Abstract
Resting-state functional Magnetic Resonance Imaging (R-fMRI) measures spontaneous low-frequency oscillations of the BOLD signal in order to identify the functional architecture of the human brain. The analysis of such data allowed to identify resting state networks (RSN) and other areas of the brain that operate synchronously in time. Over the past few years, the interest of both scientists and clinicians to various methods of R-fMRI data analysis has greatly increased. In this article, we present a review and comparison of various methods and algorithms for analyzing the functional connectivity of the human brain in resting state, developed in the world, based on an analysis of the literature.
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Orlov, V.A., Ushakov, V.L., Kozlov, S.O., Enyagina, I.M., Poyda, A.A. (2020). A Review of Method and Approaches for Resting State fMRI Analyses. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2019. BICA 2019. Advances in Intelligent Systems and Computing, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-25719-4_52
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DOI: https://doi.org/10.1007/978-3-030-25719-4_52
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