Cerebral Blood Flow and Core Mood Symptoms in Youth Bipolar Disorder: Evidence for Region–Symptom Specificity
Bibliographic record
Abstract
Objective Building on prior findings in adults, this study investigated regional cerebral blood flow (CBF) in relation to DSM-5 criterion A symptoms of depression and mania in youth with bipolar disorder (BD). Method The study recruited 81 youths with BD and 75 healthy controls 13-20 years old. CBF was ascertained using pseudocontinuous arterial spin labeling magnetic resonance imaging. Region-of-interest analyses examined the amygdala, anterior cingulate cortex (ACC), middle frontal gyrus, and global gray matter CBF. The association of criterion A depression and mania symptoms with CBF was examined dimensionally in youth with BD in regression analyses with continuous symptom severity scores. Age and sex were included as covariates. False discovery rate (FDR) was used to correct for 28 tests (4 regions by 7 symptoms; α < .0017). CBF for BD and healthy control groups was compared to give context for findings. Results In youth with BD, depressed mood inversely correlated with ACC (β = −0.31, p uncorrected = .004, p FDR = .056) and global (β = −0.27, p uncorrected = .013, p FDR = .09) CBF. The same pattern was observed for anhedonia (ACC CBF: β = −0.33, p uncorrected = .004, p FDR = .056; global CBF: β = −0.29, p uncorrected = .008, p FDR = .07). There were no significant findings for manic symptoms or in BD vs healthy control contrasts. Conclusion The present findings, while not significant after correction for multiple testing, highlight the potential value of focusing on ACC in relation to depressed mood and anhedonia, and demonstrate that CBF is sensitive to depression symptom severity in youth. Lack of findings regarding manic symptoms may relate to the exclusion of fully manic participants in this outpatient sample.
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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 | 0.001 |
| 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".