Freesurfer Dataset

<p>This is simulated data created for test and demonstration purposes for decentralized algorithms for <a href="https://github.com/trendscenter/coinstac">COINSTAC</a>.</p> <p>There is a CSV file with the two columns of demographic data and a column of filenames containing the volumes of the regions of interest (ROIs) of the subjects&#39; brains. These volumes are typically produced by segmentation using <code>recon-all</code> in the <a href="https://surfer.nmr.mgh.harvard.edu">FreeSurfer</a> program.</p> <p>Data dictionary</p> <ul> <li>freesurferfile: filename associated with subject containing volumes of ROIs, as typically produced by FreeSurfer segmentation</li> <li>age (float): subject&#39;s age</li> <li>isControl (Boolean): whether subject was a control (True) or had a medical condition (False)</li> </ul> <p>There are a total of 72 subjects.</p> <p>The volumes were simulated with equations of the following form:</p> <p>y = B0 + B1 x age + B2 x isControl + B3 x e</p> <p>where e ~ N(0,1)</p> <p>Each volume was given a fixed intercept (B0) (e.g., 48466.3 for Right-Cerebellum-Cortex). The effect of age (B1) was selected randomly from the range [-300, -100], and the effect of diagnosis (isControl, B2) was selected randomly from the range [500, 1000] for each pseudo subject. A standard unit Gaussian noise multiplied by a random index from the range [1800, 2200] was added subsequently.</p> <p>This data was created on Feb 2, 2017 by Jing Ming at the Mind Research Network and presented in this paper:</p> <p>Ming J, Verner E, Sarwate A et al. COINSTAC: Decentralizing the future of brain imaging analysis [version 1; peer review: 2 approved]. F1000Research 2017, 6:1512 (<a href="https://doi.org/10.12688/f1000research.12353.1">https://doi.org/10.12688/f1000research.12353.1</a>)</p>