All software is open-source and freely distributed on the    Yeatman Lab github page

Open source code is essential for reproducible science and we are committed to documenting and distributing all the software that we develop for our research. Each of these projects represents the ideas and code of many collaborators.  We welcome comments, feedback and contributions from anyone that finds this software useful.

Automated Fiber Quantification (AFQ)

AFQ is designed to automatically identify major fiber tracts and quantify tissue properties along their trajectories. The result is a “Tract Profile” of MRI parameters that can be used to study white matter tissue properties in healthy brains or quantify abnormalities in diseased brains. In the future we hope to be able to automatically identify abnormalities in an individual and quantify that individual’s risk for various functional consequences. The software is described in a recent PLoS ONE manuscript where we apply it to identify developmental abnormalities and predict developmental outcomes in children born prematurely.

3D Visualization

High quality three dimensional visualization is essential for analyzing and understanding brain circuits. I have written a software package for building models of an individual’s cortical surface and white matter tracts to help visualize the functional and structural properties of brain circuits in 3D. The 3Dmesh toolbox is now included in the AFQ software package and can be downloaded from the lab github site.

Lifespan Maturation and Degeneration of Human Brain White Matter

I have released a set of functions for modeling white matter maturation and degeneration to accompany the recent Nature Communications publication:

Yeatman J. D., Wandell B.A., Mezer A. (2014). Lifespan Maturation and Degeneration of Human Brain White matter. Nature Communications.

Within the “lifespan repository” is code and data to reproduce each computation and figure from the manuscript.

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