Feasibility of differentially measuring afferent and efferent neural activity with a single nerve cuff electrode
Bibliographic record
Abstract
OBJECTIVE: Advances in electrode technology have facilitated the development of neuroprostheses for restoring motor/sensory function in disabled individuals. Information extracted from a whole nerve, recorded using cuffs, can provide signals that control the operation of neuroprostheses. However, the amount of information that can be extracted from a tripolar cuff-which provides the highest signal-to-noise ratio (SNR)-is limited. The physical symmetry of the tripolar cuff results in neural recordings that cannot differentiate afferent versus efferent signals. In this study, we introduced a tetrapolar cuff to achieve low-noise and directionally sensitive recording. APPROACH: The tetrapolar cuff was initially designed using a computational approach. A finite element model was used to solve the electric potential generated at the electrode contacts by active electrical sources, such as the nodes of Ranvier and an artifact noise source. The resulting single fiber action potentials (SFAPs) and artifact noise signals (ANS) were used to characterize the performance of the tetrapolar configuration of the electrode length (EL) and electrode edge length (EEL) on simulated SFAP and ANS. The feasibility of using a tetrapolar cuff to differentiate afferent/efferent action potentials by applying potassium chloride in anesthetized rats was also investigated. MAIN RESULTS: Both the computational and experimental results of this study indicated that directional recording can be achieved using a tetrapolar cuff. Testing different design criteria (e.g. EL and EEL) showed that at EL values above 15 mm and EEL ⩾ 2 mm, the tetrapolar cuffs can yield larger SNRs than equally-sized tripolar cuffs. SIGNIFICANCE: This study indicated that low-noise directionally sensitive measurement of neural activity can be achieved with a tetrapolar cuff. The experimental results confirmed the feasibility of using a tetrapolar cuff to differentiate afferent/efferent signals by applying potassium chloride. Further work is needed to determine whether the tetrapolar cuff can differentiate afferent/efferent physiologically elicited neural activities.
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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 | 0.001 | 0.001 |
| 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".