All MRI data were processed individually through the automated subcortical segmentation and cortical parcellation tool in FreeSurfer, version 5.3 (Martinos Center for Biomedical Imaging, Charlestown, MA, USA) (Fischl et al. 2002 (link); Fischl 2012 (link)). To increase the probability that each discrete region is correctly labelled, FreeSurfer considers aspects of the collected data and general aspects of MRI such as signal intensity of different regions, producing accurate and reliably segmentation (Jovicich et al. 2009 (link)). The software produces indices of area, thickness, and volume for cortical structures, and volume for subcortical structures, resulting in 274 unique neuroanatomical features. White matter, gray matter, and pial matter boundaries were reviewed in each subject for gross artifacts and errors in segmentation by the authors (LS and JB).
Multimodal Neuroimaging Analysis Pipeline
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Corresponding Organization : University of Florida
Other organizations : University of Florida Health
Variable analysis
- None explicitly mentioned
- Thickness
- Volume for cortical structures
- Volume for subcortical structures
- Philips Achieva 3T MRI scanner
- 32-channel head coil
- 176 sagittal slices (1 mm thickness)
- TR = 7.2 ms
- TE = 3.2 ms
- FA = 8°
- FOV = 240 mm
- Voxel size = 1 mm³
- Automated subcortical segmentation and cortical parcellation tool in FreeSurfer, version 5.3
- None explicitly mentioned
- None explicitly mentioned
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