Detail publikace

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

LAMOŠ, M. MAREČEK, R. SLAVÍČEK, T. MIKL, M. REKTOR, I. JAN, J.

Originální název

Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Objective. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during electroencephalogram (EEG) data analysis may leave part of the neural activity unrecognized. We propose an approach that blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. Approach. The blind decomposition of EEG spectrogram by parallel factor analysis has been shown to be a useful technique for uncovering patterns of neural activity. The simultaneously acquired BOLD fMRI data were decomposed by independent component analysis. Dynamic functional connectivity was computed on the component's time series using a sliding window correlation, and between-network connectivity states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of between-network connectivity states and the fluctuations of EEG spectral patterns. Main results. We found three patterns related to the dynamics of between-network connectivity states. The first pattern has dominant peaks in the alpha, beta, and gamma bands and is related to the dynamics between the auditory, sensorimotor, and attentional networks. The second pattern, with dominant peaks in the theta and low alpha bands, is related to the visual and default mode network. The third pattern, also with peaks in the theta and low alpha bands, is related to the auditory and frontal network. Significance. Our previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. In this study, we suggest that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.

Klíčová slova

fMRI;EEG;ICA;PARAFAC;dynamic functional connectivity

Autoři

LAMOŠ, M.; MAREČEK, R.; SLAVÍČEK, T.; MIKL, M.; REKTOR, I.; JAN, J.

Vydáno

16. 4. 2018

Nakladatel

IOP Publishing Ltd

ISSN

1741-2552

Periodikum

Journal of Neural Engineering

Ročník

15

Číslo

3

Stát

Spojené království Velké Británie a Severního Irska

Strany od

1

Strany do

12

Strany počet

12

BibTex

@article{BUT150334,
  author="Martin {Lamoš} and Radek {Mareček} and Tomáš {Slavíček} and Michal {Mikl} and Ivan {Rektor} and Jiří {Jan}",
  title="Spatial-temporal-spectral EEG patterns of BOLD functional network connectivity dynamics",
  journal="Journal of Neural Engineering",
  year="2018",
  volume="15",
  number="3",
  pages="1--12",
  doi="10.1088/1741-2552/aab66b",
  issn="1741-2552"
}