Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI.

Galina V Portnova,Mikhail Atanov,Alexey Ivanitsky,Vladislav Balaev,Alina Tetereva,Olga Martynova,Vadim Ushakov,Lyudmila Skiteva

doi:10.3389/fnhum.2017.00654

Abstract

Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

Highlights

Multimodal neuroimaging studies have extensively explored how electroencephalogram (EEG) spectral patterns correlate with neuronal activity mapped by functional magnetic resonance imaging
We found positive correlations of blood oxygenation level dependent (BOLD) fluctuations in resting state only with alpha power spectral density (PSD) averaged across all electrodes for two brain regions: the right precuneus and the left culmen of the cerebellum (Table 1; Figure 1A)
Our findings indicate that the spectral features of EEG frequency bands, variability of alpha peak and changes in Higuchi’s fractal dimension (HFD) correlate significantly with local BOLD fluctuations in the brain during resting state

Summary

Introduction

Multimodal neuroimaging studies have extensively explored how electroencephalogram (EEG) spectral patterns correlate with neuronal activity mapped by functional magnetic resonance imaging (fMRI) (for review, see He and Liu, 2008; Murta et al, 2015). In favor of this hypothesis, Laufs et al (2003) showed that EEG alpha power was inversely correlated with different brain regions functionally responsible for attention. Beta band power was positively correlated with BOLD signal increase in the posterior cingulate, tempo-parietal and dorsomedial prefrontal cortices (Laufs et al, 2003) As these brain areas have exhibited decreased activity in task-related fMRI studies, they have been related to the default mode of brain function (Raichle et al, 2001; Greicius et al, 2003). Other parallel and consequent studies reported similar findings, demonstrating significant coupling between local changes in the BOLD signal and spectral power of distinct frequency bands (Goldman et al, 2002; Goncalves et al, 2006; Laufs et al, 2006; Mantini et al, 2007; Neuner et al, 2014; Sclocco et al, 2014)

Objectives

Methods

Results

Discussion

Conclusion