Different parts of the brain share and transmit Information through long-range connections that connect nerve cells in each part of the brain with nerve cells in other brain areas. These connections form bundles of nerve cells, and these bundles comprise a complex and expansive network within the human brain. Understanding these brain networks and their relation to the way that the brain Implements perception and cognition, and understanding how these networks break down In various brain disorders are major challenges In contemporary neuroscience. Diffusion Magnetic Resonance Imaging (dMRI) is the only currently available method to measure these connections In the living human brain non-invasively. The DIPY (Diffusion imaging in Python) project Is an International community-based effort to implement open-source software for analysis and Interpretation of dMRI data. The research and development work proposed here aims to expand the development work in DIPY, and to help share this work more widely with the community of researchers that use dMRI In their research. The project proposes to Implement and share new algorithms for analysis of dMRI data, and to share several important new datasets that will serve as benchmarks for ongoing methods development; it will support the development of software tools for cloud-computing with these data and it will facilitate the participation of a global community of scientists in the development of the software. Furthermore, it will support its wide dissemination to relevant research and enable computation on large datasets.
Diffusion-weighted Magnetic Resonance Imaging (dMRI) is the only currently available method to measure the properties of brain connections In living human brains. This method Is already widely used in clinical tests for a variety of brain disorders. Computational methods that we propose to develop here will accelerate research using dMRI for clinical application and increase our ability to make inferences from DMRI data.
