Language brain responses and neurodevelopmental outcome in preschoolers with congenital heart disease: A fNIRS study
Bibliographic record
Abstract
Neurodevelopmental disabilities affect up to 50% of survivors of congenital heart disease (CHD). Language difficulties are frequently identified during preschool period and can lead to academic, social, behavioral, and emotional difficulties. Structural brain alterations are associated with poorer neurodevelopmental outcomes in patients with CHD during infancy, childhood, and adolescence. However, evidence is lacking about the functional brain activity in children with CHD and its relationship with neurodevelopment. This study therefore aimed to characterize brain responses during a passive story-listening task in 3-year-old children with CHD, and to investigate the relationship between functional brain patterns of language processing and neurodevelopmental outcomes. To do so, we assessed hemodynamic concentration changes, using functional near-infrared spectroscopy (fNIRS), and neurodevelopmental outcomes, using the Wechsler Preschool and Primary Scale of Intelligence - 4th Edition (WPPSI-IV), in children with CHD (n = 19) and healthy controls (n = 23). Compared to their healthy peers, children with CHD had significantly lower scores on the Verbal comprehension index (VCI), the Vocabulary acquisition index (VAI), the General ability index (GAI), and the Information and the Picture Naming subtests of the WPPSI-IV. During the passive story-listening task, healthy controls showed significant hemodynamic brain responses in the temporal and the temporal posterior regions, with stronger activation in the temporal posterior than in the temporal regions. In contrast, children with CHD showed reduced activation in the temporal posterior regions compared to controls, with no difference of activation between regions. Reduced brain responses in the temporal posterior regions were also correlated with lower neurodevelopmental outcomes in both groups. This is the first study that reveals reduced brain functional responses in preschoolers with CHD during a receptive language task. It also suggests that the temporal posterior activation could be a potential brain marker of cognitive development. These findings provide support for the feasibility of identifying brain correlates of neurodevelopmental vulnerabilities in children with CHD.
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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) | 0.001 | 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".