ArticleCommunications biology2023
Dissociation between phase and power correlation networks in the human brain is driven by co-occurrent bursts.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Hierarchical whole-brain modeling of critical synchronization dynamics in the human brain.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Building blocks of functional connectivity measures for aperiodic electrophysiological brain signals.Neuroimage. Reports · 2025Article
- Dual-Site Beta tACS Over the rIFG and preSMA-Induced Phase-Specific Changes in Functional Connectivity but not Response Inhibition Performance in Older Adults.Psychophysiology · 2025Article
- Magnetoencephalography Dimensionality Reduction Informed by Dynamic Brain States.The European journal of neuroscience · 2025Article
- Causal interactions between amplitude correlation and phase coupling in cortical networks.Scientific reports · 2025Article
- Longitudinal changes in MEG-based brain network topology of ALS patients with cognitive/behavioral impairment-An exploratory study.Network neuroscience (Cambridge, Mass.) · 2025Article
- Distinct functions for beta and alpha bursts in gating of human working memory.Nature communications · 2024Article
- Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture.Communications biology · 2024Article
- The dissociative role of bursting and non-bursting neural activity in the oscillatory nature of functional brain networks.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Multi-modal and multi-model interrogation of large-scale functional brain networks.NeuroImage · 2023Article
- Linking local and large-scale salient events with oscillatory and broadband arrhythmic activities in the resting human brain.Imaging neuroscience (Cambridge, Mass.)Article
- Replication and validation of two novel magnetoencephalography functional connectivity measures in Alzheimer's disease.Imaging neuroscience (Cambridge, Mass.)Article
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Authors and funding
2 authors.
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Abstract
Well-known haemodynamic resting-state networks are better mirrored in power correlation networks than phase coupling networks in electrophysiological data. However, what do these power correlation networks reflect? We address this long-outstanding question in neuroscience using rigorous mathematical analysis, biophysical simulations with ground truth and application of these mathematical concepts to empirical magnetoencephalography (MEG) data. Our mathematical derivations show that for two non-Gaussian electrophysiological signals, their power correlation depends on their coherence, cokurtosis and conjugate-coherence. Only coherence and cokurtosis contribute to power correlation networks in MEG data, but cokurtosis is less affected by artefactual signal leakage and better mirrors haemodynamic resting-state networks. Simulations and MEG data show that cokurtosis may reflect co-occurrent bursting events. Our findings shed light on the origin of the complementary nature of power correlation networks to phase coupling networks and suggests that the origin of resting-state networks is partly reflected in co-occurent bursts in neuronal activity.
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