An AC-Coupled 1st-order Δ-ΔΣ Readout IC for Area-Efficient Neural Signal Acquisition

IEEE J Solid-State Circuits. 2023 Apr;58(4):949-960. doi: 10.1109/JSSC.2023.3234612. Epub 2023 Jan 16.

Abstract

The current demand for high-channel-count neural-recording interfaces calls for more area- and power-efficient readout architectures that do not compromise other electrical performances. In this paper, we present a miniature 128-channel neural recording integrated circuit (NRIC) for the simultaneous acquisition of local field potentials (LFPs) and action potentials (APs), which can achieve a very good compromise between area, power, noise, input range and electrode DC offset cancellation. An AC-coupled 1st-order digitally-intensive Δ-ΔΣ architecture is proposed to achieve this compromise and to leverage the advantages of a highly-scaled technology node. A prototype NRIC, including 128 channels, a newly-proposed area-efficient bulk-regulated voltage reference, biasing circuits and a digital control, has been fabricated in 22-nm FDSOI CMOS and fully characterized. Our proposed architecture achieves a total area per channel of 0.005 mm2, a total power per channel of 12.57 μW, and an input-referred noise of 7.7 ± 0.4 μVrms in the AP band and 11.9 ± 1.1 μVrms in the LFP band. A very good channel-to-channel uniformity is demonstrated by our measurements. The chip has been validated in vivo, demonstrating its capability to successfully record full-band neural signals.

Keywords: Neural recording; analog-to-digital converter; brain-machine interface; continuous-time delta-sigma conversion; electrophysiology; high-density.