Visual coding of touch: Gaze direction affects perceived location of touches to the arm, torso, and head
Bibliographic record
Abstract
Gaze position has previously been found to affect the perceived location of visual, auditory, proprioceptive and tactile targets. This is compatible with the idea that perceived target location, regardless of modality, is coded in a visual reference frame and that the gaze angle is systematically underestimated in the coordinate transformations involved in the coding of location. We investigated whether touches to parts of the body that are not in view are also coded in a visual reference frame. Vibrotactile stimuli of 250 Hz and 50 ms duration were applied to the arm, front and back of the torso and to the forehead while the head and/or eyes were held eccentrically. Participants then centered their head and eyes before reporting the perceived location of the touch relative to a visual scale. Perceived touch location was shifted in the same direction as eccentric gaze position for all of the body parts tested, regardless of whether the body part was viewable (arm, front of torso) or not (back, forehead). Eye and head position had equivalent effects, even when the touch was applied to the head. These observations support the idea that touch is first coded in an internal representation of the body that is static and in a canonical position before being recoded into a visual reference frame. Overall, our data suggest that the entire body is coded visually, regardless of whether the body part is viewable. Meeting abstract presented at VSS 2012
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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) | 0.004 | 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".