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

Functional network architecture associated with health varies across individuals, limiting neuroimaging sensitivity for detecting early network maladaptations and identifying at-risk individuals. To increase sensitivity, we use slow wave events (SWEs) as neurophysiological markers in EEG-informed fMRI analyses. Neural excitability and network state impact SWE spatiotemporal dynamics. Analyzing simultaneous EEG-fMRI from two healthy cohorts (N = 24), we generated individual SWE-related BOLD maps. We created cohort-level probabilistic maps and derived reference maps revealing consistently engaged regions, including the cingulate cortex, thalamus, hippocampus, and cerebellum. Stratifying SWEs by synchronization efficiency revealed distinct BOLD patterns. High synchronization SWEs recruited widespread cortical and subcortical networks, whereas low-synchronization SWEs engaged predominantly posterior cortical regions, refining the reference maps for physiologically distinct SWE subtypes. Building on this, we propose the "slow wave canonical activity deviation (SloCAD)" concept to quantify individual deviations from canonical SWE activation, providing a foundation for studying early network dysfunction in pathological conditions.