This package shares code for web-based visualization of brain connectivity data, built using D3.js, a Javascript library for interactive documents. This should potentially work with any data that can be stored in a connectivity matrix or graph, that is, numerical measures defined for pairs of variables. For example, this could be measures of structural integrity between brain regions, or it could be something else, like functional connectivity or statistical parameters from a group analysis. Two different visualization approaches included here and illustrated above. The first is a chord diagram that visualizes brain regions on a circle with interior chords that connect regions with coloring to denote connectivity strength. The second is a matrix diagram that supports richer interaction, including querying individual values, adjusting colormaps, and including several parameters-of-interest. The chord diagram is ideal for sparse graphs, while the matrix is more useful for denser graphs.

The code only requires a web-server, and you can find live examples running here:

• https://cabeen.io/brain-matvis-d3/chord/
• https://cabeen.io/brain-matvis-d3/matrix/

The provided diagrams present data from a diffusion MRI study of normal aging adults. You can learn more about the data from the repository website and you can request access through GAAIN at the corresponding GAAIN partners page. To use your own data, you simply have to create JSON files that match the structure of the example.

If you find this useful in your research, we kindly ask that you cite the following abstract, which you can find included in the media directory:

Cabeen, R.P., Bastin, M.E. and Laidlaw, D.H., 2013. A 
diffusion MRI resource of 80 age-varied subjects with 
neuropsychological and demographic measures. In ISMRM, 
21st Scientific Meeting and Exhibition (No. 2138).

@inproceedings{cabeen2013diffusion,
  title={A diffusion MRI resource of 80 age-varied subjects 
    with neuropsychological and demographic measures},
  author={Cabeen, Ryan P and Bastin, ME and Laidlaw, DH},
  booktitle={ISMRM, 21st Scientific Meeting and Exhibition},
  number={2138},
  year={2013}
}

Author: Ryan Cabeen, [email protected]

Data collection and analysis for this project was supported by NIH grant number R01 EB004155. The dissemintation of this work is supported by the CZI Imaging Scientist Award Program, under grant number 2020-225670 from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation.