351 Integration of Auditory and Visual Information is Associated with Ageing, Sex and Cognitive Performance
Bibliographic record
Abstract
Abstract Background In ageing, multisensory integration, i.e. the ability to combine efficiently information from different sensory modalities, is emerging as a stand-alone contributor to explaining cognitive and functional deficits. Experimental evidence shows that inefficient multisensory integration is associated with cognitive impairment, falls and balance maintenance; however these findings need to be supported by large population representative studies. We utilised the Sound-induced flash illusion (SIFI) as test of multisensory efficiency; the test was conducted on a population representative sample from the Irish Longitudinal Study on Ageing (TILDA). We hypothesized that Susceptibility to the SIFI would increase with ageing and would be associated with poorer Montreal Cognitive Assessment (MoCA) scores. Methods Participants: 3,955 adults aged 50 years and over. Participants provided informed consent. Data were drawn from the third wave of the TILDA study, in which participants took part in a Computer Assisted Interview and a Health Assessment. The SIFI test was part of the Health Assessment; SIFI is a computer-based test in which participants see a series of white dots appearing quickly on the screen, which participants are required to count; the dots (flashes) can be paired with 0, 1 or 2 beeps; when one dot is paired with two beeps, there is the illusory perception that two dots are presented. A hierarchical Bayesian, ordinal-regression model was used to determine which variables predicted audio-visual integration (SIFI proportion of correct responses, i.e. no illusions). We controlled for a range of covariates. Results As predicted, higher susceptibility to the SIFI, indicating higher integration of audio-visual information, was associated with older age, and poorer scores at MoCA. Female sex was also associated with higher susceptibility, which represents a novel result in the literature. Conclusion The present study presents the first findings on multisensory integration in a large population representative study. They confirm that inefficient integration is associated with ageing, poorer cognition and, unexpectedly, being female.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".