Adolescence is a time of continued cognitive and emotional evolution occurring with continuing brain development involving synaptic pruning and cortical myelination. The hypothesis of this study is that heavy myelination occurs in cortical regions with relatively direct, predetermined circuitry supporting unimodal sensory or motor functions and shows a steep developmental slope during adolescence (12–21 years) until young adulthood (22–35 years) when further myelination decelerates. By contrast, light myelination occurs in regions with highly plastic circuitry supporting complex functions and follows a delayed developmental trajectory. In support of this hypothesis, cortical myelin content was estimated and harmonized across publicly available datasets provided by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) and the Human Connectome Project (HCP). The cross-sectional analysis of 226 no-to-low alcohol drinking NCANDA adolescents revealed relatively steeper age-dependent trajectories of myelin growth in unimodal primary motor cortex and flatter age-dependent trajectories in multimodal mid/posterior cingulate cortices. This pattern of continued myelination showed smaller gains when the same analyses were performed on 686 young adults of the HCP cohort free of neuropsychiatric diagnoses. Critically, a predicted correlation between a motor task and myelin content in motor or cingulate cortices was found in the NCANDA adolescents, supporting the functional relevance of this imaging neurometric. Furthermore, the regional trajectory slopes were confirmed by performing longitudinally consistent analysis of cortical myelin. In conclusion, coordination of myelin content and circuit complexity continues to develop throughout adolescence, contributes to performance maturation, and may represent active cortical development climaxing in young adulthood.
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This work was funded by grants from the U.S. National Institute on Alcohol Abuse and Alcoholism: AA021697, AA005965, AA010723, AA017168.
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None of the authors have conflicts of interest with the reported data or their interpretation.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
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Myelin content with respect to the original HCP data
The data release S900 of the Human Connectome project (HCP) provided for each subject the output of the minimal processing pipeline (Glasser et al. 2013), which included the supratentorial volume and the myelin content scores along the midthickness surface (i.e., the surface with equal distance to pial and white matter) based on the raw MRI data (i.e., 0.7 mm isotropic resolution). For each voxel inside the cortical gray matter, the pipeline computed a myelin content score by the ratio between T1-weighted and T2-weighted MRI (Glasser and Van Essen 2011). These voxel-based myelin scores were then mapped to each vertex of the midthickness surface by computing their average with respect to a cylinder centered on that vertex. The myelin score at this step is referred to as the raw myelin content. To correct for residual bias field of the raw myelin content (Glasser et al. 2013), a 14.14 mm Gaussian filter kernel was applied to the vertex-wise values, the resulting low frequency patterns of the myelin content scores were then subtracted from that of the average myelin content across the Conte69 subjects (the reference myelin content) (Glasser and Van Essen 2011), and the difference was then added to the vertex-wise values. This score is called the normalized myelin content as the myelin distribution is normalized to the reference. Finally, the midthickness surface encoding the normalized myelin content was mapped onto the 2 mm HCP template (Glasser et al. 2013), which encoded each hemisphere as a sphere defined by a 2 mm standard CIFTI grayordinate space comprising 32000 vertices (Glasser et al. 2013).
Figures 8 and 9 reveal findings that are consistent with respect to the young adults at the lower resolution (see Figs. 4 and 5). Compared with the lower resolution, myelin content computed with respect to the original resolution generally varied less across age and resulted in significant age-dependent regions that were larger in size. Table 6 reaffirms the finding that age effects (βage) were less steep for areas 4,23c, and p24’ compared with those of adolescents (see Table 2). Furthermore, the age effects were bilaterally significant for areas 4 and p24’.
