Abstract
Network-based analysis methods of resting state fMRI data have revealed important aspects on the organization of the human brain. However, most of the known methods for quantifying functional coupling between fMRI time series are focused on linear correlation metrics. In this work, we used a synchronization index defined in the phase space of BOLD signals of a cohort of healthy subjects to construct their functional connectivity matrices. A regression analysis is then performed to identify age-related topological changes of synchronization-based functional connectivity. The results show that several brain regions exhibit significant age correlation, thus synchronization-based connectivity could be further be explored to investigate developmental and life-span trajectories.
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Lombardi, A., Amoroso, N., Diacono, D., Lella, E., Bellotti, R., Tangaro, S. (2019). Age Related Topological Analysis of Synchronization-Based Functional Connectivity. In: Aiello, L., Cherifi, C., Cherifi, H., Lambiotte, R., Lió, P., Rocha, L. (eds) Complex Networks and Their Applications VII. COMPLEX NETWORKS 2018. Studies in Computational Intelligence, vol 813. Springer, Cham. https://doi.org/10.1007/978-3-030-05414-4_52
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