On the Timing of Signals in Multisensory Integration and Crossmodal Interactions: a Scoping Review
Bibliographic record
Abstract
A scoping review was undertaken to explore research investigating early interactions and integration of auditory and visual stimuli in the human brain. The focus was on methods used to study low-level multisensory temporal processing using simple stimuli in humans, and how this research has informed our understanding of multisensory perception. The study of multisensory temporal processing probes how the relative timing between signals affects perception. Several tasks, illusions, computational models, and neuroimaging techniques were identified in the literature search. Research into early audiovisual temporal processing in special populations was also reviewed. Recent research has continued to provide support for early integration of crossmodal information. These early interactions can influence higher-level factors, and vice versa. Temporal relationships between auditory and visual stimuli influence multisensory perception, and likely play a substantial role in solving the 'correspondence problem' (how the brain determines which sensory signals belong together, and which should be segregated).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".