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Neural Cross-Frequency Coupling Functions in Sleep

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Neural Cross-Frequency Coupling Functions in Sleep. / Manasova, Dragana; Stankovski, Tomislav.
In: Neuroscience, Vol. 523, 15.07.2023, p. 20-30.

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Manasova D, Stankovski T. Neural Cross-Frequency Coupling Functions in Sleep. Neuroscience. 2023 Jul 15;523:20-30. Epub 2023 May 22. doi: 10.1016/j.neuroscience.2023.05.016

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Manasova, Dragana ; Stankovski, Tomislav. / Neural Cross-Frequency Coupling Functions in Sleep. In: Neuroscience. 2023 ; Vol. 523. pp. 20-30.

Bibtex

@article{9286c985ab9c4891b096573ff8c144b4,
title = "Neural Cross-Frequency Coupling Functions in Sleep",
abstract = "The human brain presents a heavily connected complex system. From a relatively fixed anatomy, it can enable a vast repertoire of functions. One important brain function is the process of natural sleep, which alters consciousness and voluntary muscle activity. On neural level, these alterations are accompanied by changes of the brain connectivity. In order to reveal the changes of connectivity associated with sleep, we present a methodological framework for reconstruction and assessment of functional interaction mechanisms. By analyzing EEG (electroencephalogram) recordings from human whole night sleep, first, we applied a time-frequency wavelet transform to study the existence and strength of brainwave oscillations. Then we applied a dynamical Bayesian inference on the phase dynamics in the presence of noise. With this method we reconstructed the cross-frequency coupling functions, which revealed the mechanism of how the interactions occur and manifest. We focus our analysis on the delta-alpha coupling function and observe how this cross-frequency coupling changes during the different sleep stages. The results demonstrated that the delta-alpha coupling function was increasing gradually from Awake to NREM3 (non-rapid eye movement), but only during NREM2 and NREM3 deep sleep it was significant in respect of surrogate data testing. The analysis on the spatially distributed connections showed that this significance is strong only for within the single electrode region and in the front-to-back direction. The presented methodological framework is for the whole-night sleep recordings, but it also carries general implications for other global neural states.",
keywords = "Bayesian inference, EEG, sleep, coupling function, brainwaves, cross-frequency coupling",
author = "Dragana Manasova and Tomislav Stankovski",
year = "2023",
month = jul,
day = "15",
doi = "10.1016/j.neuroscience.2023.05.016",
language = "English",
volume = "523",
pages = "20--30",
journal = "Neuroscience",
issn = "1873-7544",

}

RIS

TY - JOUR

T1 - Neural Cross-Frequency Coupling Functions in Sleep

AU - Manasova, Dragana

AU - Stankovski, Tomislav

PY - 2023/7/15

Y1 - 2023/7/15

N2 - The human brain presents a heavily connected complex system. From a relatively fixed anatomy, it can enable a vast repertoire of functions. One important brain function is the process of natural sleep, which alters consciousness and voluntary muscle activity. On neural level, these alterations are accompanied by changes of the brain connectivity. In order to reveal the changes of connectivity associated with sleep, we present a methodological framework for reconstruction and assessment of functional interaction mechanisms. By analyzing EEG (electroencephalogram) recordings from human whole night sleep, first, we applied a time-frequency wavelet transform to study the existence and strength of brainwave oscillations. Then we applied a dynamical Bayesian inference on the phase dynamics in the presence of noise. With this method we reconstructed the cross-frequency coupling functions, which revealed the mechanism of how the interactions occur and manifest. We focus our analysis on the delta-alpha coupling function and observe how this cross-frequency coupling changes during the different sleep stages. The results demonstrated that the delta-alpha coupling function was increasing gradually from Awake to NREM3 (non-rapid eye movement), but only during NREM2 and NREM3 deep sleep it was significant in respect of surrogate data testing. The analysis on the spatially distributed connections showed that this significance is strong only for within the single electrode region and in the front-to-back direction. The presented methodological framework is for the whole-night sleep recordings, but it also carries general implications for other global neural states.

AB - The human brain presents a heavily connected complex system. From a relatively fixed anatomy, it can enable a vast repertoire of functions. One important brain function is the process of natural sleep, which alters consciousness and voluntary muscle activity. On neural level, these alterations are accompanied by changes of the brain connectivity. In order to reveal the changes of connectivity associated with sleep, we present a methodological framework for reconstruction and assessment of functional interaction mechanisms. By analyzing EEG (electroencephalogram) recordings from human whole night sleep, first, we applied a time-frequency wavelet transform to study the existence and strength of brainwave oscillations. Then we applied a dynamical Bayesian inference on the phase dynamics in the presence of noise. With this method we reconstructed the cross-frequency coupling functions, which revealed the mechanism of how the interactions occur and manifest. We focus our analysis on the delta-alpha coupling function and observe how this cross-frequency coupling changes during the different sleep stages. The results demonstrated that the delta-alpha coupling function was increasing gradually from Awake to NREM3 (non-rapid eye movement), but only during NREM2 and NREM3 deep sleep it was significant in respect of surrogate data testing. The analysis on the spatially distributed connections showed that this significance is strong only for within the single electrode region and in the front-to-back direction. The presented methodological framework is for the whole-night sleep recordings, but it also carries general implications for other global neural states.

KW - Bayesian inference

KW - EEG

KW - sleep

KW - coupling function

KW - brainwaves

KW - cross-frequency coupling

U2 - 10.1016/j.neuroscience.2023.05.016

DO - 10.1016/j.neuroscience.2023.05.016

M3 - Journal article

C2 - 37225051

VL - 523

SP - 20

EP - 30

JO - Neuroscience

JF - Neuroscience

SN - 1873-7544

ER -