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Duration and extent of bilingual experience modulate neurocognitive outcomes

2019· article· en· W2976949611 on OpenAlexaff
Vincent DeLuca, Jason Rothman, Ellen Bialystok, Christos Pliatsikas

Bibliographic record

VenueNeuroImage · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsYork University
FundersUniversity of Reading
KeywordsNeurocognitiveNeuroscience of multilingualismPsychologyNeuroimagingCognitive psychologyComplementarity (molecular biology)Brain activity and meditationNeural correlates of consciousnessDevelopmental psychologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

The potential effects of bilingualism on executive control (EC) have been heavily debated. One possible source of discrepancy in the evidence may be that bilingualism tends to be treated as a monolithic category distinct from monolingualism. We address this possibility by examining the effects of different bilingual language experiences on brain activity related to EC performance. Participants were scanned (fMRI) while they performed a Flanker task. Behavioral data showed robust Flanker effects, not modulated by language experiences across participants. However, differences in duration of bilingual experience and extent of active language use predicted activation in distinct brain regions indicating differences in neural recruitment across conditions. This approach highlights the need to consider specific bilingual language experiences in assessing neurocognitive effects. It further underscores the utility and complementarity of neuroimaging evidence in this general line of research, contributing to a deeper understanding of the variability reported in the literature.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.300
Teacher spread0.272 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations126
Published2019
Admission routes1
Has abstractyes

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