Structural changes in the hippocampus in major depressive disorder: contributions of disease and treatment
Bibliographic record
Abstract
BACKGROUND: Previous magnetic resonance imaging (MRI) studies of patients with major depressive disorder (MDD) have consistently shown bilateral and unilateral reductions in hippocampal volume relative to healthy controls. Recent structural MRI studies have addressed the question of whether changes in the volume of hippocampal subregions may be associated with MDD. METHODS: We used a comprehensive and reliable 3-dimensional tracing protocol that enables delineation of hippocampal subregions (head, body, tail) to study changes in the hippocampus of patients with MDD. We recruited 39 MDD patients (16 medicated, 23 unmedicated) and 34 healthy age- and sex-matched controls. We acquired images using a magnetization-prepared rapid acquisition gradient echo sequence on a 1.5-T scanner with a spatial resolution of 1.5 mm x 0.5 mm x 0.5 mm. We performed volumetric analyses, blinded to diagnosis, using the interactive software package Display. All volumes were adjusted for intracranial volume. RESULTS: We found a significant reduction in the volume of the hippocampal tail bilaterally, right hippocampal head and right total hippocampus in MDD patients. Medicated MDD patients showed increased hippocampal body volume compared with both healthy controls and unmedicated patients. LIMITATIONS: This study was cross-sectional. Further prospective studies are needed to determine the direct effect of antidepressant treatment. CONCLUSION: Our results suggest that decreased hippocampal tail and hippocampal head volumes could be trait changes, whereas hippocampal body changes may be dependent on treatment. We showed that long-term antidepressant treatment may affect hippocampal volume in patients with MDD.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".