Abstract
Goal: We aimed to identify electroencephalographic (EEG) signal fluctuations within independent components (ICs) that correlate to spontaneous blood oxygenation level dependent (BOLD) activity in regions of the default mode network (DMN) during eyes-closed resting state.Methods: We analyzed simultaneously acquired EEG and functional magnetic resonance imaging (fMRI) eyes-closed resting state data in a convenience sample of 30 participants. IC analysis (ICA) was used to decompose the EEG time-series and common ICs were identified using data-driven IC clustering across subjects. The IC time courses were filtered into seven frequency bands, convolved with a hemeodynamic response function (HRF) and used to model spontaneous fMRI signal fluctuations across the brain. In parallel, group ICA analysis was used to decompose the fMRI signal into ICs from which the DMN was identified. Frequency and IC cluster associated hemeodynamic correlation maps obtained from the regression analysis were spatially correlated with the DMN. To investigate the reliability of our findings, the analyses were repeated with data collected from the same subjects 1 year later.Results: Our results indicate a relationship between power fluctuations in the delta, theta, beta and gamma frequency range and the DMN in different EEG ICs in our sample as shown by small to moderate spatial correlations at the first measurement (0.234 < |r| < 0.346, p < 0.0001). Furthermore, activity within an EEG component commonly identified as eye movements correlates with BOLD activity within regions of the DMN. In addition, we demonstrate that correlations between EEG ICs and the BOLD signal during rest are in part stable across time.Discussion: We show that ICA source separated EEG signals can be used to investigate electrophysiological correlates of the DMN. The relationship between the eye movement component and the DMN points to a behavioral association between DMN activity and the level of eye movement or the presence of neuronal activity in this component. Previous findings of an association between frontal midline theta activity and the DMN were replicated.
Highlights
Synchronous low frequency fluctuations in the blood oxygenation level dependent signal (BOLD) as measured by functional magnetic resonance imaging during rest have gained considerable interest in recent years (Raichle, 2011)
We have found an association between the power of several frequency bands of different EEG independent components (ICs) with BOLD signal fluctuations in regions that are spatially correlated with the default mode network (DMN)
The findings of this study suggest a complex relationship between the representation of the DMN found in the functional magnetic resonance imaging (fMRI)-BOLD signal and EEG component activity
Summary
Synchronous low frequency fluctuations in the blood oxygenation level dependent signal (BOLD) as measured by functional magnetic resonance imaging (fMRI) during rest have gained considerable interest in recent years (Raichle, 2011). These temporally correlated and spatially organized large-scale resting state networks (RSNs) can be detected in the absence of a specific task, are obtained from different populations (e.g., children or patients), and are consistently identified across subjects (Beckmann et al, 2005; Fox and Raichle, 2007). RSNs are commonly identified using data-driven independent component analyses (ICA), which is frequently applied as an unsupervised learning method that separates mixed signals into maximally statistically independent components (ICs; Damoiseaux et al, 2006)
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