Reliable local dynamics in the brain across sessions are revealed by whole‐brain modeling of resting state activity

• Published in: Human brain mapping Vol. 40; no. 10; pp. 2967 - 2980
• Main Authors: Donnelly‐Kehoe, Patricio, Saenger, Victor M., Lisofsky, Nina, Kühn, Simone, Kringelbach, Morten L., Schwarzbach, Jens, Lindenberger, Ulman, Deco, Gustavo
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.07.2019
• Subjects: Adult; Brain; Brain - physiology; Brain architecture; Brain mapping; Brain Mapping - methods; brain metrics; brain oscillations; consistency; Correlation analysis; Female; Functional magnetic resonance imaging; Functional morphology; Group dynamics; Heterogeneity; Hubs; Humans; Image Processing, Computer-Assisted - methods; Independent component analysis; Magnetic Resonance Imaging; Male; Models, Neurological; Neural networks; Neural Pathways - physiology; Neuroimaging; Oscillations; Parameter estimation; Rest - physiology; Sensorimotor integration; Therapeutic applications; Transition points; Variation; whole‐brain modeling; Young Adult; brain metrics; brain oscillations; consistency; whole-brain modeling
• ISSN: 1065-9471; 1097-0193; 1097-0193
• DOI: 10.1002/hbm.24572

Resting state fMRI is a tool for studying the functional organization of the human brain. Ongoing brain activity at “rest” is highly dynamic, but procedures such as correlation or independent component analysis treat functional connectivity (FC) as if, theoretically, it is stationary and therefore the fluctuations observed in FC are thought as noise. Consequently, FC is not usually used as a single‐subject level marker and it is limited to group studies. Here we develop an imaging‐based technique capable of reliably portraying information of local dynamics at a single‐subject level by using a whole‐brain model of ongoing dynamics that estimates a local parameter, which reflects if each brain region presents stable, asynchronous or transitory oscillations. Using 50 longitudinal resting‐state sessions of one single subject and single resting‐state sessions from a group of 50 participants we demonstrate that brain dynamics can be quantified consistently with respect to group dynamics using a scanning time of 20 min. We show that brain hubs are closer to a transition point between synchronous and asynchronous oscillatory dynamics and that dynamics in frontal areas have larger heterogeneity in its values compared to other lobules. Nevertheless, frontal regions and hubs showed higher consistency within the same subject while the inter‐session variability found in primary visual and motor areas was only as high as the one found across subjects. The framework presented here can be used to study functional brain dynamics at group and, more importantly, at individual level, opening new avenues for possible clinical applications.