The part and the whole: how single nodes contribute to large-scale phase-locking in functional EEG networks.
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BORIS DOI
Publisher DOI
PubMed ID
39406673
Description
Objective
The application of signal analysis techniques to electroencephalographic (EEG) recordings from epilepsy patients shows that epilepsy involves not only altered neuronal synchronization but also the reorganization of functional EEG networks. This study aims to assess the large-scale phase-locking of such functional networks and how individual network nodes contribute to this collective dynamics.Methods
We analyze the EEG recorded before, during and after seizures from sixteen patients with pharmacoresistant focal-onset epilepsy. The data is filtered to low (4-30 Hz) and high (80-150 Hz) frequencies. We define the multivariate phase-locking measure and the univariate phase-locking contribution measure. Surrogate signals are used to estimate baseline results expected under the null hypothesis that the EEG is a correlated linear stochastic process.Results
On average, nodes from inside and outside the seizure onset zone (SOZ) increase and decrease, respectively, the large-scale phase-locking. This difference becomes most evident in a joint analysis of low and high frequencies.Conclusions
Nodes inside and outside the SOZ play opposite roles for the large-scale phase-locking in functional EEG network in epilepsy patients.Significance
The application of the phase-locking contribution measure to EEG recordings from epilepsy patients can potentially help in localizing the SOZ.
The application of signal analysis techniques to electroencephalographic (EEG) recordings from epilepsy patients shows that epilepsy involves not only altered neuronal synchronization but also the reorganization of functional EEG networks. This study aims to assess the large-scale phase-locking of such functional networks and how individual network nodes contribute to this collective dynamics.Methods
We analyze the EEG recorded before, during and after seizures from sixteen patients with pharmacoresistant focal-onset epilepsy. The data is filtered to low (4-30 Hz) and high (80-150 Hz) frequencies. We define the multivariate phase-locking measure and the univariate phase-locking contribution measure. Surrogate signals are used to estimate baseline results expected under the null hypothesis that the EEG is a correlated linear stochastic process.Results
On average, nodes from inside and outside the seizure onset zone (SOZ) increase and decrease, respectively, the large-scale phase-locking. This difference becomes most evident in a joint analysis of low and high frequencies.Conclusions
Nodes inside and outside the SOZ play opposite roles for the large-scale phase-locking in functional EEG network in epilepsy patients.Significance
The application of the phase-locking contribution measure to EEG recordings from epilepsy patients can potentially help in localizing the SOZ.
Date of Publication
2024-12
Publication Type
Article
Subject(s)
Keyword(s)
Epilepsy
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Presurgical epilepsy diagnostics
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Quantitative electroencephalography
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Seizure networks
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Seizure onset zone
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Synchronization
Language(s)
en
Contributor(s)
Espinoso, Anaïs | |
Andrzejak, Ralph G |
Series
Clinical Neurophysiology
Publisher
Elsevier
ISSN
1388-2457
Access(Rights)
open.access