Selective Stimulation of Cat Sciatic Nerve Using an Array of Varying-Length Microelectrodes
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Bibliographic record
Abstract
Restoration of motor function to individuals who have had spinal cord injuries or stroke has been hampered by the lack of an interface to the peripheral nervous system. A suitable interface should provide selective stimulation of a large number of individual muscle groups with graded recruitment of force. We have developed a new neural interface, the Utah Slanted Electrode Array (USEA), that was designed to be implanted into peripheral nerves. Its goal is to provide such an interface that could be useful in rehabilitation as well as neuroscience applications. In this study, the stimulation capabilities of the USEA were evaluated in acute experiments in cat sciatic nerve. The recruitment properties and the selectivity of stimulation were examined by determining the target muscles excited by stimulation via each of the 100 electrodes in the array and using force transducers to record the force produced in these muscles. It is shown in the results that groups of up to 15 electrodes were inserted into individual fascicles. Stimulation slightly above threshold was selective to one muscle group for most individual electrodes. At higher currents, co-activation of agonist but not antagonist muscles was observed in some instances. Recruitment curves for the electrode array were broader with twitch thresholds starting at much lower currents than for cuff electrodes. In these experiments, it is also shown that certain combinations of electrode pairs, inserted into an individual fascicle, excite fiber populations with substantial overlap, whereas other pairs appear to address independent populations. We conclude that the USEA permits more selective stimulation at much lower current intensities with more graded recruitment of individual muscles than is achieved by conventional cuff electrodes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 it