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The Dynamics of Triple Interactions in Resting fMRI: Insights into Psychotic Disorders

Published 1 Nov 2024 in q-bio.NC and stat.CO | (2411.00982v2)

Abstract: The human brain dynamically integrated and configured information to adapt to the environment. To capture these changes over time, dynamic second-order functional connectivity was typically used to capture transient brain patterns. However, dynamic second-order functional connectivity typically ignored interactions beyond pairwise relationships. To address this limitation, we utilized dynamic triple interactions to investigate multiscale network interactions in the brain. In this study, we evaluated a resting-state fMRI dataset that included individuals with psychotic disorders (PD). We first estimated dynamic triple interactions using resting-state fMRI. After clustering, we estimated cohort-specific and cohort-common states for controls (CN), schizophrenia (SZ), and schizoaffective disorder (SAD). From the cohort-specific states, we observed significant triple interactions, particularly among visual, subcortical, and somatomotor networks, as well as temporal and higher cognitive networks in SZ. In SAD, key interactions involved temporal networks in the initial state and somatomotor networks in subsequent states. From the cohort-common states, we observed that high-cognitive networks were primarily involved in SZ and SAD compared to CN. Furthermore, the most significant differences between SZ and SAD also existed in high-cognitive networks. In summary, we studied PD using dynamic triple interaction, the first time such an approach has been used to study PD. Our findings highlighted the significant potential of dynamic high-order functional connectivity, paving the way for new avenues in the study of the healthy and disordered human brain.

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References (7)
  1. E. Allen, E. Damaraju, S. Plis, E. Erhardt, T. Eichele, and V. Calhoun, “Tracking whole-brain connectivity dynamics in the resting state,” Cerebral cortex (New York, N.Y. : 1991), 11 2012.
  2. Q. Li, G. V. Steeg, S. Yu, and J. Malo, “Functional connectome of the human brain with total correlation,” Entropy, vol. 24, no. 12, 2022.
  3. Q. Li, G. Ver Steeg, and J. Malo, “Functional connectivity via total correlation: Analytical results in visual areas,” Neurocomputing, vol. 571, p. 127143, 12 2023.
  4. C. A. Tamminga, G. Pearlson, M. Keshavan, J. Sweeney, B. Clementz, and G. Thaker, “Bipolar and schizophrenia network for intermediate phenotypes: Outcomes across the psychosis continuum,” Schizophrenia Bulletin, vol. 40, pp. S131–S137, 02 2014.
  5. A. Iraji, Z. Fu, A. Faghiri, M. Duda, J. Chen, S. Rachakonda, T. DeRamus, P. Kochunov, B. Adhikari, A. Belger, J. Ford, D. Mathalon, G. Pearlson, S. Potkin, A. Preda, J. Turner, T. Erp, J. Bustillo, K. Yang, and V. Calhoun, “Identifying canonical and replicable multi-scale intrinsic connectivity networks in 100k+ resting-state fmri datasets,” Human Brain Mapping, vol. 44, 10 2023.
  6. A. Iraji, A. Faghiri, N. Lewis, Z. Fu, S. Rachakonda, and V. D. Calhoun, “Tools of the trade: estimating time-varying connectivity patterns from fmri data,” Social Cognitive and Affective Neuroscience, vol. 16, pp. 849 – 874, 2020.
  7. S. Watanabe, “Information theoretical analysis of multivariate correlation,” IBM Journal of research and development, vol. 4, no. 1, pp. 66–82, 1960.

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