Muscle Spasms after Spinal Cord Injury Stem from Changes in Motoneuron Excitability and Synaptic Inhibition, Not Synaptic Excitation
Bibliographic record
Abstract
Muscle spasms are common in chronic spinal cord injury (SCI), posing challenges to rehabilitation and daily activities. Pharmacological management of spasms mostly targets suppression of excitatory inputs, an approach known to hinder motor recovery. To identify better targets, we investigated changes in inhibitory and excitatory synaptic inputs to motoneurons as well as motoneuron excitability in chronic SCI. We induced either a complete or incomplete SCI in adult mice of either sex and divided those with incomplete injury into low or high functional recovery groups. Their sacrocaudal spinal cords were then extracted and used to study plasticity below injury, with tissue from naive animals as a control. Electrical stimulation of the dorsal roots elicited spasm-like activity in preparations of chronic severe SCI but not in the control. To evaluate overall synaptic inhibition activated by sensory stimulation, we measured the rate-dependent depression of spinal root reflexes. We found inhibitory inputs to be impaired in chronic injury models. When synaptic inhibition was blocked pharmacologically, all preparations became clearly spastic, even the control. However, preparations with chronic injuries generated longer spasms than control. We then measured excitatory postsynaptic currents (EPSCs) in motoneurons during sensory-evoked spasms. The data showed no difference in the amplitude of EPSCs or their conductance among animal groups. Nonetheless, we found that motoneuron persistent inward currents activated by the EPSCs were increased in chronic SCI. These findings suggest that changes in motoneuron excitability and synaptic inhibition, rather than excitation, contribute to spasms and are better suited for more effective therapeutic interventions. Significance Statement Neural plasticity following spinal cord injury is crucial for recovery of motor function. Unfortunately, this process is blemished by maladaptive changes that can cause muscle spasms. Pharmacological alleviation of spasms without compromising the recovery of motor function has proven to be challenging. Here, we investigated changes in fundamental spinal mechanisms that can cause spasms post-injury. Our data suggest that the current management strategy for spasms is misdirected toward suppressing excitatory inputs, a mechanism that we found unaltered after injury, which can lead to further motor weakness. Instead, this study shows that more promising approaches might involve restoring synaptic inhibition or modulating motoneuron excitability.
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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) | 0.001 | 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".