Strategies for the Integration of Posture and Movement During Reaching in the Cat
Bibliographic record
Abstract
We have examined the relationship between the movement and the anticipatory postural adjustments (APAs) that precede that movement during a reaching task in the cat. We recorded ground reaction forces in all 3 planes from all 4 limbs as well as electromyographic (EMG) activity from limb and axial muscles. The reaching movement was always preceded by an APA that was characterized by a loading of the reaching forelimb and an unloading of the support forelimb. This loading of the reaching forelimb was preceded, and accompanied, by increased activity in shoulder and limb extensor muscles of the reaching limb; extensor muscle activity in the supporting limb was simultaneously decreased. An important finding from this study was that the onset of the APA and of the movement was temporally decoupled. Analyses of the onset of EMG activity showed that most of the muscles that we recorded could be classified as either related to the APA or related to the movement. These results support the idea of distributed, and perhaps independent, systems for the execution of the APA and of the prime movement. There was also postural activity in the supporting limb during the movement. Analysis of this activity, which is also anticipatory in nature, suggests that it was tightly linked to the movement. We suggest that this postural response is signaled as part of the command for movement. Some muscles, particularly the extensors of the reaching limb, received convergent input from the command signals for the APA and for the movement.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".