Perceived timing of active head movement at different speeds
Bibliographic record
Abstract
Abstract The central nervous system must determine which sensory events occur at the same time. Actively moving the head corresponds with large changes in the relationship between the observer and the environment, sensorimotor processing, and spatiotemporal perception. Numerous studies have shown that head movement onset must precede the onset of other sensory events in order to be perceived as simultaneous, indicating that head movement perception is slow. Active head movement perception has been shown to be slower than passive head movement perception and dependent on head movement velocity, where participants who move their head faster than other participants require the head to move even earlier than comparison stimuli to be perceived as simultaneous. These results suggest that head movement perception is slower (i.e., suppressed) when the head moves faster. The present study used a within-subjects design to measure the point of subjective simultaneity (PSS) between active head movement speeds and a comparison sound stimulus. Our results clearly show that i) head movement perception is faster when the head moves faster within-subjects, ii) active head movement onset must still precede the onset of other sensory events (Average PSS: -123 to -52 ms) in order to be perceived as occurring simultaneously even at the fastest speeds (Average peak velocity: 76°/s to 257°/s). We conclude that head movement perception is slow, but that this delay is minimized with increased speed. While we do not provide evidence against sensory suppression, which requires active versus passive head movement comparison, our results do rule out velocity-based suppression.
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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 | 0.003 |
| 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) | 0.004 | 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".