@article{Obaid2020,
title = {Massively parallel microwire arrays integrated withCMOS chips for neural recording},
author = {Abdulmalik Obaid and Mina-Elrahb Hanna and Yu-Wei Wu and Mihaly Kollo and Romeo Racz and Matthew R Angle and Jan Muller and Nora Brackbill and William Wray and Felix Franke and E J Chichilnski and Andreas Hierlemann and Jun B. Ding and Andreas T. Schaefer and Nicholas A. Melosh},
url = {https://advances.sciencemag.org/content/6/12/eaay2789},
doi = {10.1126/sciadv.aay2789},
year = {2020},
date = {2020-03-20},
journal = {Science Advances},
abstract = {Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.},
keywords = {Electrodes, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}