Network properties of intracortical myelin associated with psychosocial functioning in bipolar I disorder
Bibliographic record
Abstract
Abstract Objective Psychosocial functioning in bipolar disorder (BD) persists even during euthymia and has repeatedly been associated with illness progression and cognitive function. Its neurobiological correlates remain largely unexplored. Using a structural covariance approach, we explored whole cortex intracortical myelin (ICM) and psychosocial functioning in 39 BD type I and 58 matched controls. Method T1‐weighted images (3T) optimized for ICM measurement were analyzed using a surface‐based approach. The ICM signal was sampled at cortical mid‐depth using the MarsAtlas parcellation, and psychosocial functioning was measured via the Functioning Assessment Short Test (FAST). Following construction of structural covariance matrices, graph theoretical measures were calculated for each subject. Within BD and HC groups separately, correlations between network measures and FAST were explored. After accounting for multiple comparisons, significant correlations were tested formally using rank‐based regressions accounting for sex differences. Results In BD only, psychosocial functioning was associated with global efficiency (β = −0.312, pcorr = 0.03), local efficiency in the right rostral dorsolateral prefrontal cortex (β = 0.545, pcorr = 0.001) and clustering coefficient in this region (β = 0.497, pcorr = 0.0002) as well as in the right ventromedial prefrontal cortex (β = 0.428, pcorr = 0.002). All results excepting global efficiency remained significant after accounting for severity of depressive symptoms. In contrast, no significant associations between functioning and network measures were observed in the HC group. Conclusion These results uncovered a novel brain–behaviour relationship between intracortical myelin signal changes and psychosocial functioning in 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".