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Characterizing the Ventral Visual Stream with Response-Optimized Neural Encoding Models., , , и . NeurIPS, (2022)Functional connectome reorganization relates to post-stroke motor recovery and structural and functional disconnection., , , , , , , и . NeuroImage, (2021)3D Convolutional Neural Networks for Classification of Functional Connectomes., , , и . DLMIA/ML-CDS@MICCAI, том 11045 из Lecture Notes in Computer Science, стр. 137-145. Springer, (2018)A Shared Neural Encoding Model for the Prediction of Subject-Specific fMRI Response., , , , и . MICCAI (7), том 12267 из Lecture Notes in Computer Science, стр. 539-548. Springer, (2020)From Connectomic to Task-Evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-State Functional Connectivity., , , , и . MICCAI (7), том 12267 из Lecture Notes in Computer Science, стр. 62-71. Springer, (2020)NeuroMeasure: A Software Package for Quantification of Cortical Motor Maps Using Frameless Stereotaxic Transcranial Magnetic Stimulation., , , , , , , , , и 2 other автор(ы). Frontiers Neuroinformatics, (2019)Linking white matter integrity loss to associated cortical regions using structural connectivity information in Alzheimer's disease and fronto-temporal dementia: The Loss in Connectivity (LoCo) score., , и . NeuroImage, 61 (4): 1311-1323 (2012)Decoding natural image stimuli from fMRI data with a surface-based convolutional network., , , и . MIDL, том 227 из Proceedings of Machine Learning Research, стр. 107-118. PMLR, (2023)Detecting Abnormalities in Resting-State Dynamics: An Unsupervised Learning Approach., , , и . MLMI@MICCAI, том 11861 из Lecture Notes in Computer Science, стр. 301-309. Springer, (2019)Neural encoding with visual attention., , , , и . NeurIPS, (2020)