Slow wave canonical activity deviation concept: Toward a slow wave-based EEG-fMRI reference map for health-associated...

Area of Science:

• Neuroscience
• Neuroimaging
• Computational Neuroscience

Background:

• Individual variations in brain functional networks challenge neuroimaging's sensitivity for detecting early maladaptations.
• Slow wave events (SWEs) are neurophysiological markers influenced by neural excitability and network states, impacting their spatiotemporal dynamics.

Purpose of the Study:

• To enhance neuroimaging sensitivity by integrating EEG-informed fMRI analyses using SWEs.
• To develop reference maps of SWE-related brain activity and stratify these based on SWE synchronization efficiency.
• To introduce the Slow Wave Canonical Activity Deviation (SloCAD) concept for quantifying individual deviations from typical SWE activation patterns.

Main Methods:

• Simultaneous EEG-fMRI data from two healthy cohorts (N=24) were analyzed.
• Individual SWE-related Blood-Oxygen-Level-Dependent (BOLD) maps were generated.
• Cohort-level probabilistic maps and reference maps were created, with SWEs stratified by synchronization efficiency.

Main Results:

• Consistently engaged regions, including the cingulate cortex, thalamus, hippocampus, and cerebellum, were identified in reference maps.
• High synchronization SWEs engaged widespread cortical and subcortical networks.
• Low-synchronization SWEs predominantly engaged posterior cortical regions, refining reference maps for distinct SWE subtypes.

Conclusions:

• SWEs can serve as sensitive neurophysiological markers in EEG-fMRI for mapping brain activity.
• Stratification of SWEs by synchronization efficiency reveals distinct BOLD patterns, enabling refined reference maps.
• The proposed SloCAD concept offers a foundation for studying early network dysfunction in pathological conditions.