Cortical Thickness in Children of Parents Diagnosed with Bipolar Disorder
Bibliographic record
Abstract
Bipolar disorder (BD) is associated with reduced cortical thickness in prefrontal and temporal cortical areas responsible for affect regulation. Children of parents diagnosed with bipolar disorder (high-risk (HR) offspring) are at risk of developing a psychiatric illness, and may have cortical abnormalities in affect regulating pathways prior to the onset of any psychiatric disorder. The current study is investigating cortical abnormalities in children at risk of developing bipolar disorder to better understand the developmental trajectories of psychopathology. Twenty-four HR bipolar offspring (average age = 13.7 (2.69) years, 12 females), and 9 age and sex matched healthy controls (HC) (average age = 12.9 (2.70) years, 5 females) were included in this study. Structural brain scans were administered and measures of cortical thickness were extracted and compared between the HR and HC offspring. HR offspring had significantly decreased cortical thickness in the left superior frontal gyrus, BA 6 (t=4.23 and t=3.57), the left posterior cingulate, BA 30 (t=3.49 and t=3.44) compared to HC offspring. Further analysis of subgroups of the HR population found additional areas of cortical abnormalities in the frontal and temporal cortex. The significant cortical differences found between HC children and HR bipolar offspring suggest that neurobiological markers of risk and resilience can be identified in children at risk of developing BD.
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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 | 0.001 | 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".