Effects of Cognitive Reserve in Alzheimer’s Disease and Cognitively Unimpaired Individuals
Bibliographic record
Abstract
The concept of cognitive reserve (CR) has been proposed as a protective factor that modifies the effect of brain pathology on cognitive performance. It has been characterized through CR proxies; however, they have intrinsic limitations. In this study, we utilized two different datasets containing tau, amyloid PET, and T1 magnetic resonance imaging. First, 91 Alzheimer's disease (AD) continuum subjects were included from Alzheimer's Disease Neuroimaging Initiative 3. CR was conceptualized as the residual between actual cognition and estimated cognition based on amyloid, tau, and neurodegeneration. The proposed marker was tested by the correlation with CR proxy and modulation of brain pathology effects on cognitive function. Second, longitudinal data of baseline 53 AD spectrum and 34 cognitively unimpaired (CU) participants in the MEMORI dataset were analyzed. CR marker was evaluated for the association with disease conversion rate and clinical progression. Applying our multimodal CR model, this study demonstrates the differential effect of CR on clinical progression according to the disease status and the modulating effect on the relationship between brain pathology and cognition. The proposed marker was associated with years of education and modulated the effect of pathological burden on cognitive performance in the AD spectrum. Longitudinally, higher CR marker was associated with lower disease conversion rate among prodromal AD and CU individuals. Higher CR marker was related to exacerbated cognitive decline in the AD spectrum; however, it was associated with a mitigated decline in CU individuals. These results provide evidence that CR may affect the clinical progression differentially depending on the disease status.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".