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Updated: Oct 7, 2026
Scanning Dos and Don'ts: Using Magnetic Resonance Imaging in Awake Children Aged 3 to 5 Years to Assess Brain Structure and Function
Published on: March 10, 2026
Age- and sex-divergent neurodevelopmental patterns revealed through structural magnetic resonance imaging features
O Kabenova1, R Zhulduzbayev2, I Brak3,4
1Department of Biophysics, Biomedicine and Neuroscience, Al-Farabi Kazakh National University, Almaty, Kazakhstan.
Introduction:
Brain maturation during childhood and adolescence involves complex structural changes that vary among individuals. Characterizing these trajectories is essential for understanding normative development and identifying deviations associated with neurological conditions.
Methods:
We analyzed structural magnetic resonance imaging data from 179 healthy participants aged 7-20 years. Cortical thickness, regional surface area, and regional brain volumes were assessed to characterize age-related morphometric patterns and sex differences. These features were also used to predict chronological age. Ten regression algorithms spanning regularized linear, Bayesian, kernel-based, and gradient-boosting approaches were evaluated using repeated age-stratified five-fold cross-validation.
Results:
Total gray matter volume decreased with age, whereas white matter volume increased, reflecting ongoing myelination and brain maturation. The caudate nuclei and nucleus accumbens showed age-related volume reductions, while cerebellar and brainstem volumes increased, suggesting continued maturation of motor and sensory systems. No significant age-related associations were observed for cortical surface area. In contrast, cortical thickness showed widespread age-related decreases, including in the superior temporal sulcus, anterior cingulate cortex, and prefrontal cortex, consistent with functional specialization. Males had significantly larger cortical, subcortical, and white matter volumes, as well as larger surface areas across multiple cortical regions. However, cortical thickness did not differ significantly by sex. A stacking ensemble achieved the best age-prediction performance, with an age-bias-corrected mean absolute error of 1.41 years. Despite the observed morphological sex differences, the corrected brain-age gap did not differ significantly between sexes.
Discussion:
These findings provide a region-specific reference for normative brain development in a Central Asian pediatric and adolescent sample and establish a preliminary framework for predicting age from standard brain morphometric measures. Independent replication in larger and more diverse samples is required to assess the generalizability of these findings.
