Nature Nanotechnology 2024, in press [https://doi.org/10.1038/s41565-023-01570-5]

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

Damià Viana^, Steven T. Walston^, Eduard Masvidal-Codina^, Xavier Illa, Bruno Rodríguez-Meana, Jaume del Valle, Andrew Hayward, Abbie Dodd, Thomas Loret, Elisabet Prats-Alfonso, Natàlia de la Oliva, Marie Palma, Elena del Corro, María del Pilar Bernicola, Elisa Rodríguez-Lucas, Thomas A. Gener, Jose Manuel de la Cruz, Miguel Torres-Miranda, Fikret Taygun Duvan, Nicola Ria, Justin Sperling, Sara Martí-Sánchez, Maria Chiara Spadaro, Clément Hébert, Sinead Savage, Jordi Arbiol, Anton Guimerà-Brunet, M. Victoria Puig, Blaise Yvert, Xavier Navarro, Kostas Kostarelos*, Jose A. Garrido*

One 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 cm−2). 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.