Differential effects of aging, Alzheimer’s pathology, and <i>APOE4</i> on longitudinal functional connectivity and episodic memory in older adults
Bibliographic record
Abstract
Abstract INTRODUCTION Both aging and Alzheimer’s disease (AD) affect episodic memory networks. How this relates to region-specific early differences in functional connectivity (FC), however, remains unclear. METHODS We assessed resting-state FC strength in the medial temporal lobe (MTL) - posteromedial cortex (PMC) - prefrontal network and cognition over two years in cognitively normal older adults from the PREVENT-AD cohort. RESULTS FC strength within PMC and between posterior hippocampus and inferomedial precuneus decreased in “normal” aging (amyloid- and tau-negative adults). Lower FC strength within PMC was associated with poorer longitudinal episodic memory performance. Increasing FC between anterior hippocampus and superior precuneus was related to higher baseline AD pathology. Higher FC strength was differentially associated with memory trajectories depending on APOE4 genotype. DISCUSSION Findings suggest differential effects of aging and AD pathology on longitudinal FC. MTL-PMC hypoconnectivity was related to aging and cognitive decline. Furthermore, MTL-PMC hyperconnectivity was related to early AD pathology and cognitive decline in APOE4 carriers. Graphical abstract. A) “Normal aging” is characterized by a longitudinal decrease in functional connectivity. B) Cognitively unimpaired older adults with more Alzheimer’s pathology at baseline (measured via cerebrospinal fluid) exhibit a longitudinal increase in functional connectivity.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".