Sex differences in brain connectivity and male vulnerability in very preterm children
Bibliographic record
Abstract
Evidence indicates better cognitive and behavioral outcomes for females born very preterm (≤32 weeks gestation) compared to males, but the neurophysiology underlying this apparent resiliency of the female brain remains poorly understood. Here we test the hypothesis that very preterm males express more pronounced connectivity alterations as a reflection of higher male vulnerability. Resting state MEG recordings, neonatal and psychometric data were collected from 100 children at age 8 years: very preterm boys (n = 27), very preterm girls (n = 34), full-term boys (n = 15) and full-term girls (n = 24). Neuromagnetic source dynamics were reconstructed from 76 cortical brain regions. Functional connectivity was estimated using inter-regional phase-synchronization. We performed a series of multivariate analyses to test for differences across groups as well as to explore relationships between deviations in functional connectivity and psychometric scores and neonatal factors for very preterm children. Very preterm boys displayed significantly higher (p < .001) absolute deviation from average connectivity of same-sex full-term group, compared to very preterm girls versus full-term girls. In the connectivity comparison between very preterm and full-term groups separately for boys and girls, significant group differences (p < .05) were observed for boys, but not girls. Sex differences in connectivity (p < .01) were observed in very preterm children but not in full-term groups. Our findings indicate that very preterm boys have greater alterations in resting neurophysiological network communication than girls. Such uneven brain communication disruption in very preterm boys and girls suggests that stronger connectivity alterations might contribute to male vulnerability in long-term behavioral and cognitive outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".