Musical Expertise Induces Audiovisual Integration of Abstract Congruency Rules
Bibliographic record
Abstract
Perception of everyday life events relies mostly on multisensory integration. Hence, studying the neural correlates of the integration of multiple senses constitutes an important tool in understanding perception within an ecologically valid framework. The present study used magnetoencephalography in human subjects to identify the neural correlates of an audiovisual incongruency response, which is not generated due to incongruency of the unisensory physical characteristics of the stimulation but from the violation of an abstract congruency rule. The chosen rule-"the higher the pitch of the tone, the higher the position of the circle"-was comparable to musical reading. In parallel, plasticity effects due to long-term musical training on this response were investigated by comparing musicians to non-musicians. The applied paradigm was based on an appropriate modification of the multifeatured oddball paradigm incorporating, within one run, deviants based on a multisensory audiovisual incongruent condition and two unisensory mismatch conditions: an auditory and a visual one. Results indicated the presence of an audiovisual incongruency response, generated mainly in frontal regions, an auditory mismatch negativity, and a visual mismatch response. Moreover, results revealed that long-term musical training generates plastic changes in frontal, temporal, and occipital areas that affect this multisensory incongruency response as well as the unisensory auditory and visual mismatch responses.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".