Young children in different linguistic environments: A multimodal neuroimaging study of the inferior frontal gyrus
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) studies show that bilingual adults display structural and functional brain alterations, especially in the inferior frontal gyrus (IFG), dependent on when they learned their second language. However, it is unclear whether these differences are due to early exposure to another language, or to lifelong adaptation. We studied 22 children aged 3-5 years growing up in a multilingual environment and 22 age- and sex-matched controls exposed to an English-only environment. Resting-state functional MRI and T1-weighted MRI were used to assess functional connectivity and structure of the IFG. Children in a multilingual environment had higher functional connectivity between the left IFG and dorsal language and attention areas compared to children from a monolingual environment. Children in a multilingual environment also displayed decreased functional connectivity to temporal, anterior cingulate, and prefrontal areas. No significant group differences in IFG structure were observed. Our results suggest a more integrated functional language network, which is more segregated from other networks, in children who grow up in a multilingual environment. These findings suggest that functional alterations to the IFG due to second language learning occur early, while structural changes may not be apparent until later.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".