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

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

Description

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.
Show more

Year of publication

2023

Authors

Department of Neuroscience and Biomedical Engineering

Felix Siebenhühner - Creator

Gabriele Arnulfo - Creator

J Matias Palva - Creator

Lino Nobili - Creator

Marco Fusca - Creator

Satu Palva - Creator

Sheng H. Wang - Creator

Vladislav Myrov Orcid -palvelun logo - Creator

University of Genoa - Contributor

University of Glasgow - Contributor

University of Helsinki - Contributor

Zenodo - Publisher

Other information

Fields of science

Neurosciences

Open access

Open

License

Creative Commons CC0 1.0 Universal (CC0 1.0) Public Domain Dedication