摘要：The human brain is a complex system that can be efciently represented as a network of structural connectivity. Many imaging studies would beneft from such network information, which is not always available . In this work, we present a whole-brain multi-scale structural connectome atlas . This tool has been derived from a cohort of 66 healthy subjects imaged with optimal technology in the setting of the Human Connectome Project . From these data we created, using extensively validated difusion-data processing, tractography and gray-matter parcellation tools, a multi-scale probabilistic atlas of the human connectome . In addition, we provide user-friendly and accessible code to match this atlas to individual brain imaging data to extract connection-specifc quantitative information . This can be used to associate individual imaging fndings, such as focal white-matter lesions or regional alterations, to specifc connections and brain circuits . Accordingly, network-level consequences of regional changes can be analyzed even in absence of difusion and tractography data . This method is expected to broaden the accessibility and lower the yield for connectome research .
