Source localization and functional network analysis in emotion cognitive reappraisal with EEG-fMRI integration

Area of Science:

• Neuroscience
• Cognitive Science
• Brain Imaging

Background:

• Emotion regulation via cognitive reappraisal is crucial for mental health.
• Traditional neuroimaging (EEG, fMRI) has limitations in temporal and spatial resolution for studying dynamic brain processes.
• Investigating neural networks underlying emotion regulation requires advanced analytical techniques.

Purpose of the Study:

• To develop and validate a multimodal neuroimaging approach integrating EEG and fMRI for enhanced source localization.
• To analyze source-level functional brain networks during emotion-based cognitive reappraisal.
• To identify key brain regions and network dynamics involved in emotion regulation.

Main Methods:

• Simultaneous recording of EEG and fMRI data during an emotional cognitive reappraisal task.
• Application of a novel fused priori weighted minimum norm estimation (FWMNE) with sliding windows for EEG source activity dynamics.
• Construction of functional brain networks using the phase lag index (PLI) in the gamma band.

Main Results:

• The multimodal method successfully identified key brain regions involved in cognitive reappraisal.
• Analysis revealed specific regions, including the cuneus and lateral orbitofrontal cortex, as critical nodes in the reappraisal network.
• The gamma band source-level network analysis highlighted the importance of these regions based on betweenness centrality.

Conclusions:

• The integrated EEG-fMRI source localization method provides high spatiotemporal resolution for analyzing emotion regulation networks.
• This approach effectively identifies critical brain regions and network dynamics in cognitive control during reappraisal.
• The findings suggest potential clinical applications for understanding and treating affective disorders.