The Profile of Executive Functioning in Amnestic Mild Cognitive Impairment: Disproportionate Deficits in Inhibitory Control
Bibliographic record
Abstract
Amnestic mild cognitive impairment (aMCI) represents a group of individuals who are highly likely to develop Alzheimer's disease (AD). Although aMCI is typically conceptualized as involving predominantly deficits in episodic memory, recent studies have demonstrated that deficits in executive functioning may also be present, and thorough categorization of cognitive functioning in MCI may improve early diagnosis and treatment of AD. We first provide an extensive review of neuropsychology studies that examined executive functioning in MCI. We then present data on executive functioning across multiple sub-domains (divided attention, working memory, inhibitory control, verbal fluency, and planning) in 40 aMCI patients (single or multiple domain) and 32 normal elderly controls (NECs). MCI patients performed significantly worse than NECs in all 5 sub-domains, and there was impairment (>1.0 SD below the mean of NECs) in all sub-domains. Impairment on each test was frequent, with 100% of MCI patients exhibiting a deficit in at least one sub-domain of executive functioning. Inhibitory control was the most frequently and severely impaired. These results indicate that executive dysfunction in multiple sub-domains is common in aMCI and highlights the importance of a comprehensive neuropsychological evaluation for fully characterizing the nature and extent of cognitive deficits in MCI.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".