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NeuroRoots, a bio-inspired, seamless Brain Machine Interface device for long-term recording

View ORCID ProfileMarc D. Ferro, Christopher M. Proctor, Alexander Gonzalez, Eric Zhao, Andrea Slezia, Jolien Pas, Gerwin Dijk, Mary J. Donahue, Adam Williamson, Georges G. Malliaras, Lisa Giocomo, Nicholas A. Melosh
doi: https://doi.org/10.1101/460949
Marc D. Ferro
1Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
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  • ORCID record for Marc D. Ferro
Christopher M. Proctor
3Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom
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Alexander Gonzalez
2Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
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Eric Zhao
1Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
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Andrea Slezia
4Aix Marseille Université, INS, UMR_S 1106, 13005 Marseille, France
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Jolien Pas
5Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, 13541 Gardanne, France
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Gerwin Dijk
5Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, 13541 Gardanne, France
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Mary J. Donahue
5Department of Bioelectronics, Ecole Nationale Supérieure des Mines, CMP-EMSE, 13541 Gardanne, France
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Adam Williamson
4Aix Marseille Université, INS, UMR_S 1106, 13005 Marseille, France
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Georges G. Malliaras
3Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom
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Lisa Giocomo
2Department of Neurobiology, Stanford University School of Medicine, Stanford, CA, USA
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Nicholas A. Melosh
1Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA
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  • For correspondence: nmelosh@stanford.edu
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Abstract

Minimally invasive electrodes of cellular scale that approach a bio-integrative level of neural recording could enable the development of scalable brain machine interfaces that stably interface with the same neural populations over long period of time.

In this paper, we designed and created NeuroRoots, a bio-mimetic multi-channel implant sharing similar dimension (10µm wide, 1.5µm thick), mechanical flexibility and spatial distribution as axon bundles in the brain. A simple approach of delivery is reported based on the assembly and controllable immobilization of the electrode onto a 35µm microwire shuttle by using capillarity and surface-tension in aqueous solution. Once implanted into targeted regions of the brain, the microwire was retracted leaving NeuroRoots in the biological tissue with minimal surgical footprint and perturbation of existing neural architectures within the tissue. NeuroRoots was implanted using a platform compatible with commercially available electrophysiology rigs and with measurements of interests in behavioral experiments in adult rats freely moving into maze. We demonstrated that NeuroRoots electrodes reliably detected action potentials for at least 7 weeks and the signal amplitude and shape remained relatively constant during long-term implantation.

This research represents a step forward in the direction of developing the next generation of seamless brain-machine interface to study and modulate the activities of specific sub-populations of neurons, and to develop therapies for a plethora of neurological diseases.

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Posted November 04, 2018.
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NeuroRoots, a bio-inspired, seamless Brain Machine Interface device for long-term recording
Marc D. Ferro, Christopher M. Proctor, Alexander Gonzalez, Eric Zhao, Andrea Slezia, Jolien Pas, Gerwin Dijk, Mary J. Donahue, Adam Williamson, Georges G. Malliaras, Lisa Giocomo, Nicholas A. Melosh
bioRxiv 460949; doi: https://doi.org/10.1101/460949
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NeuroRoots, a bio-inspired, seamless Brain Machine Interface device for long-term recording
Marc D. Ferro, Christopher M. Proctor, Alexander Gonzalez, Eric Zhao, Andrea Slezia, Jolien Pas, Gerwin Dijk, Mary J. Donahue, Adam Williamson, Georges G. Malliaras, Lisa Giocomo, Nicholas A. Melosh
bioRxiv 460949; doi: https://doi.org/10.1101/460949

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