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Combination of Group Singular Value Decomposition and eLORETA Identifies Human EEG Networks and Responses to Transcranial Photobiomodulation

Wang, Xinlong ; Wanniarachchi, Hashini ; Wu, Anqi ; Liu, Hanli

Frontiers in human neuroscience, 2022-05, Vol.16, p.853909-853909 [Revista revisada por pares]

Switzerland: Frontiers Research Foundation

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  • Título:
    Combination of Group Singular Value Decomposition and eLORETA Identifies Human EEG Networks and Responses to Transcranial Photobiomodulation
  • Autor: Wang, Xinlong ; Wanniarachchi, Hashini ; Wu, Anqi ; Liu, Hanli
  • Materias: Brain ; Brain mapping ; Cognition ; Cognition & reasoning ; Data analysis ; Decomposition ; default mode network ; Dementia ; EEG ; Electroencephalography ; eLORETA ; Enzymes ; executive control network ; Executive function ; Experiments ; frontal parietal network ; Functional magnetic resonance imaging ; Human Neuroscience ; Human subjects ; Localization ; Metabolism ; Signal processing ; singular value decomposition ; Theta rhythms ; transcranial photobiomodulation
  • Es parte de: Frontiers in human neuroscience, 2022-05, Vol.16, p.853909-853909
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
    Edited by: F. Gonzalez-Lima, University of Texas at Austin, United States
    This article was submitted to Brain Imaging and Stimulation, a section of the journal Frontiers in Human Neuroscience
    Reviewed by: Yingchun Zhang, University of Houston, United States; Ali Jahan, Tabriz University of Medical Sciences, Iran
  • Descripción: Transcranial Photobiomodulation (tPBM) has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram (EEG) networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm . In data processing, a novel methodology by combining group singular value decomposition (gSVD) with the exact low-resolution brain electromagnetic tomography (eLORETA) was implemented and performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components (PCs) projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band (delta, theta, alpha, beta and gamma) were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes.
  • Editor: Switzerland: Frontiers Research Foundation
  • Idioma: Inglés
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