Correlating average regional normalized myelin content and grooved pegboard test scores
For each region with significant age effects, an Independent Mediation Model tested whether the effect of age (independent variable) on the pegboard test scores (dependent variable) was mediated by the average regional normalized myelin content (intermediary variable). To measure the indirect effect, the regional and performance scores were first applied to a linear regression model with the confounding factors being sex, svol, site, ethnicity, and handedness (L/R). Separately for each hand, the residual scores and age were applied to the Independent Mediation Model. For each effect, the normalized βM value was computed by dividing the β value of the effect divided with the β value of the direct (unmediated) effect (cD) between age and the pegboard score. The P value of an effect was then inferred from Permutation testing (Boca et al. 2014) of the BRAVO toolbox V.2.0 (https://sites.google.com/site/bravotoolbox; iterations: 5000; one-sided t-test) applied to the normalized βM value. The summary of that analysis is shown in Table 7.
In the NCANDA group, the relation between age and pegboard scores was most strongly mediated by the myelin content of areas 4 [L], p24’ [R] and 4 [R] (where [L] denotes left and [R] denotes right) for both the dominant and non-dominant hand. All three right hemisphere regions showed greater indirect effects for the non-dominant than the dominant hand. Furthermore, the regions associated with significant direct effects of the myelin on the performance scores (Path bX) agreed with those of the Pearson correlation (Table 3) with the exception of area 23c [R] on the Dominant hand scores, whose P value on the intermediate model was right below the significance threshold (P = 0.048).
Validating longitudinal myelin computation
The longitudinal approach improved the reliability of estimating normalized myelin content compared with the cross-sectional approach when applied to the 185 adolescents of the NCANDA data set who participated three times (Fig. 10). To verify this finding, the analysis was repeated with respect to travelling human phantoms.
Specifically, the difference in myelin content was measured between scan pairs, where each scan pair consisted of scans of the same subject that were either acquired at both sites (i.e., NCANDA collection site P and O) within 30 days (inter-site scan pair; average number of days between visits was 22.3 days) or acquired at the same site within a day (intra-site scan pair) according to the NCANDA scanning protocol. The data set contained a total of 11 inter-site scan pairs from 3 human phantoms (two women [age 30 and 64], one man [age 41]) and 3 intra-site scan pairs from a single human. The raw myelin content of areas 4, 23c and p24’ was computed using the cross-sectional approach (i.e., compute the scores independently for each visit) and the differences in the scores across the scans was computed. The procedure was then repeated for the normalized myelin content generated by the cross-sectional and longitudinal approach.
For bihemispheric areas 4, 23c and p24’, the longitudinal approach showed lower mean, standard deviation, and maximum differences in the normalized myelin content within the inter- and intra-site scan pairs than estimating the normalized myelin content independently for each visit (i.e., cross-sectional approach; Fig. 11 and Table 8). Visual comparison of myelin maps associated with the same human phantom confirmed the previous findings as the normalized myelin content across scans was very similar when computed by the longitudinal approach but showed inconsistencies when produced by the cross-sectional approach (see arrows in Fig. 12). The least reliable score was the raw myelin content generated by the cross-sectional approach.
Effects of normalization
As shown in the Fig. 13, all trajectories of the normalized myelin content of the entire cortex and area 4 and p24, had smaller variances than those of the raw myelin content, which indicates that much of the between-subject variance in the raw myelin content was due to low frequency bias most likely caused by scanner or coil loading variability (Glasser et al. 2013). Furthermore, the plots supported the cortical myelin development hypothesis visualized in Fig. 3.
Effects of cortical folding pattern removal
To study the effect of cortical folding pattern on our findings, the mean curvature along the cortical surface was regressed out from the normalized myelin content of the NCANDA cohort and the analysis for identifying cohort-specific developmental patterns was applied to residual myelin content (Fig. 14). The entire process was repeated regressing out convexity instead of curvature. In both experiments, regression had little effect on the findings with the bihemispheric areas 4, 23c and p24’, revealing again significant age effects.
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Kwon, D., Pfefferbaum, A., Sullivan, E.V. et al. Regional growth trajectories of cortical myelination in adolescents and young adults: longitudinal validation and functional correlates. Brain Imaging and Behavior 14, 242–266 (2020). https://doi.org/10.1007/s11682-018-9980-3
- Cortical myelin
- Early adulthood