Effects of head orientation on the perceived tilt of a static line and 3D global motion.
Bibliographic record
Abstract
When the head is tilted an objectively vertical (or horizontal) line is typically perceived as tilted. We explored whether this shift occurs when viewing 3D global motion displays. Global motion is processed, in part, in cortical area MST, which is believed to be involved in multisensory integration and may facilitate the mapping of spatial reference frames. Thus, we hypothesized that observers may be less susceptible to these biases for global motion compared to line displays. Observers stood, and lay left and right side down, while viewing a static line or random-dot 3D global motion display. The line and motion direction were tilted 0°, ±5°, ±10°, ±15°, ±20°, and ±25° from the gravitational vertical, and in a separate block tilted from the horizontal. After each trial, observers indicated whether the tilt was clockwise or counterclockwise from the perceived vertical or horizontal with a button press. Psychometric functions were fit to the data and shifts in the point of subjective equality (PSE) were measured. These shifts were greater when lying on the side than standing. These shifts were biased in the direction of the head tilt, consistent with the so-called A-effect. However, contrary to an earlier study by De Vrijer, Medendorp, and Van Gisbergen (2008, J Neurophysiol, 99: 915–930) that found similar PSE shifts for lines and 2D planar motion, we found significantly larger shifts for the static line than 3D global motion. There was no appreciable difference between the shift magnitude in the tilt-from-vertical and horizontal conditions. Furthermore, the direction of motion (up/down, left/right) had no significant influence on the PSE. The results will be discussed in terms of the sensory integration of motion information in cortical areas. Meeting abstract presented at VSS 2013
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 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) | 0.003 | 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".