Nanoporous graphene-based thin-film microelectrodes for in vivo high-resolution neural recording and stimulation

Author:

Viana Damià,Walston Steven T.ORCID,Masvidal-Codina EduardORCID,Illa XaviORCID,Rodríguez-Meana BrunoORCID,del Valle Jaume,Hayward Andrew,Dodd Abbie,Loret Thomas,Prats-Alfonso ElisabetORCID,de la Oliva Natàlia,Palma Marie,del Corro ElenaORCID,del Pilar Bernicola María,Rodríguez-Lucas Elisa,Gener ThomasORCID,de la Cruz Jose Manuel,Torres-Miranda Miguel,Duvan Fikret TaygunORCID,Ria NicolaORCID,Sperling Justin,Martí-Sánchez Sara,Spadaro Maria Chiara,Hébert Clément,Savage SineadORCID,Arbiol JordiORCID,Guimerà-Brunet AntonORCID,Puig M. VictoriaORCID,Yvert BlaiseORCID,Navarro Xavier,Kostarelos KostasORCID,Garrido Jose A.ORCID

Abstract

AbstractOne of the critical factors determining the performance of neural interfaces is the electrode material used to establish electrical communication with the neural tissue, which needs to meet strict electrical, electrochemical, mechanical, biological and microfabrication compatibility requirements. This work presents a nanoporous graphene-based thin-film technology and its engineering to form flexible neural interfaces. The developed technology allows the fabrication of small microelectrodes (25 µm diameter) while achieving low impedance (∼25 kΩ) and high charge injection (3–5 mC cm2). In vivo brain recording performance assessed in rodents reveals high-fidelity recordings (signal-to-noise ratio >10 dB for local field potentials), while stimulation performance assessed with an intrafascicular implant demonstrates low current thresholds (<100 µA) and high selectivity (>0.8) for activating subsets of axons within the rat sciatic nerve innervating tibialis anterior and plantar interosseous muscles. Furthermore, the tissue biocompatibility of the devices was validated by chronic epicortical (12 week) and intraneural (8 week) implantation. This work describes a graphene-based thin-film microelectrode technology and demonstrates its potential for high-precision and high-resolution neural interfacing.

Funder

EC | Horizon 2020 Framework Programme

Publisher

Springer Science and Business Media LLC

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