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Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity

Authors :
European Commission
Agencia Estatal de Investigación (España)
La Caixa
Ministerio de Ciencia, Innovación y Universidades (España)
Universidad Autónoma de Barcelona
Garcia Cortadella, Ramon
Schwesig, Gerrit
Jeschke, Christoph
Illa, Xavi
Gray, Anna L.
Savage, Sinead
Stamatidou, E.
Schiessl, I.
Masvidal Codina, Eduard
Kostarelos, Kostas
Guimerà-Brunet, Anton
Sirota, Anton
Garrido, Jose A.
European Commission
Agencia Estatal de Investigación (España)
La Caixa
Ministerio de Ciencia, Innovación y Universidades (España)
Universidad Autónoma de Barcelona
Garcia Cortadella, Ramon
Schwesig, Gerrit
Jeschke, Christoph
Illa, Xavi
Gray, Anna L.
Savage, Sinead
Stamatidou, E.
Schiessl, I.
Masvidal Codina, Eduard
Kostarelos, Kostas
Guimerà-Brunet, Anton
Sirota, Anton
Garrido, Jose A.
Publication Year :
2021

Abstract

Graphene active sensors have demonstrated promising capabilities for the detection of electrophysiological signals in the brain. Their functional properties, together with their flexibility as well as their expected stability and biocompatibility have raised them as a promising building block for large-scale sensing neural interfaces. However, in order to provide reliable tools for neuroscience and biomedical engineering applications, the maturity of this technology must be thoroughly studied. Here, we evaluate the performance of 64-channel graphene sensor arrays in terms of homogeneity, sensitivity and stability using a wireless, quasi-commercial headstage and demonstrate the biocompatibility of epicortical graphene chronic implants. Furthermore, to illustrate the potential of the technology to detect cortical signals from infra-slow to high-gamma frequency bands, we perform proof-of-concept long-term wireless recording in a freely behaving rodent. Our work demonstrates the maturity of the graphene-based technology, which represents a promising candidate for chronic, wide frequency band neural sensing interfaces.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1306020074
Document Type :
Electronic Resource