Temporal Metrics of Multisensory Processing Change in the Elderly
Bibliographic record
Abstract
Abstract Older adults exhibit greater multisensory response time (RT) facilitation by violating the race model more than younger adults; this is commonly interpreted as an enhancement in perception. Older adults typically exhibit wider temporal binding windows (TBWs) and points of subjective simultaneity (PSS) that are farther from true simultaneity as compared to younger adults when simultaneity judgment (SJ) and temporal order judgment (TOJ) tasks are utilized; this is commonly interpreted as an impairment in perception. Here we explore the relation between the three tasks in younger and older adults in order to better understand the underlying mechanisms that subserve audiovisual multisensory temporal processing. Our results confirm previous reports showing that audiovisual RT, TBWs and PSSs change with age, and we show for the first time a significant positive relation between the magnitude of race model violation in younger adults as a function of the PSS obtained from the audiovisual TOJ task with (r: 0.49, p : 0.007), that is absent among the elderly (r: 0.13, p : 0.58). Furthermore, we find no evidence for the relation between race model violation as a function of the PSS obtained from the audiovisual SJ task in both younger (r: −0.01, p : 0.94) and older adults (r: 0.1, p : 0.66). Our results confirm previous reports that i) audiovisual temporal processing changes with age; ii) there is evidence for distinct neural networks involved in simultaneity and temporal order perception; and iii) common processing between race model violation and temporal order judgment is impaired in the elderly.
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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 | 0.003 |
| 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".