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Quantitative EEG Markers of Entropy and Auto Mutual Information in Relation to MMSE Scores of Probable Alzheimer's Disease Patients., , , , , , , , , and . Entropy, 19 (3): 130 (2017)Electroencephalographic complexity markers explain neuropsychological test scores in Alzheimer's disease., , , , , , , , , and 4 other author(s). BHI, page 496-499. IEEE, (2014)How specifically do we learn? Imaging the learning of multiplication and subtraction., , , , , , and . NeuroImage, 30 (4): 1365-1375 (2006)Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease., , , , , , , , , and 3 other author(s). AIME, volume 10259 of Lecture Notes in Computer Science, page 65-75. Springer, (2017)A flexible method for the automated offline-detection of artifacts in multi-channel electroencephalogram recordings., , , , , , , and . EMBC, page 3793-3796. IEEE, (2017)Learning by strategies and learning by drill - evidence from an fMRI study., , , , , , , , and . NeuroImage, 25 (3): 838-849 (2005)Predicting rapid cognitive decline in Alzheimer's disease patients using quantitative EEG markers and neuropsychological test scores., , , , , , , , and . EMBC, page 6078-6081. IEEE, (2016)Using static and dynamic canonical correlation coefficients as quantitative EEG markers for Alzheimer's disease severity., , , , , , , , , and 4 other author(s). EMBC, page 2801-2804. IEEE, (2014)Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity., , , , , , , , , and 4 other author(s). CoRR, (2018)