IEEE Open Journal of Engineering in Medicine and Biology (Jan 2020)

Small-World Propensity Reveals the Frequency Specificity of Resting State Networks

  • Riccardo Iandolo,
  • Marianna Semprini,
  • Stefano Buccelli,
  • Federico Barban,
  • Mingqi Zhao,
  • Jessica Samogin,
  • Gaia Bonassi,
  • Laura Avanzino,
  • Dante Mantini,
  • Michela Chiappalone

Journal volume & issue
Vol. 1
pp. 57 – 64


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Goal: Functional connectivity (FC) is an important indicator of the brain's state in different conditions, such as rest/task or health/pathology. Here we used high-density electroencephalography coupled to source reconstruction to assess frequency-specific changes of FC during resting state. Specifically, we computed the Small-World Propensity (SWP) index to characterize network small-world architecture across frequencies. Methods: We collected resting state data from healthy participants and built connectivity matrices maintaining the heterogeneity of connection strengths. For a subsample of participants, we also investigated whether the SWP captured FC changes after the execution of a working memory (WM) task. Results: We found that SWP demonstrated a selective increase in the alpha and low beta bands. Moreover, SWP was modulated by a cognitive task and showed increased values in the bands entrained by the WM task. Conclusions: SWP is a valid metric to characterize the frequency-specific behavior of resting state networks.