Community-supported open-source software for computational neuroanatomy

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This project catalyzes research on brain networks by developing computational methods and software tools for analysis of diffusion MRI (dMRI) data and validating them in vivo. Understanding brain networks and their relation to neural computation is a major challenge in contemporary neuroscience. The proper function of brain networks is also inextricably tied to neurological, cognitive and psychiatric health. The networks that connect distinct regions in the brain are composed of large bundles that contain the axons of millions of neurons. DMRI is the only currently available method to measure the trajectory and physical properties of these bundles in the human brain non-invasively and a large body of research using dMRI has substantially contributed to our understanding of the way in which differences in brain connections contribute to individual differences across a spectrum of behaviors and clinical conditions. Progress in research and methods development has also translated into increasing use of dMRI in clinical applications. The project is led by the founders of the Diffusion Imaging in Python (DIPY) software project who have been working to invigorate the neuroimaging user and developer community by developing, implementing, disseminating, and maintaining important software tools. The proposed project pursues a next generation phase of development, in which the overall objective is to generate a platform to better utilize dMRI data in accordance with BRAIN 2.0 targets. To address current barriers to progress, we plan to address the following aims in the current proposal: Aim 1 will develop new tractometry methods that enhance the interpretability of dMRI data; Aim 2 will introduce new pre-processing algorithms including methods for susceptibility correction; Aim 3 will focus on improving computational performance using parallel computing within a single node (e.g., via use of graphical processing units) and across nodes (i.e., distributed computing); Aim 4 will focus on the validation of DIPY methods using publicly available human and non-human primate data. Overall, this work will enable impactful brain research and will facilitate subsequent clinical adoption of advanced computational methods using dMRI data.