Motoneuron output regulated by ionic channels: a modeling study of motoneuron frequency-current relationships during fictive locomotion
Bibliographic record
Abstract
Cat lumbar motoneurons display changes in membrane properties during fictive locomotion. These changes include reduction of input resistance and afterhyperpolarization, hyperpolarization of voltage threshold, and voltage-dependent excitation of the motoneurons. The state-dependent alteration of membrane properties leads to dramatic changes in frequency-current (F-I) relationship. The mechanism underlying these changes remains unknown. Using a motoneuron model combined with electrophysiological data, we investigated the channel mechanisms underlying the regulation of motoneuronal excitability and motor output. Simulation results showed that upregulation of transient sodium, persistent sodium, or Ca v 1.3 calcium conductances or downregulation of calcium-activated potassium or KCNQ/K v 7 potassium conductances could increase motoneuronal excitability and motor output through hyperpolarizing (left shifting) the F-I relationships or increasing the F-I slopes, whereas downregulation of input resistance or upregulation of potassium-mediated leak conductance produced the opposite effects. The excitatory phase of locomotor drive potentials (LDPs) also substantially hyperpolarized the F-I relationships and increased the F-I slopes, whereas the inhibitory phase of the LDPs had opposite effects to a similar extent. The simulation results also showed that none of the individual channel modulations could produce all the changes in the F-I relationships. The effects of modulation of Ca v 1.3 and KCNQ/K v 7 on F-I relationships were supported by slice experiments with the Ca v 1.3 agonist Bay K8644 and the KCNQ/K v 7 antagonist XE-991. The conclusion is that the varying changes in F-I relationships during fictive locomotion could be regulated by multichannel modulations. This study provides insight into the ionic basis for control of motor output in walking. NEW & NOTEWORTHY Mammalian spinal motoneurons have their excitability adapted to facilitate recruitment and firing during locomotion. Cat lumbar motoneurons display dramatic changes in membrane properties during fictive locomotion. These changes lead to a varying alteration of frequency-current relationship. The mechanisms underlying the changes remain unknown. In particular, little is known about the ionic basis for regulation of motoneuronal excitability and thus control of the motor output for walking by the spinal motor system.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".