The developing human brain: age‐related changes in cortical, subcortical, and cerebellar anatomy
Bibliographic record
Abstract
INTRODUCTION: This study is the first to characterize normal development and sex differences across neuroanatomical structures in cortical, subcortical, and cerebellar brain regions in a single large cohort. METHODS: One hundred and ninety-two magnetic resonance images were examined from 96 typically developing females and 96 age-matched typically developing males from 4 to 18 years of age. Image segmentation of the cortex was conducted with CIVET, while that of the cerebellum, hippocampi, thalamus, and basal ganglia were conducted using the MAGeT algorithm. RESULTS: Cortical thickness analysis revealed that most cortical regions decrease linearly, while surface area increases linearly with age. Volume relative to total cerebrum followed a quadratic trend with age, with only the left supramarginal gyrus showing sexual dimorphism. Hippocampal relative volume increased linearly, while the thalamus, caudate, and putamen decreased linearly, and the cerebellum did not change with age. The relative volumes of several subcortical subregions followed inverted U-shaped trends that peaked at ~12 years of age. Many subcortical structures were found to be larger in females than in males, independently of age, while others showed a sex-by-age interaction. CONCLUSION: This study provides a comprehensive assessment of cortical, subcortical, and cerebellar growth patterns during normal development, and draws attention to the role of sex on neuroanatomical maturation throughout childhood and adolescence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".