Functional brain adaptations during speech processing in 4-month-old bilingual infants
Bibliographic record
Abstract
Abstract Language learning is influenced by both neural development and environmental experiences. This work investigates the influence of early bilingual experience on the neural mechanisms underlying speech processing in 4-month-old infants. We study how an early environmental factor such as bilingualism interacts with neural development by comparing monolingual and bilingual infants’ brain responses to speech. We used functional near-infrared spectroscopy (fNIRS) to measure 4-month-old Spanish-Basque bilingual and Spanish monolingual infants’ brain responses while they listened to forward (FW) and backward (BW) speech stimuli in Spanish. We reveal distinct neural signatures associated with bilingual adaptations, including increased engagement of bilateral inferior frontal and temporal regions during speech processing in bilingual infants, as opposed to left hemispheric specialization observed in monolingual infants. This study provides compelling evidence of bilingualism-induced brain adaptations during speech processing in infants as young as four months. These findings emphasize the role of early language experience in shaping neural plasticity during infancy suggesting that bilingual exposure at this young age profoundly influences the neural mechanisms underlying speech processing. Research Highlights This research sheds light on the intricate relationship between language learning, neural maturation, and environmental factors in early infancy. Bilingual infants exhibit unique functional brain adaptations during speech processing as early as 4 months of age. This study underscores the critical role of language experience in shaping the developing brain. These findings have implications for our understanding of language acquisition and neuroplasticity in infants growing up in bilingual environments.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".