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Article

Universal Lifespan Trajectories of Source-Space Information Flow Extracted from Resting-State MEG Data

by
Stavros I. Dimitriadis
1,2,3,4,5,6,7,8
1
Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road, Cardiff CF24 4HQ, Wales, UK
2
Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road, Cardiff CF24 HQ, Wales, UK
3
MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Maindy Road, Cardiff CF24 4HQ, Wales, UK
4
Neuroinformatics Group, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road, Cardiff CF24 4HQ, Wales, UK
5
MRC Integrative Epidemiology Unit (IEU), University of Bristol, Queens Road, Bristol BS8 1QU, Wales, UK
6
Department of Clinical Psychology and Psychobiology, Faculty of Psychology, University of Barcelona, Passeig de la Vall d’Hebron, 171, 08035 Barcelona, Spain
7
Institut de Neurociències, University of Barcelona, Campus Mundet, Edifici de Ponent, Passeig de la Vall d’Hebron, 171, 08035 Barcelona, Spain
8
Integrative Neuroimaging Lab, 55133 Thessaloniki, Macedonia, Greece
Brain Sci. 2022, 12(10), 1404; https://doi.org/10.3390/brainsci12101404
Submission received: 4 May 2022 / Revised: 15 July 2022 / Accepted: 22 July 2022 / Published: 18 October 2022
(This article belongs to the Special Issue Human Brain Dynamics: Latest Advances and Prospects—2nd Edition)

Abstract

Source activity was extracted from resting-state magnetoencephalography data of 103 subjects aged 18–60 years. The directionality of information flow was computed from the regional time courses using delay symbolic transfer entropy and phase entropy. The analysis yielded a dynamic source connectivity profile, disentangling the direction, strength, and time delay of the underlying causal interactions, producing independent time delays for cross-frequency amplitude-to-amplitude and phase-to-phase coupling. The computation of the dominant intrinsic coupling mode (DoCM) allowed me to estimate the probability distribution of the DoCM independently of phase and amplitude. The results support earlier observations of a posterior-to-anterior information flow for phase dynamics in {α1, α2, β, γ} and an opposite flow (anterior to posterior) in θ. Amplitude dynamics reveal posterior-to-anterior information flow in {α1, α2, γ}, a sensory-motor β-oriented pattern, and an anterior-to-posterior pattern in {δ, θ}. The DoCM between intra- and cross-frequency couplings (CFC) are reported here for the first time and independently for amplitude and phase; in both domains {δ, θ, α1}, frequencies are the main contributors to DoCM. Finally, a novel brain age index (BAI) is introduced, defined as the ratio of the probability distribution of inter- over intra-frequency couplings. This ratio shows a universal age trajectory: a rapid rise from the end of adolescence, reaching a peak in adulthood, and declining slowly thereafter. The universal pattern is seen in the BAI of each frequency studied and for both amplitude and phase domains. No such universal age dependence was previously reported.
Keywords: magnetoencephalography; resting state; information flow; symbolic transfer entropy; atlas-based source localization; development; intrinsic coupling modes; universal brain age index magnetoencephalography; resting state; information flow; symbolic transfer entropy; atlas-based source localization; development; intrinsic coupling modes; universal brain age index

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MDPI and ACS Style

Dimitriadis, S.I. Universal Lifespan Trajectories of Source-Space Information Flow Extracted from Resting-State MEG Data. Brain Sci. 2022, 12, 1404. https://doi.org/10.3390/brainsci12101404

AMA Style

Dimitriadis SI. Universal Lifespan Trajectories of Source-Space Information Flow Extracted from Resting-State MEG Data. Brain Sciences. 2022; 12(10):1404. https://doi.org/10.3390/brainsci12101404

Chicago/Turabian Style

Dimitriadis, Stavros I. 2022. "Universal Lifespan Trajectories of Source-Space Information Flow Extracted from Resting-State MEG Data" Brain Sciences 12, no. 10: 1404. https://doi.org/10.3390/brainsci12101404

APA Style

Dimitriadis, S. I. (2022). Universal Lifespan Trajectories of Source-Space Information Flow Extracted from Resting-State MEG Data. Brain Sciences, 12(10), 1404. https://doi.org/10.3390/brainsci12101404

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