A Wide Dynamic Range Neural Data Acquisition System With High-Precision Delta-Sigma ADC and On-Chip EC-PC Spike Processor

A high-performance, wide dynamic range, fully-integrated neural interface is one key component for many advanced bidirectional neuromodulation technologies. In this paper, to complement the previously proposed frequency-shaping amplifier (FSA) and high-precision electrical microstimulator, we will present a proof-of-concept design of a neural data acquisition (DAQ) system that includes a 15-bit, low-power Delta-Sigma analog-to-digital converter (ADC) and a real-time spike processor based on one exponential component-polynomial component (EC-PC) algorithm. High-precision data conversion with low power consumption and small chip area is achieved by employing several techniques, such as opamp-sharing, multi-bit successive approximation (SAR) quantizer, two-step summation, and ultra-low distortion data weighted averaging (DWA). The on-chip EC-PC engine enables low latency, automatic detection, and extraction of spiking activities, thus supporting closed-loop control, real-time data compression and$/$or neural information decoding. The prototype chip was fabricated in a 0.13 $\mu$m CMOS process and verified in both bench-top and In-Vivo experiments. Bench-top measurement results indicate the designed ADC achieves a peak signal-to-noise and distortion ratio (SNDR) of 91.8 dB and a dynamic range of 93.0 dB over a 10 kHz bandwidth, where the total power consumption of the modulator is only 20 $\mu$W at 1.0 V supply, corresponding to a figure-of-merit (FOM) of 31.4fJ$/$conversion-step. In In-Vivo experiments, the proposed DAQ system has been demonstrated to obtain high-quality neural activities from a rat’s motor cortex and also greatly reduce recovery time from system saturation due to electrical microstimulation.

I. Introduction

Nowadays, bidirectional neuromodulation technologies with simultaneous recording and stimulation are urgently demanded in both neuroscience research and neurobiological disease treatment, such as brain-machine-interface (BMI) experiments, stroke rehabilitation, Parkinson’s disease, epilepsy, and severe depression [1]–[11]. Some recent neural recording experiments show that extracellular spikes are from several V to several hundreds of V, local field potentials (LFPs) or power line interferences are at a range of mV, and motion artifacts reach tens of mV [12]–[14]. Thus, a wide system dynamic range is required to simultaneously record LFPs, extracellular spikes, motion artifacts, and power line interferences without saturating circuits. The requirement on system dynamic range is further pushed when supporting more sophisticated neuroscience experiments and clinical applications, where electrical microstimulation is used for probing neural circuitry and identifying networks of neurons. However, large amplitude stimulation artifacts (>100 mV) that frequently appear in the experimentsapplications [15], [16] will saturate the recording systems. Thus, one key challenge is how to reduce recovery time from system saturation due to electrical microstimulation.