Cognitive–Linguistic Functions in Adults With Epilepsy: Preliminary Electrophysiological and Behavioral Findings
Bibliographic record
Abstract
Purpose Cognition and language difficulties are frequently reported in both children and adults with epilepsy. The majority of the existing research has focused on pediatric epilepsy, documenting impairments in learning, academics, and social-emotional functioning. In comparison, language deficits in younger and older adults with epilepsy have received less empirical attention. Given recently identified limitations in the extant literature regarding assessing epilepsy-related language problems in adults (Dutta et al., 2018), the current exploratory study described in this research note investigated the cognitive-linguistic abilities of adults with focal or generalized types of epilepsy. Method Twelve participants with epilepsy and 11 age- and education-matched healthy controls completed a cognitive-linguistic test battery. Event-related potential (ERP) procedures were also employed to assess the integrity of neural activity supporting psycholinguistic processing in both groups using a lexical decision task. Results No significant performance differences between epilepsy and healthy control groups were noted on basic language tasks; however, group differences were evident on the more complex language measures, including spoken discourse. Even though both groups performed the lexical decision task similarly in terms of accuracy, individuals with epilepsy demonstrated longer reaction times and some atypical ERP characteristics compared to controls. Conclusion The cognitive-linguistic assessment and ERP findings suggested that, compared to neurotypical adults, individuals with epilepsy demonstrate slower processing times and greater difficulty with high-level language and spoken discourse production, despite performing within typical limits on basic language tests. Preliminary results from this research are significant in providing new knowledge about language functioning in adults with epilepsy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".