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

  • External authors:
  • R. Garcia-Cortadella
  • G. Schwesig
  • C. Jeschke
  • X. Illa
  • Anna L. Gray
  • E. Stamatidou
  • E. Masvidal-Codina
  • A. Guimerà-Brunet
  • A. Sirota
  • J. A. Garrido

Standard

Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity. / Garcia-Cortadella, R.; Schwesig, G.; Jeschke, C.; Illa, X.; Gray, Anna L.; Savage, S.; Stamatidou, E.; Schiessl, I.; Masvidal-Codina, E.; Kostarelos, K.; Guimerà-Brunet, A.; Sirota, A.; Garrido, J. A.

In: Nature Communications, Vol. 12, No. 1, 211, 11.01.2021.

Research output: Contribution to journalArticlepeer-review

Harvard

Garcia-Cortadella, R, Schwesig, G, Jeschke, C, Illa, X, Gray, AL, Savage, S, Stamatidou, E, Schiessl, I, Masvidal-Codina, E, Kostarelos, K, Guimerà-Brunet, A, Sirota, A & Garrido, JA 2021, 'Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity', Nature Communications, vol. 12, no. 1, 211. https://doi.org/10.1038/s41467-020-20546-w

APA

Garcia-Cortadella, R., Schwesig, G., Jeschke, C., Illa, X., Gray, A. L., Savage, S., Stamatidou, E., Schiessl, I., Masvidal-Codina, E., Kostarelos, K., Guimerà-Brunet, A., Sirota, A., & Garrido, J. A. (2021). Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity. Nature Communications, 12(1), [211]. https://doi.org/10.1038/s41467-020-20546-w

Vancouver

Garcia-Cortadella R, Schwesig G, Jeschke C, Illa X, Gray AL, Savage S et al. Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity. Nature Communications. 2021 Jan 11;12(1). 211. https://doi.org/10.1038/s41467-020-20546-w

Author

Garcia-Cortadella, R. ; Schwesig, G. ; Jeschke, C. ; Illa, X. ; Gray, Anna L. ; Savage, S. ; Stamatidou, E. ; Schiessl, I. ; Masvidal-Codina, E. ; Kostarelos, K. ; Guimerà-Brunet, A. ; Sirota, A. ; Garrido, J. A. / Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity. In: Nature Communications. 2021 ; Vol. 12, No. 1.

Bibtex

@article{438b9477566b452896ede23dfbacddca,
title = "Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity",
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.",
keywords = "Animals, Behavior, Animal, Brain/physiology, Gamma Rhythm/physiology, Graphite/chemistry, Materials Testing, Rats, Long-Evans, Signal Processing, Computer-Assisted, Sleep/physiology, Time Factors, Transistors, Electronic, Wireless Technology",
author = "R. Garcia-Cortadella and G. Schwesig and C. Jeschke and X. Illa and Gray, {Anna L.} and S. Savage and E. Stamatidou and I. Schiessl and E. Masvidal-Codina and K. Kostarelos and A. Guimer{\`a}-Brunet and A. Sirota and Garrido, {J. A.}",
note = "Funding Information: This work has been funded by the European Union{\textquoteright}s Horizon 2020 research and innovation program under Grant Agreement No. 732032 (BrainCom) and Grant Agreement No. 696656 and 785219 (Graphene Flagship). The ICN2 is supported by the Severo Ochoa Centres of Excellence program, funded by the Spanish Research Agency (AEI, grant no. SEV-2017-0706), and by the CERCA Program/Generalitat de Catalunya. R.G.C. is supported by the International Ph.D Program La Caixa-Severo Ochoa (Pro-grama Internacional de Becas “la Caixa”-Severo Ochoa). This work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS “NANBIOSIS”, more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN) at the IMB-CNM. This work is within the project FIS2017-85787-R funded by the “Ministerio de Ciencia, Innovaci{\'o}n y Universidades” of Spain, the “Agencia Estatal de Investigaci{\'o}n (AEI)”, and the “Fondo Europeo de Desarrollo Regional (FEDER/UE)”. A.S. and G.S. were also supported by Bundesministerium f{\"u}r Bildung und Forschung [grant number 01GQ0440]. R.G.C. acknowledges that this work has been done in the framework of the Ph.D in Electrical and Telecommunication Engineering at the Universitat Aut{\`o}noma de Barcelona. We thank Eduardo Blanco Hern{\'a}ndez for assistance with the preprocessing of the motion tracking data. Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = jan,
day = "11",
doi = "10.1038/s41467-020-20546-w",
language = "English",
volume = "12",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Springer Nature",
number = "1",

}

RIS

TY - JOUR

T1 - Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity

AU - Garcia-Cortadella, R.

AU - Schwesig, G.

AU - Jeschke, C.

AU - Illa, X.

AU - Gray, Anna L.

AU - Savage, S.

AU - Stamatidou, E.

AU - Schiessl, I.

AU - Masvidal-Codina, E.

AU - Kostarelos, K.

AU - Guimerà-Brunet, A.

AU - Sirota, A.

AU - Garrido, J. A.

N1 - Funding Information: This work has been funded by the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 732032 (BrainCom) and Grant Agreement No. 696656 and 785219 (Graphene Flagship). The ICN2 is supported by the Severo Ochoa Centres of Excellence program, funded by the Spanish Research Agency (AEI, grant no. SEV-2017-0706), and by the CERCA Program/Generalitat de Catalunya. R.G.C. is supported by the International Ph.D Program La Caixa-Severo Ochoa (Pro-grama Internacional de Becas “la Caixa”-Severo Ochoa). This work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS “NANBIOSIS”, more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN) at the IMB-CNM. This work is within the project FIS2017-85787-R funded by the “Ministerio de Ciencia, Innovación y Universidades” of Spain, the “Agencia Estatal de Investigación (AEI)”, and the “Fondo Europeo de Desarrollo Regional (FEDER/UE)”. A.S. and G.S. were also supported by Bundesministerium für Bildung und Forschung [grant number 01GQ0440]. R.G.C. acknowledges that this work has been done in the framework of the Ph.D in Electrical and Telecommunication Engineering at the Universitat Autònoma de Barcelona. We thank Eduardo Blanco Hernández for assistance with the preprocessing of the motion tracking data. Publisher Copyright: © 2021, The Author(s).

PY - 2021/1/11

Y1 - 2021/1/11

N2 - 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.

AB - 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.

KW - Animals

KW - Behavior, Animal

KW - Brain/physiology

KW - Gamma Rhythm/physiology

KW - Graphite/chemistry

KW - Materials Testing

KW - Rats, Long-Evans

KW - Signal Processing, Computer-Assisted

KW - Sleep/physiology

KW - Time Factors

KW - Transistors, Electronic

KW - Wireless Technology

U2 - 10.1038/s41467-020-20546-w

DO - 10.1038/s41467-020-20546-w

M3 - Article

C2 - 33431878

VL - 12

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

IS - 1

M1 - 211

ER -