MétaCan
Menu
Back to cohort
Record W3034335749 · doi:10.1111/lang.12391

Brain Plasticity in Adulthood—ERP Evidence for L1‐attrition in Lexicon and Morphosyntax After Predominant L2 Use

2020· article· en· W3034335749 on OpenAlexafffund
Karsten Steinhauer, Kristina Kasparian

Bibliographic record

VenueLanguage Learning · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsMcGill UniversityCentre for Research on Brain Language and Music
FundersCanadian Institutes of Health ResearchSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaFonds de Recherche du Québec-Société et CultureFaculty of Medicine, McGill University
KeywordsPsychologyAttritionGrammarLinguisticsLexiconGermanLanguage acquisitionNeuroscience of multilingualismNeurocognitiveSentenceSecond-language acquisitionCognitive psychologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

Abstract Since the early 2000s, neurocognitive research on second language (L2) acquisition has been controversial as to how plastic the human brain is after puberty. Recent studies have extended this debate to first language loss (L1 attrition). This article gives an overview of the first event‐related brain potential (ERP) studies on L1 attrition and L2 learning and discusses their implications for our understanding of the bilingual brain. We will address the highly controversial question of whether L1 morphosyntax is subject to attrition in adult migrants. One previous ERP study on grammatical gender in German migrants failed to find such effects. However, ERP work on grammatical structures in English‐dominant Italian attriters demonstrated that they perceived a grammatical sentence in their L1 as ungrammatical if it violated the L2 grammar. These data suggest that the adult brain remains plastic for both L2 and L1.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.321
Teacher spread0.249 · 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

Citations22
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueLanguage LearningSame topicNeurobiology of Language and BilingualismFrench-language works237,207