Hernan currently has a Thesis project titled: “Modeling of states in the dynamics of brain networks in a resting state” studying the characteristics and dynamic interactions of brain states of the human brain in a functional resting state, considering the relationship between anatomical connectivity and anatomical connectivity and functional dynamics. These states are defined as quasi-stationary patterns that are produced by the dynamic regime of the brain. Furthermore, brain states coordinate different regions of the brain, shaping networks that respond to external sensory stimuli or their own processing. These networks communicate regions that are associated with defined cognitive processes such as vision, listening or language, among others. There are studies that report that functional connectivity and its dynamics are closely related to structural connectivity. In his thesis he proposes to develop a Hidden Semimarkov Model (HsMM) using a Multivariate Autoregressive (MAR) as an observational model and imposing a structural constraint based on the anatomical connectome of the brain. The anatomical constraint will considerably decrease the number of parameters to be estimated and, therefore, fewer samples will be needed to achieve the best model configuration.