The effect of anisotropy on the potential distribution in biological tissue and its impact on nerve excitation simulations
Bibliographic record
Abstract
We present a finite difference solution of the potential distribution associated with electrical current stimulation in an anisotropic in-homogeneous tissue environment and compare it to the isotropic case. The results demonstrate that there can be significant errors associated with the assumption of isotropic tissue properties in calculating the potential distribution along an axon in nerve excitation simulations. These errors can have a significant impact on predicted nerve fiber recruitment patterns when evaluating the efficacy of specific surface or intramuscular stimulus electrode configurations. The results of this study also suggest when a more comprehensive tissue model should be implemented in an electrode design study. Simulation results indicate that the isotropy assumption is worst under bipolar electrode stimulation as opposed to monopolar stimulation and that the bipolar error increases as the distance between electrodes decreases. In light of these results, it is concluded that in order to avoid large errors in the calculated potential distribution along an axon, the isotropy assumption should only be used when the transverse depth from the electrode to the nerve is relatively small.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".