Coherent Perspective Jitter Induces Visual Illusions of Self-Motion
Bibliographic record
Abstract
Palmisano et al (2000 Perception 29 57-67) found that adding coherent perspective jitter to constant-velocity radial flow improved visually induced illusions of self-motion (vection). This was a surprising finding, because unlike pure radial flow, this jittering radial flow should have generated sustained visual--vestibular conflicts--previously thought to always reduce/impair vection. We attempted to ascertain the essential stimulus features for this jitter advantage for vection by examining three novel types of jitter display. While adding incoherent jitter to radial flow was found to impair vection, adding coherent non-perspective jitter had little effect on this subjective experience (contrary to the notion that jitter improves vection by reducing adaptation to radial flow). Importantly, we found that coherent perspective jitter not only improves the vection induced by radial flow, but it also appears to induce modest vection by itself (demonstrating that vection can still occur when there is an extreme mismatch between actual and expected vestibular activity). These results suggest that the previously demonstrated advantage for coherent perspective jitter was due (in part at least) to jittering vection combining with forwards vection in depth to produce a more compelling overall vection experience.
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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 | 0.001 |
| 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".