Response of Retinal Ganglion Cells to Electrical Stimulation: From Prosthesis to "Seeing'"
Bibliographic record
Abstract
Electric stimulation is a promising method of restoring vision for those suffering from retinal degenerative diseases. To understand how retinal prostheses restore vision, computer models were developed to approximate the visual pathway. First, the electric potential generated by the subretinal implant within the retinal tissue was solved using Maxwell’s equation through finite-element method. Next, the primary neural response was calculated through the implementation of a recently proposed model of the retinal bipolar cell where the Hodgkin-Huxley equations and the cable model were solved for ten ionic currents. Finally, the entropy theory was introduced to calculate the ganglion response using the output of the bipolar response. For the first time, aspects of visual performance such as brightness and temporal response can be estimated for a subretinal implant. While these techniques have been developed to predict the biological response of any subretinal implant, much of the work presented here has been tailored towards a novel, passive implant developed by collaborators at Okayama University called the OUReP.
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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) | 0.003 | 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".