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Solving large-scale MEG/EEG source localization and functional connectivity problems simultaneously using state-space models.

, , , and . CoRR, (2022)

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Hebbian Learning-Guided Random Walks for Enhanced Community Detection in Correlation-Based Brain Networks., and . IDEAL, volume 14404 of Lecture Notes in Computer Science, page 222-232. Springer, (2023)Detecting brain network communities: Considering the role of information flow and its different temporal scales., , , and . NeuroImage, (2021)Dynamical Mean Field Model of a Neural-Glial Mass., and . Neural Comput., 22 (4): 969-997 (2010)Energy-based stochastic control of neural mass models suggests time-varying effective connectivity in the resting state., and . J. Comput. Neurosci., 32 (3): 563-576 (2012)Identification and comparison of stochastic metabolic/hemodynamic models (sMHM) for the generation of the BOLD signal., , , , and . J. Comput. Neurosci., 26 (2): 251-269 (2009)Machine Learning for Time Series Forecasting Using State Space Models., and . IDEAL, volume 14404 of Lecture Notes in Computer Science, page 470-482. Springer, (2023)Multifocus image fusion via the Hartley transform., , and . CCECE, page 1-5. IEEE, (2016)Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease., , , , and . NeuroImage, (2017)Solving large-scale MEG/EEG source localization and functional connectivity problems simultaneously using state-space models., , , and . CoRR, (2022)Realistically Coupled Neural Mass Models Can Generate EEG Rhythms., , , , and . Neural Comput., 19 (2): 478-512 (2007)