Pantomime-Grasping: Advance Knowledge of Haptic Feedback Availability Supports an Absolute Visuo-Haptic Calibration
Bibliographic record
Abstract
An emerging issue in movement neurosciences is whether haptic feedback influences the nature of the information supporting a simulated grasping response (i.e., pantomime-grasping). In particular, recent work by our group contrasted pantomime-grasping responses performed with (i.e., PH+ trials) and without (i.e., PH- trials) terminal haptic feedback in separate blocks of trials. Results showed that PH- trials were mediated via relative visual information. In contrast, PH+ trials showed evidence of an absolute visuo-haptic calibration-a finding attributed to an error signal derived from a comparison between expected and actual haptic feedback (i.e., an internal forward model). The present study examined whether advanced knowledge of haptic feedback availability influences the aforementioned calibration process. To that end, PH- and PH+ trials were completed in separate blocks (i.e., the feedback schedule used in our group's previous study) and a block wherein PH- and PH+ trials were randomly interleaved on a trial-by-trial basis (i.e., random feedback schedule). In other words, the random feedback schedule precluded participants from predicting whether haptic feedback would be available at the movement goal location. We computed just-noticeable-difference (JND) values to determine whether responses adhered to, or violated, the relative psychophysical principles of Weber's law. Results for the blocked feedback schedule replicated our group's previous work, whereas in the random feedback schedule PH- and PH+ trials were supported via relative visual information. Accordingly, we propose that a priori knowledge of haptic feedback is necessary to support an absolute visuo-haptic calibration. Moreover, our results demonstrate that the presence and expectancy of haptic feedback is an important consideration in contrasting the behavioral and neural properties of natural and simulated grasping.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".