupled instrumentation amplifier (CCIA), which is designed to occupy minimal chip area. During the current-recording mode, the complementary diode-connected load (CDCL) is used in conjunction with the CCIA to filter the input offset current and amplify the current signal. To conduct high-density neural recording, we employ the inverter-based structure for the CCIA and use its parasitic capacitance between the gate and drain terminals as the feedback capacitor, thus reducing the input capacitor of the CCIA. Thanks to the use of CDCL, the current recording is conducted without a significant increase in the design area. The proposed array, implemented in a 180-nm CMOS process, achieves the input noise of 5.86 mu V-rms and 18.17 pA(rms) for voltage- and currentrecording modes over 10-kHz bandwidth, respectively.