Enhanced vection in older adults: Evidence for age-related effects in multisensory vection experiences
Bibliographic record
Abstract
The illusion of self-motion (vection) is a multisensory phenomenon elicited by visual, auditory, tactile, or other sensory cues. Aging is often associated with changes in sensory acuity, visual motion perception, and multisensory integration, processes which may influence vection perception. However, age-related differences in vection have received little study to date. Thus, the objective of the present study was to investigate age-related differences in vection during multisensory stimulation. Nineteen younger adults and 19 older adults were exposed to rotating visual, auditory, and tactile stimuli (separately or in combination) at a speed of 45°/s inside a VR laboratory inducing circular vection. The size of the field-of-view (FOV) was large (240°), medium (75°), small (30°), or contained no visuals. Vection intensity and duration were reported verbally after each trial. Overall, older adults experienced significantly stronger and longer vection compared to younger adults. Additionally, there were main effects of FOV and sensory cues, such that larger FOVs and the presence of auditory and tactile stimulation increased vection ratings for both age groups. These findings support the idea that vection is a multisensory experience that can be elicited by visual, auditory, and tactile stimuli and demonstrates these effects for the first time in older adults.
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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 | 0.002 |
| 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".