IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-019-14166-2.html
   My bibliography  Save this article

Electrophysiological dynamics of antagonistic brain networks reflect attentional fluctuations

Author

Listed:
  • Aaron Kucyi

    (Stanford University)

  • Amy Daitch

    (Stanford University)

  • Omri Raccah

    (Stanford University)

  • Baotian Zhao

    (Beijing Tiantan Hospital
    Capital Medical University)

  • Chao Zhang

    (Beijing Tiantan Hospital
    Capital Medical University)

  • Michael Esterman

    (Veterans Administration, Boston Healthcare System
    Boston University School of Medicine)

  • Michael Zeineh

    (Stanford University)

  • Casey H. Halpern

    (Stanford University)

  • Kai Zhang

    (Beijing Tiantan Hospital
    Capital Medical University)

  • Jianguo Zhang

    (Beijing Tiantan Hospital
    Capital Medical University)

  • Josef Parvizi

    (Stanford University)

Abstract

Neuroimaging evidence suggests that the default mode network (DMN) exhibits antagonistic activity with dorsal attention (DAN) and salience (SN) networks. Here we use human intracranial electroencephalography to investigate the behavioral relevance of fine-grained dynamics within and between these networks. The three networks show dissociable profiles of task-evoked electrophysiological activity, best captured in the high-frequency broadband (HFB; 70–170 Hz) range. On the order of hundreds of milliseconds, HFB responses peak fastest in the DAN, at intermediate speed in the SN, and slowest in the DMN. Lapses of attention (behavioral errors) are marked by distinguishable patterns of both pre- and post-stimulus HFB activity within each network. Moreover, the magnitude of temporally lagged, negative HFB coupling between the DAN and DMN (but not SN and DMN) is associated with greater sustained attention performance and is reduced during wakeful rest. These findings underscore the behavioral relevance of temporally delayed coordination between antagonistic brain networks.

Suggested Citation

  • Aaron Kucyi & Amy Daitch & Omri Raccah & Baotian Zhao & Chao Zhang & Michael Esterman & Michael Zeineh & Casey H. Halpern & Kai Zhang & Jianguo Zhang & Josef Parvizi, 2020. "Electrophysiological dynamics of antagonistic brain networks reflect attentional fluctuations," Nature Communications, Nature, vol. 11(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-019-14166-2
    DOI: 10.1038/s41467-019-14166-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-14166-2
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-019-14166-2?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. Macauley Smith Breault & Pierre Sacré & Zachary B. Fitzgerald & John T. Gale & Kathleen E. Cullen & Jorge A. González-Martínez & Sridevi V. Sarma, 2023. "Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    2. Huixin Tan & Xiaoyu Zeng & Jun Ni & Kun Liang & Cuiping Xu & Yanyang Zhang & Jiaxin Wang & Zizhou Li & Jiaxin Yang & Chunlei Han & Yuan Gao & Xinguang Yu & Shihui Han & Fangang Meng & Yina Ma, 2024. "Intracranial EEG signals disentangle multi-areal neural dynamics of vicarious pain perception," Nature Communications, Nature, vol. 15(1), pages 1-18, 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:11:y:2020:i:1:d:10.1038_s41467-019-14166-2. 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.