Common Encoding of Novel Dynamic Loads Applied to the Hand and Arm
Bibliographic record
Abstract
In manual action, the relationship between a given motor command and the ensuing movement depends on the dynamics of both the arm and hand-held objects. Skilled performance relies on the brain learning both these dynamics, and previous studies have examined how people adapt to novel loads applied to either the hand or the arm. In this study, we ask whether these different kinds of load are represented independently as a result of changes in cutaneous feedback and hand-arm coordination. We used a robotic apparatus that could either apply forces to an object held in the subject's hand or directly to the segments of the arm. We tested whether subjects could retain learning of a force field applied to the hand after subsequently experiencing the opposing field applied to the arm (or vice versa), or whether retrograde interference would be observed. In separate experiments, we used force fields and torque fields that were linearly related to either hand or joint velocities, respectively. Our finding of complete interference between opposing fields suggests that loads applied to the arm and hand are not represented independently by the sensorimotor system. This interference occurred despite markedly different cutaneous inputs that were directly related to the movement task. This result suggests that the brain represents dynamics independently of these sensory inputs. In addition, we found that the rate at which subjects adapted to a given force field, specified either in hand or joint coordinates, was independent of whether the forces were applied to the hand or arm segments.
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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 | 0.000 |
| 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".