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The current study provides an overview of quantity and quality of MRI data in a large developmental twin sample (N = 512, aged 7-9), and investigated to what extent scan quantity and quality were influenced by genetic and environmental factors. This was examined in a fixed scan protocol consisting of two functional MRI tasks, high resolution structural anatomy (3DT1) and connectivity (DTI) scans, and a resting state scan. Overall, scan quantity was high (88% of participants completed all runs), while scan quality decreased with increasing session length. Scanner related distress was negatively associated with scan quantity (i.e., completed runs), but not with scan quality (i.e., included runs). In line with previous studies, behavioral genetic analyses showed that genetics explained part of the variation in head motion, with heritability estimates of 29% for framewise displacement and 65% for absolute displacement. Additionally, our results revealed that subtle head motion (after exclusion of excessive head motion) showed lower heritability estimates (0-14%), indicating that findings of motion-corrected and quality-controlled MRI data may be less confounded by genetic factors. These findings provide insights in factors contributing to scan quality in children, an issue that is highly relevant for the field of developmental neuroscience.
Pubmed ID: 31170550
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Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.
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