Entorhinal tau impairs short-term memory binding in preclinical Alzheimer’s disease
Bibliographic record
Abstract
Abstract Objective: The entorhinal cortex (EC) is the first cortical region affected by tau pathology in Alzheimer’s disease (AD), but its functions remain unclear. The EC is thought to support memory binding, which can be tested using the Visual Short-Term Memory Binding Test (VSTMBT). We aimed to test whether VSTMBT performance can identify individuals with preclinical AD before noticeable episodic memory impairment and whether these performances are related to amyloid (Aβ) pathology and/or EC tau burden. Methods: Ninety-four participants underwent the VSTMBT (including a shape-only condition (SOC) and a shape-color binding condition (SCBC)), standard neuropsychological assessment including the Preclinical Alzheimer Cognitive Composite (PACC5), an Aβ status examination, a 3D-T1 MRI and a [ 18 F]-MK-6240 tau-PET scan. Participants were classified as follows: 54 Aβ-negative cognitively normal (Aβ − CN), 22 Aβ-positive CN (Aβ + CN, preclinical AD), and 18 Aβ + individuals with Mild Cognitive Impairment (Aβ + MCI, prodromal AD). Results: Aβ + CN individuals performed worse than Aβ-CN participants in the SCBC while the SOC only distinguished Aβ − CN from MCI participants. The SCBC performance was predicted by tau burden in the EC after adjusting for Aβ, white matter hypointensities, inferior temporal cortex (ITC) tau burden, age, sex, and education. The SCBC was more sensitive than the PACC5 in identifying CN individuals with a positive tau-PET scan. Conclusion: Impaired visual short-term memory binding performance was evident from the preclinical stage of sporadic AD and related to tau pathology in the EC, suggesting that SCBC performance could detect early tau pathology in the EC among CN individuals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".