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Record W2019685687 · doi:10.3109/02699206.2011.563338

Impaired L1 and executive control after left basal ganglia damage in a bilingual Basque–Spanish person with aphasia

2011· article· en· W2019685687 on OpenAlexaff
Daniel Adrover‐Roig, Nekane Galparsoro-Izagirre, Karine Marcotte, Perrine Ferré, Maximiliano A. Wilson, Ana Inés Ansaldo

Bibliographic record

VenueClinical Linguistics & Phonetics · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsAphasiaPsychologyBasal gangliaNeuroscience of multilingualismSentenceCognitive psychologySpeech productionGrammaticalityLinguisticsAudiologyNeuroscienceMedicineCentral nervous system

Abstract

fetched live from OpenAlex

Bilinguals must focus their attention to control competing languages. In bilingual aphasia, damage to the fronto-subcortical loop may lead to pathological language switching and mixing and the attrition of the more automatic language (usually L1). We present the case of JZ, a bilingual Basque-Spanish 53-year-old man who, after haematoma in the left basal ganglia, presented with executive deficits and aphasia, characterised by more impaired language processing in Basque, his L1. Assessment with the Bilingual Aphasia Test revealed impaired spontaneous and automatic speech production and speech rate in L1, as well as impaired L2-to-L1 sentence translation. Later observation led to the assessment of verbal and non-verbal executive control, which allowed JZ's impaired performance on language tasks to be related to executive dysfunction. In line with previous research, we report the significant attrition of L1 following damage to the left basal ganglia, reported for the first time in a Basque-Spanish bilingual. Implications for models of declarative and procedural memory are discussed.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.056
GPT teacher head0.305
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 designCase report
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

Citations51
Published2011
Admission routes1
Has abstractyes

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