Assessing Functional Connectivity Dynamics During Cognitive Tasks Involving the Dorsal Stream

Auteurs

Wang HE, Gonzalez-Martinez J, Jirsa V, Chauvel P, Alario FX, Liegeois-Chauvel C

Les auteurs en lien sont membres de l'INS.

Équipes

TNG

Résumé

Functional connectivity and its dynamic reconfiguration during cognitive tasks offer valuable insights into the neural mechanisms underlying cognitive functions. The dorsal language stream plays a crucial role in linking auditory and visual information with motor functions during language-related tasks. In this study, we investigated the dynamic functional connectivity of brain regions within the dorsal stream across five cognitive tasks using invasive stereoelectroencephalography (SEEG) recordings from patients with drug-resistant epilepsy. Our results reveal distinguishable functional connectivity patterns across various cognitive tasks using clustering algorithms. Furthermore, we were able to identify specific cognitive tasks based on their unique functional connectivity signatures, with a median of accuracy 0.91. Additionally, we identified key brain regions with strong connectivity roles and high variability across tasks. We analyzed source (out-degree) and sink (in-degree) regions during the picture naming, ba/pa, and oddball tasks, highlighting both shared and task-specific connectivity patterns. Among the twenty or so brain regions displaying a median in- and out-degree &gt

Functional connectivity and its dynamic reconfiguration during cognitive tasks offer valuable insights into the neural mechanisms underlying cognitive functions. The dorsal language stream plays a crucial role in linking auditory and visual information with motor functions during language-related tasks. In this study, we investigated the dynamic functional connectivity of brain regions within the dorsal stream across five cognitive tasks using invasive stereoelectroencephalography (SEEG) recordings from patients with drug-resistant epilepsy. Our results reveal distinguishable functional connectivity patterns across various cognitive tasks using clustering algorithms. Furthermore, we were able to identify specific cognitive tasks based on their unique functional connectivity signatures, with a median of accuracy 0.91. Additionally, we identified key brain regions with strong connectivity roles and high variability across tasks. We analyzed source (out-degree) and sink (in-degree) regions during the picture naming, ba/pa, and oddball tasks, highlighting both shared and task-specific connectivity patterns. Among the twenty or so brain regions displaying a median in- and out-degree &gt

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