Bilingualism: Experience-dependent functional and structural characteristics of the adult brain
Bibliographic record
Abstract
The influence of second language (L2) acquisition on the organization of the brain has been examined behaviourally, functionally, and anatomically, and while there appear to be age-related effects on native-like attainment of an L2, studies have not yet been well controlled for age of acquisition (AOA) and proficiency when comparing bilingual and monolingual individuals. Capitalizing on the unique linguistic environment of Montreal, Quebec, this study compares simultaneous bilinguals, a group of individuals who have acquired two languages from birth, to monolinguals, a group of individuals who have acquired only one language from birth. This provides the opportunity to examine the effects of bilingualism on the brain, without the factor of AOA. Detailed behavioural measures, combined with functional and anatomical magnetic resonance imaging (MRI), were obtained to examine the differences bilinguals and monolinguals display in native language proficiency, cerebral activation during sentence reading, and white and gray matter density (GMD) in a voxel-based morphometry (VBM) analysis. Simultaneous bilingual and monolingual individuals demonstrated equivalent behavioural and functional patterns in their respective native languages and very few differences in the VBM analysis. A region of interest in left Heschl's gyrus emerged where GMD was greater in bilinguals than monolinguals, and further research is needed to understand the role of this region in early phonetic discrimination. This study adds insights about how early language experience may help shape brain function and structure.
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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".