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Temporal Stability of Resting State fMRI Data Analysis by Independent Components Method

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Biologically Inspired Cognitive Architectures 2023 (BICA 2023)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1130))

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Abstract

This paper is devoted to the analysis of the temporal stability of the independent components obtained by analyzing data of resting state functional Magnetic Resonance Imaging (fMRI). We analyzed 25 datasets of healthy volunteers, consisting of 1000 time samples each. The fMRI data recording time was 33.3 min for each volunteer. This approach made it possible to divide the experimental session into several time ranges to assess the temporal stability of the results obtained with the independent component analysis (ICA). During the analysis, the property of additivity of independent components was discovered: the dynamics of the independent components obtained in the analysis of individual time ranges have a high level of Pearson correlation (at least 0.9) with the dynamics of the independent components obtained in the analysis of the full experimental session, i.e., the result of ICA is robust to the choice of window size when analyzing a representative data sample. It was also shown that the time series of independent components, which topology corresponds to resting state networks, have a correlation with the global signal at the level of 0.4–0.5.

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Acknowledgments

The study was supported by a government task in the National Research Centre “Kurchatov Institute” and carried out using computing resources of the federal center for collective use “complex of modelling and data processing of mega-class research facilities NRC Kurchatov institute”.

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Authors and Affiliations

  1. National Research Center “Kurchatov Institute”, Moscow, Russia

    V. A. Orlov, S. I. Kartashov, M. V. Kalmykova & A. A. Poyda

  2. Institute for Advanced Study of the Brain, Lomonosov Moscow State University, Moscow, Russia

    Vadim L. Ushakov

  3. “Psychiatric Hospital No. 1 Named After N.A. Alexeev of the Department of Health of Moscow” (GBUZ “PKB No. 1 DZM”), Moscow, Russia

    Vadim L. Ushakov

Authors
  1. V. A. Orlov
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  2. S. I. Kartashov
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  3. M. V. Kalmykova
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  4. A. A. Poyda
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  5. Vadim L. Ushakov
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Corresponding author

Correspondence to V. A. Orlov .

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Editors and Affiliations

  1. Cybernetics Department, Moscow Engineering Physics Institute, Moscow, Russia

    Alexei V. Samsonovich

  2. College of Science and Technology, Ningbo University, Ningbo, China

    Tingting Liu

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Orlov, V.A., Kartashov, S.I., Kalmykova, M.V., Poyda, A.A., Ushakov, V.L. (2024). Temporal Stability of Resting State fMRI Data Analysis by Independent Components Method. In: Samsonovich, A.V., Liu, T. (eds) Biologically Inspired Cognitive Architectures 2023. BICA 2023. Studies in Computational Intelligence, vol 1130. Springer, Cham. https://doi.org/10.1007/978-3-031-50381-8_70

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