The brain’s structural connectivity and pre-reading abilities in young children with prenatal alcohol exposure
Bibliographic record
Abstract
Children with prenatal alcohol exposure (PAE) may develop a range of neurological and behavioral deficits, including reading and language disorders. Studying the brain’s structural connectivity and its relationship to pre-reading/reading skills in young children with PAE can help understand the roots of reading deficits associated with PAE. 363 diffusion MRI scans from 135 children (114 scans from 53 children with PAE) were collected between ages 3–7 years. Children completed NEPSY-II Phonological Processing and Speeded Naming to assess pre-reading skills at each scan. Structural brain network properties were assessed in 16 regions from both hemispheres using graph theory. Linear mixed models were used to account for repeated measures within participants. Children with PAE had significantly lower pre-reading scores than unexposed children, and significantly lower graph theory metrics across bilateral reading networks. Moreover, PAE significantly moderated the associations between Phonological Processing and global efficiency and nodal degree in the bilateral and left hemisphere reading networks, such that children with PAE had stronger associations than unexposed controls. No significant associations were found for Speeded Naming. Our results suggest that brain alterations may underlie early pre-reading difficulties in children with PAE. • Examined structural brain connectivity and pre-reading skills in 135 children (53 with PAE) aged 2–7 years. • Children with PAE have reduced structural connectivity in the reading network and lower pre-reading scores. • PAE significantly moderated the structural connectivity correlates of pre-reading skills. • Brain connectivity appears to underlie emerging reading deficits in children with PAE.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".