The impact of auditory feedback on reaching movements with induced paresthesia
Bibliographic record
Abstract
Beyond visual feedback, somatosensory feedback provides information to help determine limb locations and movement accuracy. Previously we found that induced paresthesia removed the predicted movement time (MT) and time to peak velocity (ttPV) differences for reaching movements in vision and no vision conditions. Induced paresthesia also led to early end-position bias, but only when vision of limb was unavailable. The present study investigated if adding auditory feedback for accurate reaching trials improves reaching movements when vision is removed. Fourteen healthy right-handed participants (9 males, M=22.7[SD=2.9] years), performed 400 reaching movements over two days. Four possible targets were paired with four experimental condition combinations: Vision/No Vision; Paresthesia/No Paresthesia. Order of the target locations and visual targets were blocked and counterbalanced. Visual feedback was removed using visual occlusion spectacles (PLATO, Translucent Technologies). Median nerve paresthesia was temporarily induced using a constant current stimulator (DS7AH, Digitimer), and standardized sensory testing confirmed disrupted feedback. Participants were motivated to improve their MTs while maintaining endpoint accuracy with incentives for accurate movements with shorter MTs. Movements were recorded using a 3D motion analysis system at 300Hz (Optotrak-3D Investigator, NDI) and analyzed using a 2 Vision by 2 Paresthesia by 2 Performance (Early trials/Late trials) repeated measures ANOVA. Analyses revealed that participants’ reaction times improved with practice, MTs remained unchanged. A Vision by Early/Late Performance interaction revealed that participants decreased their ttPV only when vision was available (early=192ms; late=179ms). A Paresthesia by Movement Proportion by Performance interaction revealed that with paresthesia trial-trial variability of the limb position increased from early to late performance, however, a difference was no longer present at endpoint. In contrast, limb position variability decreased from early to late performance when paresthesia was not present. The present results support the use of auditory cues to mitigate the detrimental effect of paresthesia on movement accuracy. Acknowledgments: This project was funded by Manitoba Medical Service Foundation, Manitoba Health Research Council and Natural Sciences and Engineering Research Council. We would like to thank Brie Page, Tamires Prado and Aric Bremer for their help with data collection.
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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 | 0.003 |
| 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) | 0.002 | 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".