Sensory Perturbations from Hindlimb Cutaneous Afferents Generate Coordinated Functional Responses in All Four Limbs during Locomotion in Intact Cats
Bibliographic record
Abstract
Coordinating the four limbs is an important feature of terrestrial mammalian locomotion. When the foot dorsum contacts an obstacle, cutaneous mechanoreceptors send afferent signals to the spinal cord to elicit coordinated reflex responses in the four limbs to ensure dynamic balance and forward progression. To determine how the locomotor pattern of all four limbs changes in response to a sensory perturbation evoked by activating cutaneous afferents from one hindlimb, we electrically stimulated the superficial peroneal (SP) nerve with a relatively long train at four different phases (mid-stance, stance-to-swing transition, mid-swing, and swing-to-stance transition) of the hindlimb cycle in seven adult cats. The largest functional effects of the stimulation were found at mid-swing and at the stance-to-swing transition with several changes in the ipsilateral hindlimb, such as increased activity in muscles that flex the knee and hip joints, increased joint flexion and toe height, increased stride/step lengths and increased swing duration. We also observed several changes in support periods to shift support from the stimulated hindlimb to the other three limbs. The same stimulation applied at mid-stance and the swing-to-stance transition produced more subtle changes in the pattern. We observed no changes in stride and step lengths in the ipsilateral hindlimb with stimulation in these phases. We did observe some slightly greater flexions at the knee and ankle joints with stimulation at mid-stance and a reduction in double support periods and increase in triple support. Our results show that correcting or preventing stumbling involves functional contributions from all four limbs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".