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NeuroRoots, a bio-inspired, seamless brain machine interface for long-term recording in delicate brain regions.
Ferro, Marc D; Proctor, Christopher M; Gonzalez, Alexander; Jayabal, Sriram; Zhao, Eric; Gagnon, Maxwell; Slézia, Andrea; Pas, Jolien; Dijk, Gerwin; Donahue, Mary J; Williamson, Adam; Raymond, Jennifer; Malliaras, George G; Giocomo, Lisa; Melosh, Nicholas A.
Affiliation
  • Ferro MD; Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA.
  • Proctor CM; Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom.
  • Gonzalez A; Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA.
  • Jayabal S; Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA.
  • Zhao E; Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA.
  • Gagnon M; Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA.
  • Slézia A; 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.
  • Pas J; Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, 13541 Gardanne, France.
  • Dijk G; Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, 13541 Gardanne, France.
  • Donahue MJ; Laboratory of Organic Electronics, Department of Science and Technology, Linköping University, Norrköping, 60221, Sweden.
  • Raymond J; Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA.
  • Malliaras GG; Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom.
  • Giocomo L; Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94304, USA.
  • Melosh NA; Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA.
AIP Adv ; 14(8): 085109, 2024 Aug.
Article de En | MEDLINE | ID: mdl-39130131
ABSTRACT
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.

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: AIP Adv Année: 2024 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: États-Unis d'Amérique

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: AIP Adv Année: 2024 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: États-Unis d'Amérique