IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v12y2021i1d10.1038_s41467-020-20546-w.html
   My bibliography  Save this article

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

Author

Listed:
  • R. Garcia-Cortadella

    (Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra)

  • G. Schwesig

    (Ludwig-Maximilians Universität München)

  • C. Jeschke

    (Multi Channel Systems (MCS) GmbH)

  • X. Illa

    (Instituto de Microelectrónica de Barcelona, IMB-CNM (CSIC), Esfera UAB
    Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN))

  • Anna L. Gray

    (Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester)

  • S. Savage

    (Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester)

  • E. Stamatidou

    (Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester)

  • I. Schiessl

    (Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester)

  • E. Masvidal-Codina

    (Instituto de Microelectrónica de Barcelona, IMB-CNM (CSIC), Esfera UAB
    Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN))

  • K. Kostarelos

    (Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra
    Nanomedicine Lab, National Graphene Institute and Faculty of Biology, Medicine & Health, University of Manchester)

  • A. Guimerà-Brunet

    (Instituto de Microelectrónica de Barcelona, IMB-CNM (CSIC), Esfera UAB
    Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN))

  • A. Sirota

    (Ludwig-Maximilians Universität München)

  • J. A. Garrido

    (Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra
    ICREA, Pg. Lluís Companys 23)

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.

Suggested Citation

  • R. Garcia-Cortadella & G. Schwesig & C. Jeschke & X. Illa & Anna L. Gray & S. Savage & E. Stamatidou & I. Schiessl & E. Masvidal-Codina & K. Kostarelos & A. Guimerà-Brunet & A. Sirota & J. A. Garrido, 2021. "Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity," Nature Communications, Nature, vol. 12(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20546-w
    DOI: 10.1038/s41467-020-20546-w
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-20546-w
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-020-20546-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hongyan Gao & Zhien Wang & Feiyu Yang & Xiaoyu Wang & Siqi Wang & Quan Zhang & Xiaomeng Liu & Yubing Sun & Jing Kong & Jun Yao, 2024. "Graphene-integrated mesh electronics with converged multifunctionality for tracking multimodal excitation-contraction dynamics in cardiac microtissues," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20546-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.