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Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory., , , , and . NeuroImage, 40 (3): 1064-1076 (2008)Surface area and cortical thickness descriptors reveal different attributes of the structural human brain networks., , , , , , , and . NeuroImage, 50 (4): 1497-1510 (2010)Covert face recognition without the fusiform-temporal pathways., , , , , , , , and . NeuroImage, 57 (3): 1162-1176 (2011)Mapping grip force to motor networks., , , , , , , and . NeuroImage, (2021)A Bayesian framework to identify principal intravoxel diffusion profiles based on diffusion-weighted MR imaging., , , , , and . NeuroImage, 42 (2): 750-770 (2008)Repeatability Analysis of Global and Local Metrics of Brain Structural Networks., , , , , and . Brain Connect., 4 (3): 203-220 (2014)Studying the topological organization of the cerebral blood flow fluctuations in resting state., , and . NeuroImage, (2013)Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting., , , , , , , , , and 5 other author(s). CoRR, (2024)Simultaneous estimation of population receptive field and hemodynamic parameters from single point BOLD responses using Metropolis-Hastings sampling., , , , and . NeuroImage, (2018)Characterizing brain anatomical connections using diffusion weighted MRI and graph theory., , , , , , and . NeuroImage, 36 (3): 645-660 (2007)