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

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Brain Network Analysis

Background:

• Sustained attention involves anticorrelated activity between the default mode network (DMN) and task positive network (TPN).
• Existing electroencephalography (EEG) studies on this phenomenon are limited and often lack behavioral validation.

Purpose of the Study:

• To investigate brain network dynamics during sustained attention using EEG-based source-level analysis.
• To identify EEG components correlating with attentional performance and validate findings in attention deficit/hyperactivity disorder (ADHD).

Main Methods:

• Applied source-level independent component analysis (ICA) using eLORETA-ICA across multiple frequencies.
• Analyzed EEG data from a large sample (N=1397) of healthy subjects during resting-state and sustained attention tasks.
• Correlated identified brain network components with behavioral measures of inattention (omission errors) and compared optimal vs. suboptimal performers.

Main Results:

• Identified a specific component reflecting anticorrelated delta activity (anterior cingulate, precuneus) and delta/theta/alpha/gamma activity (medial frontal regions) that correlated with inattention.
• Observed greater changes in this component's loading between resting-state and sustained attention in suboptimal compared to optimal performers.
• Prospectively replicated and validated these findings in individuals with ADHD, supporting the default mode interference hypothesis.

Conclusions:

• A distinct pattern of DMN and related network activity is associated with attentional deficits.
• This EEG-based network analysis provides a valid method for studying attention and its disorders.
• Findings support the 'default mode interference hypothesis' of attention regulation.