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Stimulus repetition probability effects on repetition suppression are position invariant for faces., , , and . NeuroImage, 60 (4): 2128-2135 (2012)A Model for Classification Based on the Functional Connectivity Pattern Dynamics of the Brain., , , , and . ENIC, page 203-208. IEEE Computer Society, (2016)Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture., , and . Front. Neuroinform., (2017)FMRI repetition suppression for voices is modulated by stimulus expectations., , , , and . NeuroImage, (2013)Receptive Field Atlas and Related CNN Models., , , , , , , , , and 5 other author(s). I. J. Bifurcation and Chaos, 14 (2): 551-584 (2004)Position-specific and position-invariant face aftereffects reflect the adaptation of different cortical areas., , , , and . NeuroImage, 43 (1): 156-164 (2008)Neural basis of distractor resistance during visual working memory maintenance., , , , , , and . NeuroImage, (2021)Tracking the Saliency Features in Images Based on Human Observation Statistics., , and . MUSCLE, volume 7252 of Lecture Notes in Computer Science, page 219-233. Springer, (2011)Classification of fMRI data using dynamic time warping based functional connectivity analysis., , , , and . EUSIPCO, page 245-249. IEEE, (2016)Repetition probability effects for inverted faces., , , and . NeuroImage, (2014)