Critical Points in the Forelimb Fictive Locomotor Cycle and Motor Coordination: Evidence From the Effects of Tonic Proprioceptive Perturbations in the Cat
Bibliographic record
Abstract
During locomotion, the limbs of one girdle must remain coordinated in different conditions. To understand the neural mechanisms underlying such coordination, tonic protraction/ retraction of one shoulder or tonic flexion/extension of one elbow was applied during fictive locomotion in high decerebrate and paralyzed cats. We studied bilateral changes in the timing and amplitude characteristics of electroneurographic (ENG) muscle nerve bursts of cleidobrachialis (ClB, elbow flexor and shoulder protractor) and the two heads of triceps (long, TriLo, elbow extensor and shoulder retractor and lateral, TriLa, elbow extensor). Perturbations induced bilateral changes in amplitude and timing of ENG bursts that were anchored on certain critical points in the cycle. These critical points could correspond to morphological characteristics within the bursts or to bilateral onsets or offsets of ENG bursts. For instance, in response to shoulder and elbow perturbations, burst changes occur in relation to a fixed point, labeled point C, occurring at about mid-extensor burst and corresponding to a simultaneous abrupt increase in TriLa amplitude and a decrease in amplitude of contralateral ClB. At a point labeled B, corresponding to about mid-flexor burst, ClB amplitude increases above control with elbow extension or starts decreasing with shoulder protraction. Although cycle reorganization is specific for each type of tonic perturbation, a common feature is that the changes in burst duration are achieved through discrete shifts between consecutive critical points. It is postulated that coordination may be based on a discrete temporal cycle structure along which critical points delimiting burst components are shifted.
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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 | 0.000 |
| 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) | 0.001 | 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".