Differential modulation of trunk muscle activation using thoracic epidural spinal stimulation
Bibliographic record
Abstract
Abstract Objective . Epidural spinal stimulation (ESS) has demonstrated promising functional improvements in trunk control following spinal cord injury (SCI). However, previous ESS studies targeting trunk muscle activation have been limited to stimulation over the eleventh thoracic to first lumbar vertebral levels, which may not be optimal based on anatomical evidence regarding trunk muscle innervation. In this light, the objective of this study was to investigate trunk muscle activity in response to ESS at varying stimulation locations above the thoracic spine. Approach. An electrode array was implanted above the thoracic spine of 13 participants. ESS-evoked responses in trunk muscles were quantified while stimulation location along the rostrocaudal and mediolateral axes of the spine was systematically manipulated. Main results. Ipsilateral ESS between the T6 and T10 vertebrae induced responses in all trunk muscles, resulting in average motor thresholds (MTs) and latencies of abdominal muscles ranging from 1.5 to 2.0 µ C and 7.4 to 9.2 ms, respectively; however, stimulation between the T8 and T10 vertebrae demonstrated lower MTs and shorter latencies. Ipsilateral stimulation resulted in 2.4 times greater maximum response amplitudes, 30% lower MTs, and 0.9 ms shorter latencies compared to contralateral stimulation. Significance . Our study provides quantitative evidence on the differential effects of ESS amplitude and location on trunk muscle activity while also suggesting that both afferent and efferent pathways contribute to ESS-evoked muscle activation. The results enhance our fundamental understanding of ESS-induced trunk muscle activity and have the potential to guide electrode placement for future therapeutic or restorative applications toward improving trunk control following SCI.
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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 | 0.000 | 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".