High-dimensional brain-wide functional connectivity mapping in magnetoencephalography

Brain functional connectivity (FC) analyses based on magneto/electroencephalography (M/EEG) signals have yet to exploit the intrinsic high-dimensional information. Typically, these are constrained regions of interest avoid curse dimensionality, with latter leading conservative hypothesis testing. We removed such constraint by estimating source-based M/EEG-FC using cluster-permutation statistic (CPS) and demonstrated feasibility this approach identifying resting-state changes in mild cognitive impairment (MCI), a prodromal stage Alzheimer’s disease. Particularly, we proposed unified framework for CPS analysis together novel neighbourhood measure estimate more compact neurophysiological plausible neural communication. As clusters could confidently reveal interregional communication, tested cluster-strength index demonstrate other advantages analysis. found increased communication or hypersynchronization MCI compared healthy controls delta (1?4 Hz) higher-theta (6?8 bands oscillations. These mainly consisted interactions between occipitofrontal occipitotemporal left hemisphere, which may be critically affected early stages Our important create high-resolution FC maps from neuroimaging studies general, allowing multimodal across multiple spatial scales. robustly represent dense bundles connections that less sensitive inter-individual anatomical variability. Overall, help better understand information processing disease conditions as needed developing biomarker research.