Direction of information flow in large-scale resting-state networks is frequency-dependent

Arjan Hillebrand, Prejaas Tewarie, Edwin van Dellen, Meichen Yu, Ellen W. S. Carbo, Linda Douw, Alida A. Gouw, Elisabeth C. W. van Straaten, Cornelis J. Stam

Research output: Contribution to journalArticleAcademicpeer-review

220 Citations (Scopus)

Abstract

Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow.
Original languageEnglish
Pages (from-to)3867-3872
JournalPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume113
Issue number14
DOIs
Publication statusPublished - 5 Apr 2016

Keywords

  • atlas-based beamforming
  • information flow
  • magnetoencephalography
  • phase transfer entropy
  • resting-state networks

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