Interpreting temporal fluctuations in resting-state functional connectivity MRI

• Published in: NeuroImage (Orlando, Fla.) Vol. 163; pp. 437 - 455
• Main Authors: Liégeois, Raphaël, Laumann, Timothy O., Snyder, Abraham Z., Zhou, Juan, Yeo, B.T. Thomas
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.12.2017; Elsevier Limited
• Subjects: Autoregressive model; Brain - physiology; Brain architecture; Brain mapping; Brain states; Connectome - methods; Data processing; Dynamic FC; Functional magnetic resonance imaging; Humans; Hypothesis testing; Image Processing, Computer-Assisted - methods; Linear dynamical systems; Magnetic Resonance Imaging - methods; Markov chains; Models, Neurological; Nerve Net - physiology; Neural networks; Neural Pathways - physiology; Nonlinear systems; Random variables; Stationarity; Statistics; Surrogate data; Time series; Stationarity; Linear dynamical systems; Autoregressive model; Dynamic FC; Brain states; Surrogate data

Resting-state functional connectivity is a powerful tool for studying human functional brain networks. Temporal fluctuations in functional connectivity, i.e., dynamic functional connectivity (dFC), are thought to reflect dynamic changes in brain organization and non-stationary switching of discrete...