Effects of Localized Intraspinal Injections of a Noradrenergic Blocker on Locomotion of High Decerebrate Cats
Bibliographic record
Abstract
Previous studies demonstrated that neuronal networks located in midlumbar segments (L3-L4) are critical for the expression of locomotion in cats following complete spinalization. In the present study the importance of several thoracolumbar segments (T8-L7) for the generation of spontaneous hindlimb locomotion in decerebrate cats was evaluated. Experiments were performed in high decerebrate cats (n = 18) walking spontaneously. Yohimbine, an alpha2-noradrenergic antagonist, was microinjected intraspinally in various thoracolumbar segments. Locomotor performance was evaluated with kinematics and electromyographic (EMG) recordings before and after each injection. When and if spontaneous locomotion (SL) was abolished, skin or perineal stimuli (exteroceptive stimuli) were used to trigger locomotion (exteroceptive-induced locomotion [EL]). Yohimbine injections at L3 or L4 completely inhibited SL and EL. In contrast, injections at T8 did not interfere with SL or EL. Injections at T10, T11, T12, L5, L6, and L7 inhibited SL but EL could still be evoked. Injections at T13, L1, and L2 had similar effects except that the quality of locomotion evoked by exteroceptive stimulation declined. Combined injections at T13, L1, and L2 abolished SL and EL, in contrast to injections restricted to the same individual segments. Simultaneous injections at L5, L6, and L7 also abolished SL but EL could still be induced. These results suggest that noradrenergic mechanisms in L3-L4 segments are involved in the expression of locomotion in decerebrate cats, whereas antagonizing noradrenergic inputs in individual rostral or caudal segments may alter the expression and overall quality of the locomotor pattern without abolishing locomotion.
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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) | 0.001 | 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 | 0.001 |
| 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".