https://doi.org/10.1140/epjs/s11734-025-02040-w
Regular Article
Research on spatial feature analysis and dynamical processes of brain functional networks based on data correlation
1
Shanghai Engineering Research Center of Physical Vapor Deposition (PVD) Superhard Coating and Equipment, Shanghai Institute of Technology, 201418, Shanghai, China
2
School of Mathematics and Statistics, Northwestern Polytechnical University, 710072, Xi’an, Shaanxi, China
3
MIIT Key Laboratory of Dynamics and Control of Complex Systems, 710072, Xi’an, Shaanxi, China
Received:
30
July
2025
Accepted:
20
October
2025
Published online:
30
October
2025
This study investigates spatial feature analysis and dynamical processes of brain functional networks based on data correlation. After preprocessing the electroencephalogram recordings from participants, brain functional networks are constructed using phase transfer entropy, capturing the interactions between neuronal clusters in the brain. Independent sample t tests are conducted to assess statistical significance, and ROC curve analysis is employed to characterize the spatial features distinguishing Parkinson’s disease (PD) and healthy controls, quantifying the differences in brain network organization. Additionally, the directionality of information flow between brain regions is analyzed through the phase transfer entropy networks to elucidate interregional information transfer. By analyzing the transmission mechanisms of signals in different brain regions, the spatial feature of brain functional network for PD are obtained. The findings from the simulation analysis are consistent with previously reported physiological experimental results, offering a theoretical foundation for understanding the dynamical processes of brain networks.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
