At time 1 and time 2, structural magnetic resonance images were acquired on Siemens 1.5 T systems. Cortical reconstruction and volumetric segmentation were performed with the FreeSurfer image analysis suite (http://surfer.nmr.mgh.harvard.edu ). Diffusion-weighted data were analyzed using TRActs Constrained by UnderLying Anatomy [TRACULA; (64 (link))], an automatic reconstruction tool for identifying major white matter tracts from diffusion-weighted images and measuring the diffusion within these tracts at a set number of locations. The acquisition sequences for gray matter data differed in minor ways across acquisitions. Following recommendations (60 (link), 65 (link)), we documented that there was no evidence of heteroskedasticity before completing our longitudinal analysis. Please see the Supplementary Materials for details about data acquisition, analysis, and tests of heteroskedasticity.
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Longitudinal Brain Imaging and Diffusion Analysis
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Corresponding Organization : University of North Carolina at Chapel Hill
Other organizations : Bryn Mawr College, Boston Children's Hospital, University of Toronto, Vanderbilt University, Yale University, University of Maryland, College Park, Tulane University, Harvard University
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Variable analysis
independent variables
- Time (time 1 and time 2)
- Cortical reconstruction and volumetric segmentation
- Diffusion-weighted data analysis using TRACULA
- Siemens 1.5 T systems for structural magnetic resonance imaging
- FreeSurfer image analysis suite for cortical reconstruction and volumetric segmentation
- TRACULA for diffusion-weighted data analysis
- No evidence of heteroskedasticity before completing the longitudinal analysis
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