Memory retrieval activation moderates the effect of Alzheimer’s disease pathology on memory performance
Bibliographic record
Abstract
Abstract Background Cognitive reserve (CR) is a concept explaining better than expected cognitive performance given the degree of brain disease. More specifically, as a compensation mechanism, individual differences in patterns of brain activity during fMRI tasks may explain differential susceptibility to pathological burden. CR might already manifest in early preclinical Alzheimer’s disease (AD) stages. Method Participants of the longitudinal PREVENT‐AD study have well‐characterized AD biomarkers via [18F]AV1451 and [18F]NAV469 PET for Aβ and tau as well as repeated MRI measurements including a memory retrieval task. Participants also completed cognitive testing with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). We selected a subsample of 82 cognitively unimpaired older adults (age: 67.9 ± 4.8 years; 24 male) with (f)MRI data within 2 years of PET. PET‐ and MRI‐based ATN biomarkers were reduced to a single composite measure for AD pathological load (PL; Fig.1). We extracted mean retrieval‐related fMRI activation (hits versus correct rejections) from specific regions, comprising all task‐positive regions (pFWE < 0.05), all task‐negative regions, entorhinal cortex, precuneus, and inferior parietal cortex. Subsequently, we tested fMRI activation as a moderator variable between PL and delayed memory performance in line with the CR framework. Result Activation in task‐positive regions showed an interaction (moderation) effect with PL on memory performance (p = 0.033). In individuals with low retrieval activation in the task‐positive network, AD pathological load was related to poorer memory performance, whereas this association was diminished in individuals with high retrieval activation. This moderation was not significant for task‐negative regions (p = 0.104). We observed a similar interaction for tau and activity in the entorhinal cortex (p = 0.0003) as well as for Aβ and activity in the precuneus (p = 0.056) and inferior parietal cortex (p = 0.010). Conclusion Our results indicate that the association between early AD pathology and memory performance differs dependent on the level of fMRI activation during memory retrieval, with an attenuated effect of pathology on memory at high levels of activation. It remains open if higher activity in the retrieval network serves as a functional reserve, or whether it reflects adaptive functional changes due to early pathology.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".