Is there an association between cognitive and visual decline?
Bibliographic record
Abstract
Cognitive and visual abilities decline with age. Recently, it has been suggested that the risk to suffer from dementia is associated with decreased visual acuity. Two theories, the sensory deprivation theory (stating that visual impairments cause cognitive decline) and the common cause theory (stating that cognitive and visual decline are caused by a general age-related decline of the system) have been proposed to explain the relationship between cognitive and visual changes. There is currently no consensus on which theory is valid. However, both agree that visual factors could act as biomarkers for cognitive decline. Given the limited research studying the link between vision and cognition using multiple measures of vision, we tested a battery of 19 visual tasks on 39 older adults with mild cognitive impairment (i.e., MCI group, age = 67 ± 5, 26 females) and 91 without evidence of cognitive decline (i.e., healthy group, age = 66 ± 5, 60 females), as measured by the Montreal Cognitive Assessment (MoCa). Our results revealed a strong association between visual and cognitive decline. The tasks showing the largest effect sizes were orientation discrimination, biological motion, motion detection and visual search. However, mirroring previous results in young adults, there were only weak correlations between the performance levels of the visual functions in both the healthy and the MCI groups, arguing against a common factor. Our results suggest that visual and cognitive abilities decline simultaneously, but they do so independently across visual and cognitive functions and participants.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".