Education, and the balance between dynamic and stationary functional connectivity jointly support executive functions in relapsing–remitting multiple sclerosis

• Published in: Human brain mapping Vol. 39; no. 12; pp. 5039 - 5049
• Main Authors: Lin, Sue‐Jin, Vavasour, Irene, Kosaka, Brenda, Li, David K. B., Traboulsee, Anthony, MacKay, Alex, McKeown, Martin J.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.12.2018
• Subjects: Adult; Anxiety; Biomarkers; Cerebral Cortex - diagnostic imaging; Cerebral Cortex - physiopathology; Cerebral hemispheres; Cognition; Cognitive ability; Cognitive tasks; Connectome - methods; Coordination; Correlation analysis; Demographics; Density; Education; Educational Status; Executive function; Executive Function - physiology; Fatigue; Female; Functional magnetic resonance imaging; Functionals; Graph theory; Humans; Intelligence; Magnetic Resonance Imaging; Male; Mental depression; Middle Aged; Mood; Multiple sclerosis; Multiple Sclerosis, Relapsing-Remitting - diagnostic imaging; Multiple Sclerosis, Relapsing-Remitting - physiopathology; Nerve Net - diagnostic imaging; Nerve Net - physiopathology; Severity of Illness Index; Short term memory; cognitive function; dynamic functional connectivity; graph theory; sliding window approach; multiset canonical correlation analysis; resting-state fMRI; network characteristics

Graphical network characteristics and nonstationary functional connectivity features, both derived from resting‐state functional magnetic resonance imaging (rsfMRI) data, have been associated with cognitive performance in healthy subjects. How these features jointly relate to cognition in diseased s...