Reach adaptation and proprioceptive recalibration following terminal visual feedback of the hand
Bibliographic record
Abstract
We have shown that when subjects reach with continuous, misaligned visual feedback of their hand, their reaches are adapted and proprioceptive sense of hand position is recalibrated to partially match the visual feedback (Salomonczyk et al., 2011). It is unclear if similar changes arise after reaching with visual feedback that is provided only at the end of the reach (i.e., terminal feedback), when there are shorter temporal intervals for subjects to experience concurrent visual and proprioceptive feedback. Subjects reached to targets with an aligned hand-cursor that provided visual feedback at the end of each reach movement across a 99-trial training block, and with a rotated cursor over three successive blocks of 99 trials each. After each block, no cursor reaches, to measure aftereffects, and felt hand positions were measured. Felt hand position was determined by having subjects indicate the position of their unseen hand relative to a reference marker. We found that subjects adapted their reaches following training with rotated terminal visual feedback, yet slightly less (i.e., reach aftereffects were smaller), than subjects from a previous study who experienced continuous visual feedback. Nonetheless, current subjects recalibrated their sense of felt hand position in the direction of the altered visual feedback, but this proprioceptive change increased incrementally over the three rotated training blocks. Final proprioceptive recalibration levels were comparable to our previous studies in which subjects performed the same task with continuous visual feedback. Thus, compared to reach training with continuous, but altered visual feedback, subjects who received terminal altered visual feedback of the hand produced significant but smaller reach aftereffects and similar changes in hand proprioception when given extra training. Taken together, results suggest that terminal feedback of the hand is sufficient to drive motor adaptation, and also proprioceptive recalibration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".