Language Network Function in Young Children Born Very Preterm
Bibliographic record
Abstract
Language deficits are reported in preterm born children across development. Recent neuroimaging studies have found functional alterations in large-scale brain networks underlying these language deficits, but the early childhood development of the language network has not been investigated. Here, we compared intrinsic language network connectivity in 4-year-old children born VPT and term-born controls, using defined language regions (Broca's area, Wernicke's areas, and their homologues in the right hemisphere). Resting-state functional magnetic resonance imaging (fMRI) was obtained, and the group differences in whole-brain connectivity were examined from each seed as well as correlations with language outcomes. We found significantly decreased functional connectivity in almost all language regions in children born VPT compared to their term controls. Notably, Broca's area homologue in the right hemisphere emerged as a functional hub of decreased connectivity in VPT group, specifically to bilateral inferior frontal and supramarginal gyri; connectivity strength between Broca's area homologue with the right supramarginal and the left inferior frontal gyri was associated with better language outcomes at 4 years of age. Wernicke's area and its homologue also showed decreased inter-hemispheric connections to bilateral supramarginal gyri in the VPT group. Decreased intra- and inter-hemispheric connectivity among primary language regions suggests immature and altered function in the language network in children born VPT.
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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 | 0.002 |
| 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".