Stimulus Driven Single Unit Activity From Micro-Electrocorticography.

action potential birdsong brain machine interface electrocorticogram neural interface

Journal

Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481

Informations de publication

Date de publication:
2020
Historique:
received: 02 09 2019
accepted: 14 01 2020
entrez: 18 3 2020
pubmed: 18 3 2020
medline: 18 3 2020
Statut: epublish

Résumé

High-fidelity measurements of neural activity can enable advancements in our understanding of the neural basis of complex behaviors such as speech, audition, and language, and are critical for developing neural prostheses that address impairments to these abilities due to disease or injury. We develop a novel high resolution, thin-film micro-electrocorticography (micro-ECoG) array that enables high-fidelity surface measurements of neural activity from songbirds, a well-established animal model for studying speech behavior. With this device, we provide the first demonstration of sensory-evoked modulation of surface-recorded single unit responses. We establish that single unit activity is consistently sensed from micro-ECoG electrodes over the surface of sensorimotor nucleus HVC (used as a proper name) in anesthetized European starlings, and validate responses with correlated firing in single units recorded simultaneously at surface and depth. The results establish a platform for high-fidelity recording from the surface of subcortical structures that will accelerate neurophysiological studies, and development of novel electrode arrays and neural prostheses.

Identifiants

pubmed: 32180695
doi: 10.3389/fnins.2020.00055
pmc: PMC7059620
doi:

Types de publication

Journal Article

Langues

eng

Pagination

55

Subventions

Organisme : NIDCD NIH HHS
ID : R01 DC018446
Pays : United States

Informations de copyright

Copyright © 2020 Hermiz, Hossain, Arneodo, Ganji, Rogers, Vahidi, Halgren, Gentner, Dayeh and Gilja.

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Auteurs

John Hermiz (J)

Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States.

Lorraine Hossain (L)

Department of Materials Science and Engineering, University of California, San Diego, La Jolla, CA, United States.

Ezequiel M Arneodo (EM)

Biocircuits Institute, University of California, San Diego, La Jolla, CA, United States.

Mehran Ganji (M)

Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States.

Nicholas Rogers (N)

Department of Physics, University of California, San Diego, La Jolla, CA, United States.

Nasim Vahidi (N)

Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States.

Eric Halgren (E)

Department of Radiology, University of California, San Diego, La Jolla, CA, United States.
Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States.

Timothy Q Gentner (TQ)

Department of Psychology, University of California, San Diego, La Jolla, CA, United States.
Kavli Institute for Brain and Mind, La Jolla, CA, United States.
Neurobiology Section, University of California, San Diego, La Jolla, CA, United States.

Shadi A Dayeh (SA)

Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States.
Department of Materials Science and Engineering, University of California, San Diego, La Jolla, CA, United States.
Department of Nanoengineering, University of California, San Diego, La Jolla, CA, United States.

Vikash Gilja (V)

Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States.

Classifications MeSH