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<detected). In bimodal vs. unimodal conditions we found activation differences in the left cerebellum for detected vs. undetected trials and an increased cerebellar-sensory cortex connectivity. Thus, action-related predictive mechanisms lead to BOLD suppression in multiple sensory brain regions. These findings support the hypothesis of multisensory predictive mechanisms, which are probably conducted in the left cerebellum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".