Inhibition and Facilitation of the Spinal Locomotor Central Pattern Generator and Reflex Circuits by Somatosensory Feedback From the Lumbar and Perineal Regions After Spinal Cord Injury
Bibliographic record
Abstract
Somatosensory feedback from peripheral receptors dynamically interacts with networks located in the spinal cord and brain to control mammalian locomotion. Although somatosensory feedback from the limbs plays a major role in regulating locomotor output, those from other regions, such as lumbar and perineal areas also shape locomotor activity. In mammals with a complete spinal cord injury, inputs from the lumbar region powerfully inhibit hindlimb locomotion, while those from the perineal region facilitate it. Our recent work in cats with a complete spinal cord injury shows that they also have opposite effects on cutaneous reflexes from the foot. Lumbar inputs increase the gain of reflexes while those from the perineal region decrease it. The purpose of this review is to discuss how somatosensory feedback from the lumbar and perineal regions modulate the spinal locomotor central pattern generator and reflex circuits after spinal cord injury and the possible mechanisms involved. We also discuss how spinal cord injury can lead to a loss of functional specificity through the abnormal activation of functions by somatosensory feedback, such as the concurrent activation of locomotion and micturition. Lastly, we discuss the potential functions of somatosensory feedback from the lumbar and perineal regions and their potential for promoting motor recovery after spinal cord injury.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".