Visual Abnormalities Associate With Hippocampus in Mild Cognitive Impairment and Early Alzheimer's Disease
Bibliographic record
Abstract
Background and Objective: Alzheimer's disease (AD) has been shown to affect vision in human patients and animal models. This study was conducted to explore ocular abnormalities in the primary visual pathway and their relationship with hippocampal atrophy in patients with AD and mild cognitive impairment (MCI). The aim of this study was to investigate the potential value of ocular examinations as a biomarker during the AD progression. Methods: Patients with MCI ( n = 23) or AD ( n = 17) and age-matched cognitively normal controls (NC; n = 19) were enrolled. Pattern visual-evoked potentials (PVEP), flash electroretinogram (FERG) recordings and optical coherence tomography (OCT) were performed for all participants. Hippocampal volumes were measured by 3T magnetic resonance imaging. Cognitive function was assessed by Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog). Pearson correlation was employed to analyze the potential associations between ocular abnormalities and hippocampal volumes. Hierarchical regression models were conducted to determine associations between cognitive performances and ocular abnormalities as well as hippocampal volumes after adjusting for confounding factors including age, sex, cognitive reserve, and APOE4 status. Results: PVEP amplitude of P100 waveform was significantly decreased in AD patients compared to MCI and normal individuals. In FERG test, delayed latencies of rod response, rod cone response and 3.0 flicker time were found in cognitively impaired groups, indicating dysfunctions of both the rod and cone systems in the disease progression. OCT test revealed reduced macular retinal nerve fiber layer (m-RNFL) thickness in MCI and AD patients, which significantly correlated with brain structure of hippocampus particularly vulnerable during the progression of AD. Interestingly, P100 amplitude showed a significant association with hippocampal volumes even after adjusting confounding factors including age, sex, and cognitive reserve. Hierarchical regression analysis further demonstrated that m-RNFL thickness, as well as hippocampal volumes, significantly associated with ADAS-cog scores. Conclusion: P100 amplitude and m-RNFL thickness showed significant correlations with brain structure involved in AD-related neurodegeneration, and therefore proved to be potential indicators of brain imaging pathologies.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".