Literature DB >> 33276088

Resting-state EEG Dynamics Reveals Differences in Network Organization and its Fluctuation between Frequency Bands.

Nicolas Zink1, Moritz Mückschel2, Christian Beste2.   

Abstract

Functional connectivity in EEG resting-state is not stable but fluctuates considerably. The aim of this study was to investigate how efficient information flows through a network, i.e. how resting-state EEG networks are organized and whether this organization it also subject to fluctuations. Differences of the network organization (small-worldness), degree of clustered connectivity, and path length as an indicator of how information is integrated into the network across time was compared between theta, alpha and beta bands. We show robust differences in network organization (small-worldness) between frequency bands. Fluctuations in network organization were larger in the theta, compared to the alpha and beta frequency. Variation in network organization and not the frequency of fluctuations differs between frequency bands. Furthermore, the degree of clustered connectivity and its modulation across time is the same across frequency bands, but the path length revealed the same modulatory pattern as the small-world metric. It is therefore the interplay of local processing efficiency and global information processing efficiency in the brain that fluctuates in a frequency-specific way. Properties of how information can be integrated is subject to fluctuations in a frequency-specific way in the resting-state. The possible relevance of these resting-state EEG properties is discussed including its clinical relevance.
Copyright © 2020 IBRO. Published by Elsevier Ltd. All rights reserved.

Keywords:  EEG; alpha; beta; connectivity; networks; theta

Mesh:

Year:  2020        PMID: 33276088     DOI: 10.1016/j.neuroscience.2020.11.037

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


  3 in total

1.  Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm.

Authors:  Hongli Yu; Sidi Ba; Yuxue Guo; Lei Guo; Guizhi Xu
Journal:  Brain Sci       Date:  2022-01-30

2.  A Novel Approach for Segment-Length Selection Based on Stationarity to Perform Effective Connectivity Analysis Applied to Resting-State EEG Signals.

Authors:  Leonardo Góngora; Alessia Paglialonga; Alfonso Mastropietro; Giovanna Rizzo; Riccardo Barbieri
Journal:  Sensors (Basel)       Date:  2022-06-23       Impact factor: 3.847

3.  An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States.

Authors:  Dalton J Edwards; Logan T Trujillo
Journal:  Brain Sci       Date:  2021-03-05
  3 in total

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