Cortical Correlates of the Simulated Viewpoint Oscillation Advantage for Vection
Bibliographic record
Abstract
Behavioural studies have consistently found stronger vection responses for oscillating, compared to smooth/constant, patterns of radial flow (the simulated viewpoint oscillation advantage for vection). Traditional accounts predict that simulated viewpoint oscillation should impair vection by increasing visual–vestibular conflicts in stationary observers (as this visual oscillation simulates self-accelerations that should strongly stimulate the vestibular apparatus). However, support for increased vestibular activity during accelerating vection has been mixed in the brain imaging literature. This fMRI study examined BOLD activity in visual (cingulate sulcus visual area — CSv; medial temporal complex — MT+; V6; precuneus motion area — PcM) and vestibular regions (parieto-insular vestibular cortex — PIVC/posterior insular cortex — PIC; ventral intraparietal region — VIP) when stationary observers were exposed to vection-inducing optic flow (i.e., globally coherent oscillating and smooth self-motion displays) as well as two suitable control displays. In line with earlier studies in which no vection occurred, CSv and PIVC/PIC both showed significantly increased BOLD activity during oscillating global motion compared to the other motion conditions (although this effect was found for fewer subjects in PIVC/PIC). The increase in BOLD activity in PIVC/PIC during prolonged exposure to the oscillating (compared to smooth) patterns of global optical flow appears consistent with vestibular facilitation.
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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 | 0.002 |
| 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) | 0.002 | 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".