%A Chamberland,Maxime %A Bernier,Michaël %A Fortin,David %A Whittingstall,Kevin %A Descoteaux,Maxime %D 2015 %J Frontiers in Neuroscience %C %F %G English %K diffusion MRI,Resting-state fMRI,tractography,Structure-Function Relationship,visualization %Q %R 10.3389/fnins.2015.00275 %W %L %M %P %7 %8 2015-August-11 %9 Methods %+ Mr Maxime Chamberland,Univeristé de Sherbrooke,Centre de Recherche CHUS,Sherbrooke,Canada,m.chamberland@tue.nl %+ Mr Maxime Chamberland,Université de Sherbrooke,Computer Science Department, Faculty of Science,Sherbrooke,Canada,m.chamberland@tue.nl %+ Mr Maxime Chamberland,Université de Sherbrooke,Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Science,Sherbrooke,Canada,m.chamberland@tue.nl %# %! Tractography-informed resting-state fMRI connectivity %* %< %T 3D interactive tractography-informed resting-state fMRI connectivity %U https://www.frontiersin.org/articles/10.3389/fnins.2015.00275 %V 9 %0 JOURNAL ARTICLE %@ 1662-453X %X In the past decade, the fusion between diffusion magnetic resonance imaging (dMRI) and functional magnetic resonance imaging (fMRI) has opened the way for exploring structure-function relationships in vivo. As it stands, the common approach usually consists of analysing fMRI and dMRI datasets separately or using one to inform the other, such as using fMRI activation sites to reconstruct dMRI streamlines that interconnect them. Moreover, given the large inter-individual variability of the healthy human brain, it is possible that valuable information is lost when a fixed set of dMRI/fMRI analysis parameters such as threshold values are assumed constant across subjects. By allowing one to modify such parameters while viewing the results in real-time, one can begin to fully explore the sensitivity of structure-function relations and how they differ across brain areas and individuals. This is especially important when interpreting how structure-function relationships are altered in patients with neurological disorders, such as the presence of a tumor. In this study, we present and validate a novel approach to achieve this: First, we present an interactive method to generate and visualize tractography-driven resting-state functional connectivity, which reduces the bias introduced by seed size, shape and position. Next, we demonstrate that structural and functional reconstruction parameters explain a significant portion of intra- and inter-subject variability. Finally, we demonstrate how our proposed approach can be used in a neurosurgical planning context. We believe this approach will promote the exploration of structure-function relationships in a subject-specific aspect and will open new opportunities for connectomics.