Cerebellar Purkinje cells combine sensory and motor information to predict the sensory consequences of active self-motion in macaques
Bibliographic record
Abstract
Accurate perception and behavior rely on distinguishing sensory signals arising from unexpected events from those originating from our own voluntary actions. In the vestibular system, sensory input that is the consequence of active self-motion is canceled early at the first central stage of processing to ensure postural and perceptual stability. However, the source of the required cancellation signal was unknown. Here, we show that the cerebellum combines sensory and motor-related information to predict the sensory consequences of active self-motion. Recordings during attempted but unrealized head movements in two male rhesus monkeys, revealed that the motor-related signals encoded by anterior vermis Purkinje cells explain their altered sensitivity to active versus passive self-motion. Further, a model combining responses from ~40 Purkinje cells accounted for the cancellation observed in early vestibular pathways. These findings establish how cerebellar Purkinje cells predict sensory outcomes of self-movements, resolving a long-standing issue of sensory signal suppression during self-motion.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".