Probing the “Default Network Interference Hypothesis” With EEG: An RDoC Approach Focused on Attention

Abstract

Studies have shown that specific networks (default mode network [DMN] and task positive network [TPN]) activate in an anticorrelated manner when sustaining attention. Related EEG studies are scarce and often lack behavioral validation. We performed independent component analysis (ICA) across different frequencies (source-level), using eLORETA-ICA, to extract brain-network activity during resting-state and sustained attention. We applied ICA to the voxel domain, similar to functional magnetic resonance imaging methods of analyses. The obtained components were contrasted and correlated to attentional performance (omission errors) in a large sample of healthy subjects (N = 1397). We identified one component that robustly correlated with inattention and reflected an anticorrelation of delta activity in the anterior cingulate and precuneus, and delta and theta activity in the medial prefrontal cortex and with alpha and gamma activity in medial frontal regions. We then compared this component between optimal and suboptimal attentional performers. For the latter group, we observed a greater change in component loading between resting-state and sustained attention than for the optimal performers. Following the National Institute of Mental Health Research Domain Criteria (RDoC) approach, we prospectively replicated and validated these findings in subjects with attention deficit/hyperactivity disorder. Our results provide further support for the “default mode interference hypothesis.”

A polygenic-informed approach to a predictive EEG signature empowers stratified antidepressant treatment

“…functional brain networks), in a large dataset of severely ill psychiatric patients and healthy controls. In a prior study, this fICA method was tested and validated (45,46), and demonstrated to reliably identify the default mode network (DMN) and task-positive network (TP) in a sample of 1,397 subjects, replicated in an independent ADHD sample (45). Here, we show that two functional networks are signi cantly associated with polygenic liability to multiple common psychiatric disorders (PRS-cross disorder).…”

“…functional networks). This method was recently validated in Aoki et al and Gerrits et al and reliable identi ed DMN (default mode network) and TP (task-positive) networks (45,46).…”

Assessing Fine-Granularity Structural and Functional Connectivity in Children With Attention Deficit Hyperactivity Disorder

“…An experiment comparing 24-h sleep deprivation state with natural arousal state showed that sleep deprivation increased the variation of subjects' reaction time in behavioral performance, and this phenomenon was related to the functional connectivity within DMN and the weakening of negative correlation between component DMN and external brain network (De Havas et al, 2012). Recently, studies using electroencephalogram have also proved the relationship between the variation of behavioral performance and the synchronization of brain activity (Gerrits et al, 2019;Machida et al, 2019;Kucyi et al, 2020). This association also exists in the ADHD population.…”

Neural mechanisms associated with semantic and basic self-oriented memory processes interact moderating self-esteem

“…EEG methods allow the present study to explore the proposed self-protection mechanisms via real-time monitoring of the dynamic interaction between neural regions integral for these processes. Recent advances also provide a means for highly accurate source localization of neural activity, especially regarding regions in the default mode network ( Gerrits et al., 2019 ; Canuet et al., 2011 ; Michel and Brunet, 2019 ; Lin et al., 2006 ). EEG also provides a direct and accurate assessment of activity within (i.e., power) and between (i.e., phase locking) regions and thus the effect of regions on one another via measuring oscillations, a direct byproduct of neural activity, on the order of milliseconds.…”

“…Past research has identified a collection of brain regions integral for basic encoding processes including the hippocampus, lateral aspects of the temporal cortex, medial, and lateral aspects of the prefrontal cortex, and the precuneus/posterior cingulate cortex (PCC) ( Svoboda et al., 2006 ). Of interest to the current study (given its EEG-accessible location in the cortex, Gerrits et al., 2019 ; Canuet et al., 2011 ), the precuneus/PCC has been identified as integral for processes such as attentional allocation, and episodic memory encoding and consolidation ( Northoff et al., 2006 ; Bird et al., 2015 ). PCC has also been shown to integrate new information into autobiographical memories during self-reflection ( Van der Meer et al., 2010 ).…”