WAND: A 128-channel, closed-loop, wireless artifact-free neuromodulation device
Abstract
Closed-loop neuromodulation systems aim to treat a variety of neurological conditions by dynamically delivering and adjusting therapeutic electrical stimulation in response to a patient's neural state, recorded in real-time. Existing systems are limited by low channel counts, lack of algorithmic flexibility, and distortion of recorded signals from large, persistent stimulation artifacts. Here, we describe a device that enables new research applications requiring high-throughput data streaming, low-latency biosignal processing, and truly simultaneous sensing and stimulation. The Wireless Artifact-free Neuromodulation Device (WAND) is a miniaturized, wireless neural interface capable of recording and stimulating on 128 channels with on-board processing to fully cancel stimulation artifacts, detect neural biomarkers, and automatically adjust stimulation parameters in a closed-loop fashion. It combines custom application specific integrated circuits (ASICs), an on-board FPGA, and a low-power bidirectional radio. We validate wireless, long-term recordings of local field potentials (LFP) and real-time cancellation of stimulation artifacts in a behaving nonhuman primate (NHP). We use WAND to demonstrate a closed-loop stimulation paradigm to disrupt movement preparatory activity during a delayed-reach task in a NHP in vivo. This wireless device, leveraging custom ASICs for both neural recording and electrical stimulation modalities, makes possible a neural interface platform technology to significantly advance both neuroscientific discovery and preclinical investigations of stimulation-based therapeutic interventions.
Cite
@article{arxiv.1708.00556,
title = {WAND: A 128-channel, closed-loop, wireless artifact-free neuromodulation device},
author = {Andy Zhou and Samantha R. Santacruz and Benjamin C. Johnson and George Alexandrov and Ali Moin and Fred L. Burghardt and Jan M. Rabaey and Jose M. Carmena and Rikky Muller},
journal= {arXiv preprint arXiv:1708.00556},
year = {2018}
}