Examining the boundary sharpness coefficient as an index of cortical microstructure and its relationship to age and sex in autism spectrum disorder

Olafson, Emily; Bedford, Saashi A.; Devenyi, Gabriel A.; Tullo, Stephanie; Park, Min Tae M.; Parent, Olivier; Anagnostou, Evdokia; Baron‐Cohen, Simon; Bullmore, Edward T.; Chura, Lindsay R.; Craig, Michael C.; Ecker, Christine; Floris, Dorothea L.; Holt, Rosemary; Lenroot, Rhoshel; Lerch, Jason P.; Lombardo, Michael; Murphy, Declan; Raznahan, Armin; Ruigrok, Amber; Spencer, Michael D.; Suckling, John; Taylor, Margot J.; Lai, Meng‐Chuan; Chakravarty, M. Mallar

doi:10.1101/2020.07.09.196212

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“…The sensitivity of automated cortical measurements to scan-specific field distortions and to small movement artifacts has already been established ( Reuter et al, 2015 ), and the need for a quality control of pipeline outputs is now considered necessary as failing to do so can significantly alter findings when it comes to developmental trajectories ( Ducharme et al, 2016 ; Olafson et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Maturational trajectories of pericortical contrast in typical brain development

et al. 2021

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In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample ( n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1–3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories.

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Section: Methodsmentioning

confidence: 99%