Cerebellar Morphological Differences in Bipolar Disorder Type I
Bibliographic record
Abstract
Abstract Background The neural underpinnings of bipolar disorder (BD) remain poorly understood. The cerebellum is ideally positioned to modulate emotional regulation circuitry yet has been understudied in BD. Previous studies have suggested differences in cerebellar activity and metabolism in BD, however findings on cerebellar structural differences remain contradictory. Methods We collected 3T anatomical MRI scans from participants with (N = 131) and without (N = 81) BD type I. Differences in cerebellar volumes were assessed along with factors that influence the results. Results The cerebellar cortex was smaller bilaterally in participants with BD. Polygenic propensity score (bipolar N = 103, control N = 64) did not predict any cerebellar volumes, suggesting that non-genetic factors may have greater influence on the cerebellar volume difference we observed in BD. Cerebellar white matter volumes increased with more adverse childhood events, but we did not observe any associations with parental psychiatric illness. We also evaluated time from onset and symptom burden and found no associations with cerebellar volumes, suggesting neurodevelopment may differ prior to onset. Finally, we found taking sedatives was associated with larger cerebellar white matter and non-significantly larger cortical volume. Limitations This study was cross-sectional, limiting interpretation of possible mechanisms. Most of our participants were White, which could limit the generalizability. Additionally, we did not account for potential polypharmacy interactions. Conclusions These findings suggest that external influences, such as medications, may influence cerebellum structure in BD and may mask underlying differences. Accounting for medication may be critical for consistent findings in future studies.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".