Association between Adolescent Brain Morphometry and Cognitive Function: Insights from a Cross-Sectional Analysis of ABCD Data from 9 to 15 Years Old

Abstract

AbstractDuring the adolescent developmental stage, significant changes occur in both brain structure and cognitive function. Brain structure serves as the foundation for cognitive function and can be accurately assessed using a comprehensive set of brain cortical and subcortical morphometry measures. Exploring the association between whole-brain morphometry and cognitive function during adolescence can help elucidate the underlying relationship between brain structural development and cognitive development. Despite extensive research in this area, previous studies have two main limitations. Firstly, they often use a limited number of brain morphometry measures, which do not provide a comprehensive representation of brain structure. Secondly, most previous studies rely on relatively small sample sizes, increasing the risk of sampling error, low statistical power, and even overestimation of effects. To address these limitations, we analyzed the Adolescent Brain Cognitive Development (ABCD) dataset, which includes 8543 subjects (13,992 scans) aged 9-15 years. These scans were categorized into six groups with one-year intervals based on their ages for independent age-specific analysis. We computed 16 brain regional morphometry measures derived from Structural Magnetic Resonance Imaging (SMRI), Diffusion Tensor Imaging (DTI), and Restriction Spectrum Imaging (RSI), and integrated them with morphometric similarity networks (MSNs). This approach enabled us to compute 16,563 morphometry measures encompassing brain region, connection, and hub aspects. Subsequently, these measures were input into a robust large-scale computational model to investigate their relationship with cognitive performances. We found that brain regions making the most significant contributions to cognitive function during adolescence, and those exhibiting the greatest variability in their contributions over time, were primarily situated in the frontal and temporal lobes. Subcortex were the least involved. We also observed strong correlations between key brain morphometry measures related to different cognitive performances within same domain. Furthermore, SMRI measures demonstrated stronger associations with cognitive performances compared to DTI and RSI measures. Overall, our study aims to facilitate a comprehensive and reliable understanding of the association between adolescent brain morphometry and cognitive function.