An update on regional brain volume differences associated with mood disorders
Bibliographic record
Abstract
PURPOSE OF REVIEW: Structural brain changes are apparent in some magnetic resonance imaging studies of patients with mood disorders, but results are inconsistent. The focus of this review is to examine whether there are demographic or clinical characteristics of people with mood disorders that are associated with regional brain volume changes. A systematic search of the literature in English, from January 2004 to July 2005, was performed on MEDLINE. References cited in all reports were searched iteratively to identify missing studies. RECENT FINDINGS: Recent studies have focused on factors that might help to reconcile the divergent reports of regional brain volume changes in major depressive disorder and bipolar disorder. Small hippocampal volumes are apparent in patients with recurrent major depressive disorder, but not generally reported early in the course of adult onset depression. Small hippocampal volumes may be apparent in patients with childhood onset illness. Small hippocampal volumes are infrequently reported in bipolar disorder, but studies to date have not accounted for illness history or treatment status. Changes in amygdala volumes are inconsistently reported in patients with major depressive disorder or bipolar disorder. There are relatively fewer reports of other brain regions, including the areas of the frontal cortex and striatum. An extensive preclinical literature suggests that various psychotropic medications may have neurotrophic and neuroprotective effects, making documentation of treatment history essential. SUMMARY: Patients' age, sex, age at onset of disease, course of illness and treatment status may affect the detection of regional brain volume changes in people with mood disorders.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".