Hello-- Our dataset has 130ish scans with a bad temporal lobe artifact and a minor parietal lobe artifact. This artifact has affected the normalization and thus the white matter/gray matter selection, which we've manually fixed. However, the temporal lobe artifact is bad enough that chunks of data are missing in the surfaces. How will this affect curvature and LGI? We saw we can constrain our cortical thickness analyses to an ROI using mri_glmfit. Can we do this with curvature and LGI, and will having chunks of data missing affect readings elsewhere in the brain?
Thank you, Erin Browning
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