Reversal of the late phase of spike frequency adaptation in cat spinal motoneurons during fictive locomotion
Bibliographic record
Abstract
In spinal motoneurons, late spike frequency adaptation (SFA) is defined as the slowing of the firing rate over tens of seconds and can be seen during sustained or intermittent current injection. Although the function of late SFA is not known, it may result in a decrease in force production over time, or muscle fatigue. Because locomotion can persist for long periods of time without fatigue, late SFA was studied using intracellular recordings from adult cat motoneurons during fictive locomotion. Of eight lumbar motoneurons studied, all showed late adaptation during control conditions, but none demonstrated late adaptation during locomotor activity. The most consistent properties that correlated with the presence or absence of late SFA were those related to availability of fast, inactivating sodium channels, particularly action potential rate of rise. Evidence of the reversal of late SFA during locomotion was present for several minutes following locomotor trials, consistent with the suggestion that SFA is modulated through slow metabotropic pathways. The abolition of late adaptation in spinal motoneurons during fictive locomotion is an example of a state-dependent change in the "intrinsic" properties of mammalian motoneurons. This change contributes to increased excitability of motoneurons during locomotion and results in robust firing during sustained 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 | 0.001 |
| 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 | 0.000 |
| 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".