Data from: Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings

Phase synchronization of neuronal oscillations in specific frequency bands
coordinates anatomically distributed neuronal processing and
communication. Typically, oscillations and synchronization take place
concurrently in many distinct frequencies, which serve separate
computational roles in cognitive functions. While within-frequency phase
synchronization has been studied extensively, less is known about the
mechanisms that govern neuronal processing distributed across frequencies
and brain regions. Such integration of processing between frequencies
could be achieved via cross-frequency coupling (CFC), either by
phase-amplitude coupling (PAC) or by n:m-cross-frequency phase synchrony
(CFS). So far, studies have mostly focused on local CFC in individual
brain regions, whereas the presence and functional organization of CFC
between brain areas have remained largely unknown. We posit that
inter-areal CFC may be essential for large-scale coordination of neuronal
activity and investigate here whether genuine CFC networks are present in
human resting-state brain activity. To assess the functional organization
of CFC networks, we identified brain-wide CFC networks at meso-scale
resolution from stereo-electroencephalography (SEEG) and at macro-scale
resolution from source-reconstructed magnetoencephalography (MEG) data. We
developed a novel graph-theoretical method to distinguish genuine CFC from
spurious CFC that may arise from non-sinusoidal signals ubiquitous in
neuronal activity. We show that genuine inter-areal CFC is present in
human resting-state activity in both MEG and SEEG data. Both CFS and PAC
networks coupled theta and alpha oscillations with higher frequencies in
large-scale networks connecting anterior and posterior brain regions. CFS
and PAC networks had distinct spectral patterns and opposing distribution
of low- and high frequency   network hubs, implying that
they constitute distinct CFC mechanisms. The strength of CFS networks was
also predictive of cognitive performance in a separate neuropsychological
assessment. In conclusion, these results provide evidence for inter-areal
CFS and PAC being two distinct mechanisms for coupling oscillations across
frequencies in large-scale brain networks.