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Record W2925231405 · doi:10.1073/pnas.1811513116

Redefining bilingualism as a spectrum of experiences that differentially affects brain structure and function

2019· article· en· W2925231405 on OpenAlexaff
Vincent DeLuca, Jason Rothman, Ellen Bialystok, Christos Pliatsikas

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsYork University
Fundersnot available
KeywordsNeuroscience of multilingualismOperationalizationCognitive psychologyCognitionCategorical variablePsychologyBrain Structure and FunctionDevelopmental psychologyComputer scienceNeuroscienceMachine learning

Abstract

fetched live from OpenAlex

Learning and using an additional language is shown to have an impact on the structure and function of the brain, including in regions involved in cognitive control and the connections between them. However, the available evidence remains variable in terms of the localization, extent, and trajectory of these effects. Variability likely stems from the fact that bilingualism has been routinely operationalized as a categorical variable (bilingual/monolingual), whereas it is a complex and dynamic experience with a number of potentially deterministic factors affecting neural plasticity. Here we present a study investigating the combined effects of experience-based factors (EBFs) in bilingual language use on brain structure and functional connectivity. EBFs include an array of measures of everyday usage of a second language in different types of immersive settings (e.g., amount of use in social settings). Analyses reveal specific adaptations in the brain, both structural and functional, correlated to individual EBFs and their combined effects. Taken together, the data show that the brain adapts to be maximally efficient in the processing and control of two languages, although modulated ultimately by individual language experience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.033
GPT teacher head0.295
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations430
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicNeurobiology of Language and BilingualismFrench-language works237,207