Functional connectivity of the attention networks is altered and relates to neuropsychological outcomes in children with prenatal alcohol exposure
Bibliographic record
Abstract
Cognitive and functional brain alterations can occur in children with prenatal alcohol exposure (PAE). We examined the functional connectivity (FC) among regions within and between attention networks, and whether inter- and intranetwork FC moderated cognition in children with PAE (n = 37; age 12.8 ± 2.8 years) and nonexposed controls (n = 40; age 13.2 ± 2.8 years). Participants completed standardized attention and executive functioning tasks and resting state functional MRI. Inter- and intra-network FC and graph-theoretical metrics were calculated among attention network regions. Relative to controls, PAE was associated with reduced FC between the left temporoparietal junction and left ventral frontal cortex and anterior insula/frontal operculum (aI/fO), and between the left intraparietal sulcus and bilateral aI/fO. PAE was associated with increased FC between the right precuneus and intraparietal lobes, the right anterior prefrontal cortex and left ventral frontal cortex and aI/fO, and the left thalamus and dorsal frontal cortex. Graph-theoretical metrics did not differ by group. FC predicted cognitive performance, negatively in the children with PAE and positively in controls. Increased intra-network together with reduced internetwork FC suggests inefficient network specialization and impaired long-range FC among attention network regions after PAE. Results further suggest that those alterations may underlie attention and executive dysfunction in children with PAE.
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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".