36 Naming in Monolingual and Bilingual Children with Epilepsy
Bibliographic record
Abstract
Objective: Word finding or “naming” difficulty is a symptom of multiple neurological disorders; therefore, naming assessment is an integral component of neuropsychological evaluation. Prior work has found weaker second-language naming in healthy proficient bilingual youth than monolingual youth, and similar findings have been shown in adults with epilepsy. Considering the potential influences of both early onset epilepsy and bilingualism on brain development, we compared naming in English second language (ESL) and monolingual youth with epilepsy. To assess the impact of bilingualism independent of the known effects of seizure laterality (i.e., poor naming in those with left, dominant-hemisphere seizures), we excluded patients with left language dominance and unilateral seizures. We hypothesized that like other groups, naming would be weaker in ESL than in monolingual youth with epilepsy. Participants and Methods: Participants included 84 children with seizures that could not be lateralized clinically (n=36), bilateral seizures (n=20), centrotemporal spikes (n=3), and those with unilateral seizures and atypical language dominance (n=25), ages 6-15 years old: 66 monolingual, English (mean age: 10.87 ± 2.70 years) and 18 ESL (mean age: 10.78 ± 2.88 years). Those with FSIQ < 70 and vocabulary SS < 6 were excluded to ensure English proficiency. Independent samples t-tests, multivariate ANOVA, and chi-square tests compared groups on demographic factors and test performance. All measures (FSIQ, WISC/WASI Vocabulary, letter and category fluency, Children’s Auditory (AN) and Visual Naming (VN) Tests) were administered in English. Results: Monolingual and ESL groups did not differ in: age, sex, SES, seizure type (i.e., non-lateralized, bilateral, centrotemporal spikes, or atypical language dominance), epilepsy onset age, or number of AEDs. Comparisons also showed no differences in FSIQ, vocabulary, letter fluency, or category fluency (all ps > 0.05). By contrast, auditory and visual naming performances were weaker among ESL patients than monolingual patients: AN accuracy, F(1,81) = 10.89, p = 0.001; AN tip-of-the-tongues (TOTs), F(1,81) = 6.35, p = 0.014; AN Summary Scores (SS), F(1,81) = 6.17, p = 0.015; VN accuracy, F(1,81) = 4.66, p = 0.034; VN SS, F(1,81) = 4.87, p = 0.030, with the exception of VN TOTs, which approached significance, F(1,81) = 3.55, p = 0.063. Conclusions: Consistent with findings in bilingual healthy youth and ESL adults with epilepsy, naming in ESL youth with epilepsy was weaker than in monolingual children. The groups did not differ on other aspects of language. Thus, unlike other expressive verbal functions, naming is adversely affected in the second language of bilingual people with epilepsy across the age span. These results suggest that poor naming in ESL patients cannot be used to infer a naming deficit, and/or left (dominant) temporal lobe dysfunction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".