Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data

Marco Fuscà, Felix Siebenhühner, Sheng H. Wang, Vladislav Myrov, Gabriele Arnulfo, Lino Nobili, J. Matias Palva and Satu Palva ()
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Marco Fuscà: University of Glasgow
Felix Siebenhühner: University of Helsinki
Sheng H. Wang: University of Helsinki
Vladislav Myrov: Aalto University
Gabriele Arnulfo: University of Helsinki
Lino Nobili: University of Genoa
J. Matias Palva: University of Glasgow
Satu Palva: University of Glasgow

Nature Communications, 2023, vol. 14, issue 1, 1-13

Abstract: Abstract Neuronal oscillations and their synchronization between brain areas are fundamental for healthy brain function. Yet, synchronization levels exhibit large inter-individual variability that is associated with behavioral variability. We test whether individual synchronization levels are predicted by individual brain states along an extended regime of critical-like dynamics – the Griffiths phase (GP). We use computational modelling to assess how synchronization is dependent on brain criticality indexed by long-range temporal correlations (LRTCs). We analyze LRTCs and synchronization of oscillations from resting-state magnetoencephalography and stereo-electroencephalography data. Synchronization and LRTCs are both positively linearly and quadratically correlated among healthy subjects, while in epileptogenic areas they are negatively linearly correlated. These results show that variability in synchronization levels is explained by the individual position along the GP with healthy brain areas operating in its subcritical and epileptogenic areas in its supercritical side. We suggest that the GP is fundamental for brain function allowing individual variability while retaining functional advantages of criticality.

Date: 2023
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DOI: 10.1038/s41467-023-40056-9

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