Integrating Different Aspects of Resting Brain Activity: A Review of Electroencephalographic Signatures in Resting State Networks Derived from Functional Magnetic Resonance Imaging

Abstract

Electroencephalography (EEG) is an established measure in the field of brain resting state with a range of quantitative methods (qEEG) that yield unique information about neuronal activation and synchronization. Meanwhile, in the last decade, functional magnetic resonance imaging (fMRI) studies have revealed the existence of more than a dozen resting state networks (RSNs), and combined qEEG and fMRI have allowed us to gain understanding about the relationship of qEEG and fMRI-RSNs. However, the overall picture is less clear because there is no a priori hypothesis about which EEG features correspond well to fMRI-RSNs. We reviewed the associations of several types of qEEG features to four RSNs considered as neurocognitive systems central for higher brain processes: the default mode network, dorsal and ventral frontoparietal networks, and the salience network. We could identify 12 papers correlating qEEG and RSNs in adult human subjects and employing a simultaneous design under a no-task resting state condition. A systematic overview investigates which qEEG features replicably relate to the chosen RSNs. This review article leads to the conclusion that spatially delimited θ and whole/local α may be the most promising measures, but the time domain methods add important additional information.

Pre-stimulus BOLD-network activation modulates EEG spectral activity during working memory retention

“…In addition, in the low-load condition, the level of pre-stimulus DMN activation was predictive for alpha increases, which were widespread, but had occipital maxima. As reported in the literature, occipital alpha typically showed positive correlations with DMN activity under resting conditions (Nishida et al, 2015 ). The result, in conjunction with the finding that the low-load condition on average did not produce a significant suppression of DMN activity, may thus suggest that DMN fluctuations were relatively unaffected by the stimulus and may have extended from the pre-stimulus period into the retention period, such that the encountered alpha band effect in the retention period and pre-stimulus DMN fluctuations represent common, but temporally extended processes.…”

Parsing heterogeneity in attention‐deficit hyperactivity disorder using EEG‐based subgroups

“…In terms of underlying neurobiological mechanisms, previous studies using concurrent EEG and fMRI have found that resting state theta (and to some extent delta) band power is negatively associated with activity in the default mode network (DMN) (Luchinger, Michels, Martin, & Brandeis, ), suggesting the slow‐wave activity subgroups may have reduced DMN activity and aberrant network interactions resulting in cortical slowing and lower neural activity during resting state. On the other hand, alpha and beta band power were positively correlated with activity in the DMN and thalamus (Jann, Kottlow, Dierks, Boesch, & Koenig, ; Mantini, Perrucci, Del Gratta, Romani, & Corbetta, ) and negatively associated with attention networks as well as primary sensory regions (Luchinger et al., ; Nishida et al., ). This indicates that subgroups with elevated power in higher frequencies may have higher thalamocortical arousal levels and lower sensory and cognitive processing while at rest.…”

“…Attention problems 65 (10) 66 (10) 67 (11) (7) 24 (6) 20 (8) 21 (8) 21 (8) 1.30 4.0** SWM, spatial working memory; GNG, Go/No-Go. Columns with different superscript letters indicate significant difference (p hand, alpha and beta band power were positively correlated with activity in the DMN and thalamus (Jann, Kottlow, Dierks, Boesch, & Koenig, 2010;Mantini, Perrucci, Del Gratta, Romani, & Corbetta, 2007) and negatively associated with attention networks as well as primary sensory regions (Luchinger et al, 2012;Nishida et al, 2015). This indicates that subgroups with elevated power in higher frequencies may have higher thalamocortical arousal levels and lower sensory and cognitive processing while at rest.…”

Effect of cocaine dependence on brain connections: clinical implications

“…EEG has low spatial resolution and high temporal resolution and so it is natural to combine it with fMRI which has a high spatial resolution, but relatively low temporal resolution, to gain more understanding of brain connectivity. A review [69] of 12 papers correlating EEG and fMRI-based resting state networks in adult human subjects suggests that spatially delimited theta and whole/local alpha waves could add important additional information to fMRI-based resting state networks (RSNs). Combined fMRI-based functional/effective connectivity and MRI diffusion-based structural connectivity may provide additional insight for the relationship between brain structure and function [55,70].…”