Structural Connectome Atlas Construction in the Space of Riemannian Metrics
This work addresses the challenge of connectome analysis for neuroscience researchers, but it appears incremental as it applies existing mathematical frameworks to a specific domain.
The authors tackled the problem of analyzing structural connectomes by representing them as Riemannian metrics in an infinite-dimensional manifold, and they demonstrated connectome registration and atlas formation using data from the Human Connectome Project.
The structural connectome is often represented by fiber bundles generated from various types of tractography. We propose a method of analyzing connectomes by representing them as a Riemannian metric, thereby viewing them as points in an infinite-dimensional manifold. After equipping this space with a natural metric structure, the Ebin metric, we apply object-oriented statistical analysis to define an atlas as the Fréchet mean of a population of Riemannian metrics. We demonstrate connectome registration and atlas formation using connectomes derived from diffusion tensors estimated from a subset of subjects from the Human Connectome Project.