NeuroRoots, a bio-inspired, seamless brain machine interface for long-term recording in delicate brain regions
Marc D. Ferro,
Christopher M. Proctor,
Alexander Gonzalez,
Sriram Jayabal,
Eric Zhao,
Maxwell Gagnon,
Andrea Slézia,
Jolien Pas,
Gerwin Dijk,
Mary J. Donahue,
Adam Williamson,
Jennifer Raymond,
George G. Malliaras,
Lisa Giocomo,
Nicholas A. Melosh
Affiliations
Marc D. Ferro
Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
Christopher M. Proctor
Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom
Alexander Gonzalez
Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA
Sriram Jayabal
Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA
Eric Zhao
Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
Maxwell Gagnon
Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA
Andrea Slézia
Multimodal Neurotechnology Group, Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Hungarian Research Network, 1117 Budapest, Magyar tudósok körútja 2., Hungary
Jolien Pas
Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, 13541 Gardanne, France
Gerwin Dijk
Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, 13541 Gardanne, France
Mary J. Donahue
Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, Norrköping, 60221, Sweden
Adam Williamson
International Clinical Research Center, ICRC, St. Anne’s University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
Jennifer Raymond
Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA
George G. Malliaras
Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom
Lisa Giocomo
Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA
Nicholas A. Melosh
Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA
Scalable electronic brain implants with long-term stability and low biological perturbation are crucial technologies for high-quality brain–machine interfaces that can seamlessly access delicate and hard-to-reach regions of the brain. Here, we created “NeuroRoots,” a biomimetic multi-channel implant with similar dimensions (7 μm wide and 1.5 μm thick), mechanical compliance, and spatial distribution as axons in the brain. Unlike planar shank implants, these devices consist of a number of individual electrode “roots,” each tendril independent from the other. A simple microscale delivery approach based on commercially available apparatus minimally perturbs existing neural architectures during surgery. NeuroRoots enables high density single unit recording from the cerebellum in vitro and in vivo. NeuroRoots also reliably recorded action potentials in various brain regions for at least 7 weeks during behavioral experiments in freely-moving rats, without adjustment of electrode position. This minimally invasive axon-like implant design is an important step toward improving the integration and stability of brain–machine interfacing.
