AI Article Synopsis
- Dynamic Functional Connectivity (dFC) is linked to cognitive processing and measures how fast brain connectivity networks change over time, particularly under conditions of Sleep Deprivation (SD).
- After 24 hours of sleep deprivation, global dFC speed slows down, but this slowdown doesn’t explain individual cognitive task performance variations, which are diverse and subtle.
- Instead, specific task performance, like Rapid Visual Processing (RVP) related to visual attention, shows strong correlations with dFC speed in targeted functional subnetworks, particularly a frontoparietal module.
Article Abstract
Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks -including Rapid Visual Processing (RVP, assessing sustained visual attention)- and dFC speed quantified at the level of functional sub-networks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module.
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| http://dx.doi.org/10.1016/j.neuroimage.2020.117155 | DOI Listing |
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