Detection of functional brain network reconfiguration during task-driven cognitive states.

摘要: Abstract Network science offers computational tools to elucidate the complex patterns of interactions evident in neuroimaging data. Recently, these have been used detect dynamic changes network connectivity that may occur at short time scales. The dynamics fMRI connectivity, and how they differ across scales, are far from understood. A simple way interrogate different scales is alter size window extract sequential (or rolling) measures functional connectivity. Here, n  = 82 participants performing three distinct cognitive visual tasks recognition memory strategic attention, we subdivided regional BOLD series into variable sized windows determined impact on observed dynamics. Specifically, applied a multilayer community detection algorithm identify temporal communities calculated flexibility quantify over time. Within our frequency band interest, large small were associated with narrow range values brain, while medium broad values. Using 75–100 s, uncovered brain regions low (considered core regions, attention areas) high periphery subcortical lobe regions) via comparison appropriate null models. Generally, this work demonstrates length during task performance, offering pragmatic considerations choice analysis. More broadly, reveals organizational principles not accessible static approaches.