Visual entrainment responses are altered in patients with mild cognitive impairment and Alzheimer’s disease
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease (AD) is the most common cause of dementia in later life. AD is histologically characterized by the accumulation of extracellular amyloid‐β (Aβ) plaques and intracellular hyperphosphorylated‐tau neurofibrillary tangles. Recent research has indicated that visual entrainment may be useful in clearing Aβ‐ and tau‐load in the central nervous system in mouse models of AD. However, human studies in this area are rare and the degree to which patients with AD exhibit aberrations in visual entrainment are unknown, as is the impact of entrainment on amyloid and tau‐load. Method We recorded magnetoencephalography (MEG) during a 15‐Hz visual entrainment paradigm in amyloid‐positive patients on the AD spectrum and compared their neural responses to biomarker‐negative, demographically‐matched, cognitively‐normal controls. MEG data were imaged using a beamformer and virtual sensor data were extracted from the peak responses. Result Our results indicated that participants on the AD spectrum exhibited significantly stronger entrainment relative to baseline in primary visual cortices. However, interestingly, the two groups exhibited roughly equal absolute levels of entrainment, which suggests lower spontaneous levels of 15‐Hz activity in the AD spectrum group. Additionally, we found that higher absolute levels of entertainment predicted greater MoCA scores. Conclusion This pattern of results indicates that the increased entrainment in patients on the AD spectrum was compensatory and that those patients who were closer to the level seen in controls had better cognitive performance. Overall, these results indicate that entrainment may be altered in humans with AD and should be further examined in future studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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".