Executive functions predict time reference processing in French-speaking people with Alzheimer’s disease
Bibliographic record
Abstract
The ability to express time through language, known as time reference, is impaired in people with Alzheimer's disease. While cognitive impairments have been documented in this population, particularly in executive functions, few studies have examined how these deficits impact time reference abilities, including tense and grammatical aspect. Since producing time reference requires the integration of grammatical, conceptual, and subjective information, potentially demanding in processing resources, the aim of this study was to investigate whether the cognitive profile (i.e., executive function abilities) of French-speaking people with biologically probable Alzheimer's disease determines their ability in time reference. Verb inflection tasks and cognitive tests were administered to 21 people with a diagnosis of Alzheimer's disease confirmed by cerebrospinal fluid or amyloid positron emission tomography (PET) biomarkers and a control group. Results revealed that individuals with Alzheimer's disease have difficulty with tense and aspect marking, with verbal working memory, inhibition, and mental flexibility playing a significant role in time reference processing. These findings suggest that deficits in executive functions impact the ability of French speakers with Alzheimer's disease to mark tense and grammatical aspect, highlighting the cognitive basis of time reference impairments in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".