Abstract #1458

Mapping the Human Connectome at Multiple Scales with Diffusion Spectrum MRI

Leila Cammoun¹, Xavier Gigandet¹, Olaf Sporns², Jean-Philippe Thiran¹, Kim Q. Do³, Philippe Maeder⁴, Reto Meuli⁴, Patric Hagmann^1,4

¹Signal Processing Laboratory 5, Ecole Polytechnique Fdrale de Lausanne, Lausanne, VD, Switzerland; ²Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA; ³Center of Psychiatric Neuroscience, University Hospital Center and University of Lausanne (CHUV), Lausanne, VD, Switzerland; ⁴Department of Radiology, University Hospital Center and University of Lausanne (CHUV), Lausanne, VD, Switzerland

We propose to map the human connectome by constructing normalized whole-brain structural connection matrices derived from diffusion spectrum MRI tractography at 5 different scales. These connection matrices are then examined across scales for several important network characteristics. We show that key network measures can be robustly estimated across multiple scales with results that are consistent with previous single-scale investigations. In particular, we confirm that cortical networks exhibit exponential distributions of node degree and fiber densities, robust small world characteristics, as well as consistent estimates for node centrality at all scales examined.