Classifying Vulnerability to Sleep Deprivation Using Resting-State Functional MRI Graph Theory Metrics
نویسندگان
چکیده
منابع مشابه
Graph-Based Network Analysis of Resting-State Functional MRI
In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivi...
متن کاملClassifying vulnerability to sleep deprivation using baseline measures of psychomotor vigilance.
OBJECTIVES To identify measures derived from baseline psychomotor vigilance task (PVT) performance that can reliably predict vulnerability to sleep deprivation. DESIGN Subjects underwent total sleep deprivation and completed a 10-min PVT every 1-2 h in a controlled laboratory setting. Participants were categorized as vulnerable or resistant to sleep deprivation, based on a median split of lap...
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Significant inter-individual differences in vigilance decline following sleep deprivation exist. We characterized functional connectivity in 68 healthy young adult participants in rested wakefulness and following a night of total sleep deprivation. After whole brain signal regression, functionally connected cortical networks during the well-rested state exhibited reduced correlation following s...
متن کاملPredicting vulnerability to sleep deprivation using diffusion model parameters.
We used diffusion modelling to predict vulnerability to decline in psychomotor vigilance task (PVT) performance following a night of total sleep deprivation (SD). A total of 135 healthy young adults (69 women, age = 21.9 ± 1.7 years) participated in several within-subject cross-over design studies that incorporated the PVT. Participants were classified as vulnerable (lower tertile) or non-vulne...
متن کاملGraph analysis of resting-state ASL perfusion MRI data: Nonlinear correlations among CBF and network metrics
Human connectome mapping is important to understand both normal brain function and disease-related dysfunction. Although blood-oxygen-level-dependent (BOLD) fMRI has been the most commonly used method for human connectome mapping, arterial spin labeling (ASL) is an fMRI technique to measure cerebral blood flow (CBF) directly and noninvasively, and thus provides a more direct quantitative correl...
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ژورنال
عنوان ژورنال: Frontiers in Neuroscience
سال: 2021
ISSN: 1662-453X
DOI: 10.3389/fnins.2021.660365