The Relationship Between Executive Functioning and Narrative Language Abilities in Aphasia
Bibliographic record
Abstract
PURPOSE: Although individuals with aphasia commonly exhibit challenges in executive functioning (EF) and spoken discourse, there is limited research exploring connections between these abilities within this specific population. Therefore, this study investigated the relationship between verbal and nonverbal EF and narrative productions in aphasia using a multilevel linguistic approach. METHOD: Participants included 22 persons with aphasia (PWA) and 24 age- and education-matched, neurologically healthy controls (NHC). All participants completed assessments for EF and a story retelling task. Narrative samples were analyzed for microlinguistic (productivity, lexical and syntactic features, semantic content, word and sentence errors) and macrolinguistic (coherence, informational content, organization, and language use) characteristics. Correlational analyses were employed to explore the relationships among narrative variables. EF factors, extracted from principal component analysis, were used as predictive variables in hierarchical stepwise regression analyses to evaluate their role in predicting narrative performances of PWA and NHC. RESULTS: Relative to NHC, PWA exhibited impaired narrative performance affecting both microlinguistic and macrolinguistic levels. Breakdowns at the structural level (i.e., reduced productivity, syntax, lexical retrieval, and diversity) correlated with impaired story completeness, organization, and connectedness; this relationship was more prominent for PWA. Three EF factors representing (1) verbal EF, (2) verbal and nonverbal fluency, and (3) nonverbal EF were extracted. Factors 1 and 2 largely predicted narrative performance, whereas Factor 3 (i.e., nonverbal EF) contributed prominently to predicting macrolinguistic discourse performance in both groups although accounting for less variance in the data. Overall, lower EF scores, particularly verbal EF variables, predicted poor narrative performance in both groups. CONCLUSIONS: Our results indicate that both linguistic and extralinguistic cognitive abilities play a role in story retelling performances among PWA. Notably, both verbal and nonverbal EF skills were found to be correlated with narrative abilities. However, the extent of their contributions varied depending on the discourse levels assessed. These findings provide a significant contribution to our understanding of the cognitive factors associated with breakdowns in discourse among PWA and highlight the importance of comprehensive assessment of EF and discourse within this population. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.26485627.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".