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Mining cross-frequency coupling microstates (CFCμstates) from EEG recordings during resting state and mental arithmetic tasks., , , and . EMBC, page 5517-5520. IEEE, (2016)Aberrant Whole-Brain Transitions and Dynamics of Spontaneous Network Microstates in Mild Traumatic Brain Injury., , , , and . Frontiers Comput. Neurosci., (2019)Optimization of graph construction can significantly increase the power of structural brain network studies., , and . NeuroImage, (2019)Phase to amplitude coupling as a potential biomarker for creative ideation: An EEG study., , , and . EMBC, page 383-386. IEEE, (2016)Comparison of brain network models using cross-frequency coupling and attack strategies., , , , , , , and . EMBC, page 7426-7429. IEEE, (2015)A Novel, Fast, Reliable, and Data-Driven Method for Simultaneous Single-Trial Mining and Amplitude - Latency Estimation Based on Proximity Graphs and Network Analysis., , , , and . Frontiers Neuroinformatics, (2018)Classifying children with reading difficulties from non-impaired readers via symbolic dynamics and complexity analysis of MEG resting-state data., , , , , , and . ISSPIT, page 333-336. IEEE, (2016)Querying functional brain connectomics to discover consistent subgraph patterns., , , and . BIBE, page 1-4. IEEE Computer Society, (2013)Mining cross-frequency coupling microstates from resting state MEG: An application to mild traumatic brain injury., , , , and . EMBC, page 5513-5516. IEEE, (2016)Multilayer Network Framework Reveals Cross-Frequency Coupling Hubs in Cortical Olfactory Perception., , , , , , and . EMBC, page 3338-3341. IEEE, (2022)