Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging

Aging and poor sleep quality are associated with altered brain dynamics, yet current electroencephalography (EEG) analyses often overlook regional complexity. This study addresses this gap by introducing a novel integration of intra- and inter-regional complexity analysis using multivariate multisca...

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Main Authors: Ahmad Zandbagleh, Saeid Sanei, Lucía Penalba-Sánchez, Pedro Miguel Rodrigues, Mark Crook-Rumsey, Hamed Azami
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Biosensors
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Online Access:https://www.mdpi.com/2079-6374/15/4/240
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author Ahmad Zandbagleh
Saeid Sanei
Lucía Penalba-Sánchez
Pedro Miguel Rodrigues
Mark Crook-Rumsey
Hamed Azami
author_facet Ahmad Zandbagleh
Saeid Sanei
Lucía Penalba-Sánchez
Pedro Miguel Rodrigues
Mark Crook-Rumsey
Hamed Azami
author_sort Ahmad Zandbagleh
collection DOAJ
description Aging and poor sleep quality are associated with altered brain dynamics, yet current electroencephalography (EEG) analyses often overlook regional complexity. This study addresses this gap by introducing a novel integration of intra- and inter-regional complexity analysis using multivariate multiscale dispersion entropy (mvMDE) from awake resting-state EEG for the first time. Moreover, assessing both intra- and inter-regional complexity provides a comprehensive perspective on the dynamic interplay between localized neural activity and its coordination across brain regions, which is essential for understanding the neural substrates of aging and sleep quality. Data from 58 participants—24 young adults (mean age = 24.7 ± 3.4) and 34 older adults (mean age = 72.9 ± 4.2)—were analyzed, with each age group further divided based on Pittsburgh Sleep Quality Index (PSQI) scores. To capture inter-regional complexity, mvMDE was applied to the most informative group of sensors, with one sensor selected from each brain region using four methods: highest average correlation, highest entropy, highest mutual information, and highest principal component loading. This targeted approach reduced computational cost and enhanced the effect sizes (ESs), particularly at large scale factors (e.g., 25) linked to delta-band activity, with the PCA-based method achieving the highest ESs (1.043 for sleep quality in older adults). Overall, we expect that both inter- and intra-regional complexity will play a pivotal role in elucidating neural mechanisms as captured by various physiological data modalities—such as EEG, magnetoencephalography, and magnetic resonance imaging—thereby offering promising insights for a range of biomedical applications.
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spelling doaj-art-eadef70df5894236a27875178b68f2cc2025-08-20T03:14:27ZengMDPI AGBiosensors2079-63742025-04-0115424010.3390/bios15040240Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and AgingAhmad Zandbagleh0Saeid Sanei1Lucía Penalba-Sánchez2Pedro Miguel Rodrigues3Mark Crook-Rumsey4Hamed Azami5School of Electrical Engineering, Iran University of Science and Technology, Tehran 1684613114, IranElectrical and Electronic Engineering Department, Imperial College London, London SW7 2AZ, UKInstitute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke-University Magdeburg (OVGU), 39120 Magdeburg, GermanyCentro de Biotecnologia e Química Fina (CBQF)—Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, 4169-005 Porto, PortugalUK Dementia Research Institute (UK DRI), Centre for Care Research and Technology, Imperial College London, London W1T 7NF, UKCentre for Addiction and Mental Health, University of Toronto, Toronto, ON M6J 1H1, CanadaAging and poor sleep quality are associated with altered brain dynamics, yet current electroencephalography (EEG) analyses often overlook regional complexity. This study addresses this gap by introducing a novel integration of intra- and inter-regional complexity analysis using multivariate multiscale dispersion entropy (mvMDE) from awake resting-state EEG for the first time. Moreover, assessing both intra- and inter-regional complexity provides a comprehensive perspective on the dynamic interplay between localized neural activity and its coordination across brain regions, which is essential for understanding the neural substrates of aging and sleep quality. Data from 58 participants—24 young adults (mean age = 24.7 ± 3.4) and 34 older adults (mean age = 72.9 ± 4.2)—were analyzed, with each age group further divided based on Pittsburgh Sleep Quality Index (PSQI) scores. To capture inter-regional complexity, mvMDE was applied to the most informative group of sensors, with one sensor selected from each brain region using four methods: highest average correlation, highest entropy, highest mutual information, and highest principal component loading. This targeted approach reduced computational cost and enhanced the effect sizes (ESs), particularly at large scale factors (e.g., 25) linked to delta-band activity, with the PCA-based method achieving the highest ESs (1.043 for sleep quality in older adults). Overall, we expect that both inter- and intra-regional complexity will play a pivotal role in elucidating neural mechanisms as captured by various physiological data modalities—such as EEG, magnetoencephalography, and magnetic resonance imaging—thereby offering promising insights for a range of biomedical applications.https://www.mdpi.com/2079-6374/15/4/240agingEEGmachine learningmultivariate multiscale dispersion entropysleep quality
spellingShingle Ahmad Zandbagleh
Saeid Sanei
Lucía Penalba-Sánchez
Pedro Miguel Rodrigues
Mark Crook-Rumsey
Hamed Azami
Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging
Biosensors
aging
EEG
machine learning
multivariate multiscale dispersion entropy
sleep quality
title Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging
title_full Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging
title_fullStr Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging
title_full_unstemmed Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging
title_short Intra- and Inter-Regional Complexity in Multi-Channel Awake EEG Through Multivariate Multiscale Dispersion Entropy for Assessing Sleep Quality and Aging
title_sort intra and inter regional complexity in multi channel awake eeg through multivariate multiscale dispersion entropy for assessing sleep quality and aging
topic aging
EEG
machine learning
multivariate multiscale dispersion entropy
sleep quality
url https://www.mdpi.com/2079-6374/15/4/240
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