Predicting the Multisensory Consequences of One’s Own Action: BOLD Suppression in Auditory and Visual Cortices
Bibliographic record
Abstract
Predictive mechanisms are essential to successfully interact with the environment and to compensate for delays in the transmission of neural signals. However, whether and how we predict multisensory action outcomes remains largely unknown. Here we investigated the existence of multisensory predictive mechanisms in a context where actions have outcomes in different modalities. During fMRI data acquisition auditory, visual and auditory-visual stimuli were presented in active and passive conditions. In the active condition, a self-initiated button press elicited the stimuli with variable short delays (0-417ms) between action and outcome, and participants had to detect the presence of a delay for auditory or visual outcome (task modality). In the passive condition, stimuli appeared automatically, and participants had to detect the number of stimulus modalities (unimodal/bimodal). For action consequences compared to identical but unpredictable control stimuli we observed suppression of the blood oxygen level depended (BOLD) response in a broad network including bilateral auditory and visual cortices. This effect was independent of task modality or stimulus modality and strongest for trials where no delay was detected (undetected
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".