Adolescent depression and brain development: evidence from voxel-based morphometry
Bibliographic record
Abstract
Background: Investigating adolescents and young adults may provide a unique opportunity to understand developmental aspects of the neurobiology of depression. During adolescence, a considerable physiologic reorganization of both grey and white matter of the brain takes place, and it has been suggested that differences in grey-matter volumes during adolescence may reflect different maturational processes. Methods: We investigated grey-matter volumes in a comparatively large sample (n = 103) of adolescents and young adults (aged 12 to 27 years), 60 of them with a diagnosis of current depression. Results: Replicating previous studies, we found a clear wholebrain effect of age: the older the participants, the lower their global grey-matter volumes, particularly in the paracingulate and prefrontal cortices. Contrasting depressed and healthy youth in a whole-brain approach, we found greater grey-matter volumes in the dorsolateral prefrontal cortex of those with depression. Furthermore, a region-of-interest analysis indicated lower grey-matter volumes in the hippocampus in participants with depression compared with healthy controls. Limitations: The present study was limited because of a skewed sex distribution, its cross-sectional design and the fact that some participants were taking an antidepressant. Conclusion: During adolescence, restructuring of the brain is characterized by marked decreases in prefrontal grey-matter volumes, interpreted as a correlate of brain maturation. Findings of greater volumes in the prefrontal cortex, particularly in younger adolescents with depression, may suggest that these participants were more prone to delayed brain maturation or increased neuroplasticity. This finding may represent a risk factor for depression or constitute an effect of developing depression.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".