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Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data.

, , , , , and . PRNI, page 1-4. IEEE Computer Society, (2015)

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Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods., , , , , and . Frontiers Comput. Neurosci., (2017)Graph Embeddings of Dynamic Functional Connectivity Reveal Discriminative Patterns of Task Engagement in HCP Data., , , , , and . PRNI, page 1-4. IEEE Computer Society, (2015)The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI., , , , , , and . NeuroImage, (2016)Towards tailoring non-invasive brain stimulation using real-time fMRI and Bayesian optimization., , , , , , , , , and . PRNI, page 1-4. IEEE, (2016)Text-mining the neurosynth corpus using deep boltzmann machines., , , , and . PRNI, page 1-4. IEEE, (2016)Automated Task Load Detection with Electroencephalography: Towards Passive Brain-Computer Interfacing in Robotic Surgery., , , , , , , and . J. Medical Robotics Res., 2 (1): 1750003:1-1750003:10 (2017)Bayesian optimization for automatic design of face stimuli., , , , and . CoRR, (2020)Novel Modeling of Task vs. Rest Brain State Predictability Using a Dynamic Time Warping Spectrum: Comparisons and Contrasts with Other Standard Measures of Brain Dynamics., , , , , and . Frontiers Comput. Neurosci., (2016)