Localization of Spinal Neurons Activated During Locomotion Using the<i>c-fos</i>Immunohistochemical Method
Bibliographic record
Abstract
The c-fos immunohistochemical method of activity-dependent labeling was used to localize locomotor-activated neurons in the adult cat spinal cord. In decerebrate cats, treadmill locomotion was evoked by electrical stimulation of the mesencephalic locomotor region (MLR). Spontaneous or MLR-evoked fictive locomotion was produced in decerebrate animals paralyzed with a neuromuscular blocking agent. After bouts of locomotion during a 7- to 9-h time period, the animals were perfused and the L3-S1 spinal cord segments removed for immunohistochemistry. Control animals were subjected to the same surgical procedures but no locomotor task. Labeled cells were concentrated in Rexed's laminae III and IV of the dorsal horn and laminae VII, VIII, and X of the intermediate zone/ventral horn after treadmill locomotion. Cells in laminae VII, VIII, and X were labeled after fictive locomotion, but labeling in the dorsal horn was much reduced. In control animals, c-fos labeling was a small fraction of that observed in the locomotor animals. The results suggest that labeled cells in laminae VII, VIII, and X are premotor interneurons involved in the production of locomotion, whereas the laminae III and IV cells are those activated during locomotion due to afferent feedback from the moving limb. c-fos-labeled cells were most numerous in the L5-L7 segments, consistent with the distribution of locomotor activated neurons detected through the use of MLR-evoked field potentials.
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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 | 0.001 | 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 | 0.001 |
| 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".