paper.md

title	tags	authors	affiliations	date	bibliography
A software ecosystem for white matter tractometry	Preprint Jupyter Book Reproducible article Neuroscience	name affiliation John Kruper 1, 2 name affiliation Ariel Rokem 1, 2	name index Department of Psychology, University of Washington, Seattle, WA, USA 1 name index eScience Institute, University of Washington, Seattle, WA, USA 2	15 October 2024	paper.bib

Summary

Tractometry uses diffusion-weighted magnetic resonance imaging (dMRI) to assess the physical properties of long-range brain connections [@Yeatman2012AFQ]. We present an integrative ecosystem of software that performs all steps of tractometry: post-processing of dMRI data, delineation of major white matter pathways, and modeling of the tissue properties within them. This ecosystem also provides tools that extract insights from these measurements, including novel implementations of machine learning and statistical analysis methods that consider the unique structure of tractometry data [@RichieHalford2021SGL,@Muncy2022GAMs], as well as tools for visualization and interpretation of the results [@Yeatman2018AFQBrowser,@Kruper2024-ke]. Taken together, these open-source software tools provide a comprehensive environment for the analysis of dMRI data.

Acknowledgements

This work was funded by National Institutes of Health grants MH121868, MH121867, and EB027585, as well as by National Science Foundation grant #1934292. Software development was also supported by the Chan Zuckerberg Initiative's Essential Open Source Software for Science program, the Alfred P. Sloan Foundation and the Gordon & Betty Moore Foundation.

References