“…DTI is a noninvasive tool with a high sensitivity to changes in myelination, and axonal density and diameter, that can be used to investigate the pathophysiology underlying unfavorable neurodevelopmental alterations in the preterm brain ( Rogers et al, 2016 ). While previous reports of altered WM in preterm children have been obtained using univariate analytical methods with high exploratory power – e.g., region of interest (ROI)-based analysis ( Caldinelli et al, 2017 , Dodson et al, 2017 , Murray et al, 2016 ), tract-based spatial statistics (TBSS) ( Coker-Bolt et al, 2016 , Collins et al, 2019 , Hollund et al, 2018 , Jurcoane et al, 2016 , Murner-Lavanchy et al, 2018 ), and tensor-based morphometry (TBM) ( Rajagopalan et al, 2017 ) – these methods may be too conservative to detect subtle, spatially distributed differences because they require corrections for multiple comparisons to control the expected false discovery rate (FDR) ( Ecker et al, 2010b ). By contrast, a multivariate pattern analysis (MVPA) (e.g., support vector machine (SVM) and logistic regression models) accounts for interregional correlations and features increased sensitivity to abnormalities in neural systems ( Ecker et al, 2010 , Li et al, 2014 , Little and Beaulieu, 2019 , Schadl et al, 2018 ).…”