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.
Original language | English |
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Article number | 286 |
Pages (from-to) | 1-13 |
Number of pages | 13 |
Journal | Communications biology |
Volume | 6 |
Issue number | 1 |
DOIs | |
Publication status | Published - 18 Mar 2023 |
Bibliographical note
Funding Information:R.H. was funded by NWO-Wiskundeclusters grant nr. 613.009.105. P.K.B.T. was funded by an EMBO New Venture Fellowship 9139 and an EAN Research Experience Fellowship awarded to P.K.B.T.
Publisher Copyright:
© 2023, The Author(s).
Funding
R.H. was funded by NWO-Wiskundeclusters grant nr. 613.009.105. P.K.B.T. was funded by an EMBO New Venture Fellowship 9139 and an EAN Research Experience Fellowship awarded to P.K.B.T.