Integration of auditory input with vestibular and neck proprioceptive information in the interpretation of dynamic sound localization cues
Bibliographic record
Abstract
To determine the front/back location of a sound source via head rotation, the auditory system must integrate sensorimotor information about head motion with the dynamic acoustic cues resulting from motion of the source relative to the head. In order to determine the influence of vestibular and proprioceptive cues on processing of dynamic acoustic cues, we measured, in active, passive, and counter-rotation conditions, listeners' ability to discriminate front/rear locations of low-frequency sounds not accurately localizable without head motion. Targets were presented over headphones during head rotations using dynamic virtual auditory space methods. In the active condition, the subject performed a head-on-body rotation, which provided vestibular and neck proprioceptive information. In the passive condition, proprioceptive information was minimized by whole-body rotation with no neck movement using a motorized rotating chair. In the counter-rotation condition, the subject performed a head-on-body rotation while the body was counter-rotated, which minimized vestibular input by keeping the head still in space. Dynamic acoustic cues corresponded to the head-on-body angle. Discrimination was accurate in active and passive conditions, but near chance under counter-rotation, suggesting that vestibular inputs are necessary and sufficient to inform the auditory system about head movement, whereas proprioceptive cues are neither necessary nor sufficient.
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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".