Journal article Open Access
Riccardo Iandolo; Marianna Semprini; Stefano Buccelli; Federico Barban; Mingqi Zhao; Jessica Samogin; Gaia Bonassi; Laura Avanzino; Dante Mantini; Michela Chiappalone
{ "DOI": "10.1109/ojemb.2020.2965323", "abstract": "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 demonstrates 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. ispartof: IEEE Open Journal of Engineering in Medicine and Biology status: accepted", "author": [ { "family": "Riccardo Iandolo" }, { "family": "Marianna Semprini" }, { "family": "Stefano Buccelli" }, { "family": "Federico Barban" }, { "family": "Mingqi Zhao" }, { "family": "Jessica Samogin" }, { "family": "Gaia Bonassi" }, { "family": "Laura Avanzino" }, { "family": "Dante Mantini" }, { "family": "Michela Chiappalone" } ], "id": "46656", "issued": { "date-parts": [ [ 2020, 1, 9 ] ] }, "language": "eng", "note": "", "title": "Small-World Propensity Reveals the Frequency Specificity of Resting State Networks", "type": "article-journal" }
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