Reaction Time Intraindividual Variability Reveals Inhibitory Deficits in Single- and Multiple-Domain Amnestic Mild Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVES: Amnestic mild cognitive impairment (aMCI), a prodromal stage of Alzheimer's disease and other dementias, is characterized by episodic memory impairment. Recent evidence has shown inhibitory control deficits in aMCI, but the extent of these deficits across inhibitory domains (i.e., response inhibition and interference control) and aMCI subtypes (i.e., single vs multiple domain) remains unclear. Few studies have included reaction time intraindividual variability (RT IIV) in these efforts. The aim of this study was to compare response inhibition and interference control between aMCI subtypes using measures of accuracy, mean RT, and RT IIV. METHODS: We report data from 34 individuals with single-domain aMCI (sdaMCI, 66-86 years), 20 individuals with multiple-domain aMCI (mdaMCI, 68-88 years), and 52 healthy controls (HC, 64-88 years) who completed tasks of response inhibition (Go-NoGo) and interference control (Flanker). Group differences in accuracy, mean RT, and RT IIV were examined for both tasks. RESULTS: Individuals with mdaMCI had higher RT IIV than the other groups on both tasks. In RT IIV, we observed an interference control deficit in mdaMCI and sdaMCI relative to healthy controls, a finding not observed through accuracy or mean RT. DISCUSSION: RT IIV may detect subtle differences in inhibition deficits between aMCI subtypes that may not be evident with conventional behavioral measures. Findings support the supplementary use of RT IIV when assessing early executive function deficits.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".