Recent technological advances have introduced the potential for non-invasively identifying and tracking normal and abnormal development of cortical myelin in vivo. These technologies assume that MRI-based signals across the cortical gray matter mirror myelin content. This myelin-inclusive signal is assessed by optimizing T1-weighted protocols for intracortical dynamic ranges (Bock et al. 2009; Bock et al. 2013; Fischl et al. 2004; Lutti et al. 2014; Rowley et al. 2017), modeling the short T2 relaxation component for water trapped between myelin sheaths using multi-echo T2 maps (Arshad et al. 2017; MacKay et al. 1994; Whittall et al. 1997), or computing the ratio of T1-weighted and T2-weighted MRIs (Ganzetti et al. 2014; Glasser and Van Essen 2011; Glasser et al. 2013; Glasser et al. 2014; Grydeland et al. 2013; Grydeland et al. 2016; Shafee et al. 2015). Computing the ratio based on common T1-weighted and T2-weighted MRI acquisition protocols (Glasser and Van Essen 2011; Glasser et al. 2013; Glasser et al. 2014) lays the foundation for repurposing existing MRI data to estimate the temporal order of normal regional cortical development throughout adolescence to
