Assessing the Effects of Exercise, Cognitive Demand, and Rest on Audiovisual Multisensory Processing in Older Adults: A Pilot Study
Bibliographic record
Abstract
A single bout of aerobic exercise is related to positive changes in higher-order cognitive function among older adults; however, the impact of aerobic exercise on multisensory processing remains unclear. Here we assessed the effects of a single bout of aerobic exercise on commonly utilized tasks that measure audiovisual multisensory processing: response time (RT), simultaneity judgements (SJ), and temporal-order judgements (TOJ), in a pilot study. To our knowledge this is the first effort to investigate the effects of three well-controlled intervention conditions on multisensory processing: resting, completing a cognitively demanding task, and performing aerobic exercise for 20 minutes. Our results indicate that the window of time within which stimuli from different modalities are integrated and perceived as simultaneous (temporal binding window; TBW) is malleable and changes after each intervention condition for both the SJ and TOJ tasks. Specifically, the TBW consistently became narrower post exercise while consistently increasing in width post rest, suggesting that aerobic exercise may improve temporal perception precision via broad neural change rather than targeting the specific networks that subserve either the SJ or TOJ tasks individually. The results from the RT task further support our findings of malleability of the multisensory processing system, as changes in performance, as assessed through cumulative probability models, were observed after each intervention condition. An increase in integration (i.e., greater magnitude of multisensory effect) however, was only found after a single bout of aerobic exercise. Overall, our results indicate that exercise uniquely affects the central nervous system and may broadly affect multisensory processing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".