Modular 128-Channel $\Delta$ - $\Delta \Sigma$ Analog Front-End Architecture Using Spectrum Equalization Scheme for 1024-Channel 3-D Neural Recording Microsystems

Abstract

We report an area- and energy-efficient integrated circuit architecture of a 128-channel $\Delta$ -modulated $\Delta \Sigma$ analog front-end ( $\Delta$ - $\Delta \Sigma$ AFE) for 1024-channel 3-D massive-parallel neural recording microsystems. Our platform has adopted a modularity of 128 channels and consists of eight multi-shank neural probes connected to individual AFEs through interposers in a small form factor. In order to reduce both area and energy consumption in the recording circuits, we implemented a spectrum equalization scheme to take advantage of the inherent spectral characteristics of neural signals, where most of the energy is confined in low frequencies and follows a ~1/f curve in the spectrum. This allows us to implement the AFE with a relaxed dynamic range by ~30 dB, thereby contributing to the significant reduction of both energy and area without sacrificing signal integrity. The $\Delta$ - $\Delta \Sigma$ AFE was fabricated using 0.18- $\mu \text{m}$ CMOS processes. The single-channel AFE consumes 3.05 $\mu \text{W}$ from 0.5 and 1.0 V supplies in an area of 0.05 mm2 with 63.8-dB signal-to-noise-and-distortion ratio, 3.02 noise efficiency factor (NEF), and 4.56 NEF2VDD. We also have achieved an energy-area product, a figure-of-merit most critical for massive-parallel neural recording systems, of 6.34 fJ/ $\text{C}\cdot \text{s}\cdot$ mm2.