Multiway Array Decomposition of EEG Spectrum: Implications of Its Stability for the Exploration of Large-Scale Brain Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F17%3A00095530" target="_blank" >RIV/00216224:14740/17:00095530 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989592:15110/17:73580497 RIV/00216305:26220/17:PU120920

Výsledek na webu

<a href="https://www.mitpressjournals.org/doi/full/10.1162/NECO_a_00933" target="_blank" >https://www.mitpressjournals.org/doi/full/10.1162/NECO_a_00933</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1162/NECO_a_00933" target="_blank" >10.1162/NECO_a_00933</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multiway Array Decomposition of EEG Spectrum: Implications of Its Stability for the Exploration of Large-Scale Brain Networks

Popis výsledku v původním jazyce

The multiway array decomposition methods have been shown to be promising statistical tools for identifying neural activity in the EEG spectrum. They blindly decompose the EEG spectrum into spatial-temporal-spectral patterns by taking into account inherent relationships among signals acquired at different frequencies and sensors. Our study evaluates the stability of spatial-temporal-spectral patterns derived by one particular method called PARAFAC. We focused on patterns’ stability over time and in population and divided the complete dataset containing data from 50 healthy subjects into several subsets. Our results suggest that the patterns are highly stable in time as well as among different subgroups of subjects. Further, we show with simultaneously acquired fMRI data that power fluctuations of some patterns have stable correspondence to hemodynamic fluctuations in large scale brain networks. We did not find such correspondence for power fluctuations in standard frequency bands, i.e. the common way of dealing with EEG data. Altogether our results suggest that the PARAFAC is a suitable method for research in the field of large scale brain networks and their manifestation in EEG signal.

Název v anglickém jazyce

Multiway Array Decomposition of EEG Spectrum: Implications of Its Stability for the Exploration of Large-Scale Brain Networks

Popis výsledku anglicky

The multiway array decomposition methods have been shown to be promising statistical tools for identifying neural activity in the EEG spectrum. They blindly decompose the EEG spectrum into spatial-temporal-spectral patterns by taking into account inherent relationships among signals acquired at different frequencies and sensors. Our study evaluates the stability of spatial-temporal-spectral patterns derived by one particular method called PARAFAC. We focused on patterns’ stability over time and in population and divided the complete dataset containing data from 50 healthy subjects into several subsets. Our results suggest that the patterns are highly stable in time as well as among different subgroups of subjects. Further, we show with simultaneously acquired fMRI data that power fluctuations of some patterns have stable correspondence to hemodynamic fluctuations in large scale brain networks. We did not find such correspondence for power fluctuations in standard frequency bands, i.e. the common way of dealing with EEG data. Altogether our results suggest that the PARAFAC is a suitable method for research in the field of large scale brain networks and their manifestation in EEG signal.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Neural Computation

ISSN

0899-7667

e-ISSN

—

Svazek periodika

29

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

22

Strana od-do

968-989

Kód UT WoS článku

000399678100005

EID výsledku v databázi Scopus

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