Intraspinal Microstimulation Excites Multisegmental Sensory Afferents at Lower Stimulus Levels Than Local α-Motoneuron Responses
Bibliographic record
Abstract
Microstimulation within the motor regions of the spinal cord is often assumed to activate motoneurons and propriospinal neurons close to the electrode tip. However, previous work has shown that intraspinal microstimulation (ISMS) in the gray matter activates sensory afferent axons as well as alpha-motoneurons (MNs). Here we report on the recruitment of sensory afferent axons and MNs as ISMS amplitudes increased. Intraspinal microstimulation was applied through microwires implanted in the dorsal horn, intermediate region and ventral horn of the L(5)-L(7) segments of the spinal cord in four acutely decerebrated cats, two of which had been chronically spinalized. Activation of sensory axons was detected with electroneurographic recordings from dorsal roots. Activation of MNs was detected with electromyographic (EMG) recordings from hindlimb muscles. Sensory axons were nearly always activated at lower stimulus levels than MNs irrespective of the stimulating electrode location. EMG response latencies decreased as ISMS stimulus intensities increased, suggesting that MNs were first activated transsynaptically and then directly as intensity increased. ISMS elicited antidromic activity in dorsal root filaments with entry zones up to 17 mm rostral and caudal to the stimulation sites. We posit that action potentials elicited in localized terminal branches of afferents spread antidromically to all terminal branches of the afferents and transsynaptically excite MNs and interneurons far removed from the stimulation site. This may help explain how focal ISMS can activate many MNs of a muscle even though they are distributed in long thin columns.
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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".