Estimating Dynamic Functional Brain Connectivity With a Sparse Hidden Markov Model

Estimating dynamic functional network connectivity (dFNC) of the brain from functional magnetic resonance imaging (fMRI) data can reveal both spatial and temporal organization and can be applied to track the developmental trajectory of brain maturity as well as to study mental illness. Resting state fMRI (rs-fMRI) is regarded as a promising task since it reflects the spontaneous brain activity without an external stimulus. The sliding window...