Switching Mesostate Space Model is a tools that allow Neuroscientists to detect and predict temporal changes in dynamical brain networks (brain states). The methods are based in hierarchical Bayesian models that combines temporal and spatial clustering, brain connectivity analysis called Multivariate Autoregresive Model (MAR) and Variational Bayesian inference. Iván, Olier, Nelson J.Trujillo-Barreto, Wael El-Deredy. 2013. A switching multi-scale dynamical network model of EEG/MEG. Neuroimage, 83, 262-287. https://doi.org/10.1016/j.neuroimage.2013.04.046. 

Brain State Dynamics (BSD) is a new methods that allow Neuroscientists to detect and predict temporal changes in dynamical brain networks (brain states. The methods are based in hierarchical Bayesian models that combines hybrid dynamical models called Hidden Semi Markov Model (HSMM), brain connectivity analysis called Multivariate Autoregresive Model (MAR) and Variational Bayesian inference. Trujillo-Barreto NJ, Araya D, El-Deredy W (2020) “The discrete logic of the Brain-Explicit modelling of Brain State durations in EEG and MEG”. Submitted to Neuroimage, Available in BiorXiv: DOI: https://doi.org/10.1101/635300.