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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
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    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.

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