Neurochemical brain imaging studies in bipolar disorder
Bibliographic record
Abstract
OBJECTIVE: We reviewed the neurochemical brain imaging literature in bipolar disorder to synthesize the findings and provide directions for future research. METHODS: Relevant articles were retrieved by computerized Medline Ovid search (up to and including 2002) and complemented by bibliographic manual searches of reviews known to the authors. RESULTS: PET and SPECT studies in bipolar disorder have identified changes in various aspects of dopaminergic and serotonergic neurotransmission. Ligands for other neurotransmitters are actively being pursued. Spectroscopy studies have utilized a number of MRS-sensitive nuclei to chemically 'biopsy' the brain of patients with bipolar disorder. Few consistent findings are emerging, however, the majority of nuclei that can be measured are not directly related to the pathophysiology of the disorder. CONCLUSIONS: Brain imaging has the potential to unravel the neurochemical underpinnings of bipolar disorder, however, there is a continuing need for clinical, technical and methodological sophistication.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".