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State-transition dynamics of resting-state functional magnetic resonance imaging data: Model comparison and test-to-retest analysis
Electroencephalogram (EEG) microstate analysis entails finding dynamics of quasi-stable and generally recurrent discrete states in multichannel EEG time series data and relating properties of the estimated state-transition dynamics to observables such as cognition and behavior.
Reliability of energy landscape analysis of resting-state functional MRI data
Energy landscape analysis is a data-driven method to analyze multidimensional time series, including functional magnetic resonance imaging (fMRI) data.
Modeling state-transition dynamics in resting-state brain signals by the hidden Markov and Gaussian mixture models
However, we also find that the accuracy of the GMM is comparable to that of the HMM under the condition that the sampling frequency is reasonably low (e. g., TR = 2. 88 or 3. 60 s) or the data is relatively short.
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