How our body influences our perception of the world
Bibliographic record
Abstract
Incorporating the fact that the senses are embodied is necessary for an organism to interpret sensory information. Before a unified perception of the world can be formed, sensory signals must be processed with reference to body representation. The various attributes of the body such as shape, proportion, posture, and movement can be both derived from the various sensory systems and can affect perception of the world (including the body itself). In this review we examine the relationships between sensory and motor information, body representations, and perceptions of the world and the body. We provide several examples of how the body affects perception (including but not limited to body perception). First we show that body orientation effects visual distance perception and object orientation. Also, visual-auditory crossmodal-correspondences depend on the orientation of the body: audio "high" frequencies correspond to a visual "up" defined by both gravity and body coordinates. Next, we show that perceived locations of touch is affected by the orientation of the head and eyes on the body, suggesting a visual component to coding body locations. Additionally, the reference-frame used for coding touch locations seems to depend on whether gaze is static or moved relative to the body during the tactile task. The perceived attributes of the body such as body size, affect tactile perception even at the level of detection thresholds and two-point discrimination. Next, long-range tactile masking provides clues to the posture of the body in a canonical body schema. Finally, ownership of seen body parts depends on the orientation and perspective of the body part in view. Together, all of these findings demonstrate how sensory and motor information, body representations, and perceptions (of the body and the world) are interdependent.
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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 | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".