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Title: A browser-based tool for visualization and analysis of diffusion MRI data

Abstract

Human neuroscience research faces several challenges with regards to reproducibility. While scientists are generally aware that data sharing is important, it is not always clear how to share data in a manner that allows other labs to understand and reproduce published findings. Here we report a new open source tool, AFQ-Browser, that builds an interactive website as a companion to a diffusion MRI study. Because AFQ-Browser is portable—it runs in any web-browser—it can facilitate transparency and data sharing. Moreover, by leveraging new web-visualization technologies to create linked views between different dimensions of the dataset (anatomy, diffusion metrics, subject metadata), AFQ-Browser facilitates exploratory data analysis, fueling new discoveries based on previously published datasets. In an era where Big Data is playing an increasingly prominent role in scientific discovery, so will browser-based tools for exploring high-dimensional datasets, communicating scientific discoveries, aggregating data across labs, and publishing data alongside manuscripts.

Authors:
ORCiD logo [1];  [2];  [3];  [4]; ORCiD logo [5]
  1. Univ. of Washington, Seattle, WA (United States). Inst. for Learning & Brain Sciences and Department of Speech and Hearing Sciences
  2. Univ. of Washington, Seattle, WA (United States). Dept. of Physics
  3. Univ. of Washington, Seattle, WA (United States). Dept of Chemical Engineering
  4. Univ. of Washington, Seattle, WA (United States). Inst. for Learning & Brain Sciences, Department of Speech and Hearing Sciences, and eScience Institute
  5. Univ. of Washington, Seattle, WA (United States). eScience Institute
Publication Date:
Research Org.:
Krell Institute, Ames, IA (United States)
Sponsoring Org.:
USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1529919
Grant/Contract Number:  
FG02-97ER25308
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES

Citation Formats

Yeatman, Jason D., Richie-Halford, Adam, Smith, Josh K., Keshavan, Anisha, and Rokem, Ariel. A browser-based tool for visualization and analysis of diffusion MRI data. United States: N. p., 2018. Web. doi:10.1038/s41467-018-03297-7.
Yeatman, Jason D., Richie-Halford, Adam, Smith, Josh K., Keshavan, Anisha, & Rokem, Ariel. A browser-based tool for visualization and analysis of diffusion MRI data. United States. https://doi.org/10.1038/s41467-018-03297-7
Yeatman, Jason D., Richie-Halford, Adam, Smith, Josh K., Keshavan, Anisha, and Rokem, Ariel. Mon . "A browser-based tool for visualization and analysis of diffusion MRI data". United States. https://doi.org/10.1038/s41467-018-03297-7. https://www.osti.gov/servlets/purl/1529919.
@article{osti_1529919,
title = {A browser-based tool for visualization and analysis of diffusion MRI data},
author = {Yeatman, Jason D. and Richie-Halford, Adam and Smith, Josh K. and Keshavan, Anisha and Rokem, Ariel},
abstractNote = {Human neuroscience research faces several challenges with regards to reproducibility. While scientists are generally aware that data sharing is important, it is not always clear how to share data in a manner that allows other labs to understand and reproduce published findings. Here we report a new open source tool, AFQ-Browser, that builds an interactive website as a companion to a diffusion MRI study. Because AFQ-Browser is portable—it runs in any web-browser—it can facilitate transparency and data sharing. Moreover, by leveraging new web-visualization technologies to create linked views between different dimensions of the dataset (anatomy, diffusion metrics, subject metadata), AFQ-Browser facilitates exploratory data analysis, fueling new discoveries based on previously published datasets. In an era where Big Data is playing an increasingly prominent role in scientific discovery, so will browser-based tools for exploring high-dimensional datasets, communicating scientific discoveries, aggregating data across labs, and publishing data alongside manuscripts.},
doi = {10.1038/s41467-018-03297-7},
journal = {Nature Communications},
number = 1,
volume = 9,
place = {United States},
year = {2018},
month = {3}
}

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Cited by: 33 works
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Figures / Tables:

Fig. 1 Fig. 1 : Development of the corticospinal tract, arcuate fasciculus, and cingulum. Tract profiles of mean diffusivity (top) and fractional anisotropy (bottom) are shown for the left hemisphere corticospinal tract (CST, orange), arcuate fasciculus (blue), and cingulum (green). Splitting the group by age, and selecting 3 bins, displays mean linesmore » of three groups: 8–15 (red), 15–30 (purple), and 30–50 (blue). For the CST, there is a region that shows a decrease in FA with development, and this location of the tract is highlighted on the plot using the “brushable tracts” feature (shaded gray box). The linked view in the anatomy displays the portion of the CST that is brushed in the plot demonstrating that this effect occurs in the anatomical portion of the CST known as the centrum semiovale, adjacent to the arcuate fasciculus. This linked visualization provides a connection between the data plots and the 3D Anatomy. Data and MATLAB code are available at https://github.com/YeatmanLab/AFQ-Browser_data (see Figure2_Development.m) and running AFQ-Browser instance at: https://YeatmanLab.github.io/AFQBrowser-demo/)« less

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Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.