Out-of-Plane Focusing Grating on Implantable Neural Probes for Spatially Targeted Optogenetic Stimulation
Bibliographic record
Abstract
Optogenetics is a valuable tool in dissecting the functions of neural circuits by enabling the optical stimulation of genetically targeted neurons. One key challenge is delivering light at depth beyond the attenuation length in tissue. Implantable silicon nitride (SiN) waveguide-based nanophotonic probes offer complex optoelectronic integration and patterned illumination through grating couplers in a compact form factor, making them a unique tool for interrogating neural circuits [1]. We have previously demonstrated probes with gratings that emit steerable low-divergence beams and planar sheets [2–4]. In those works, the optical intensity decays exponentially from the probe, and neurons closest to the shank are excited. In this work, we present the design and characterization of neural probes with grating couplers that focus the light to a point above the plane of the probe for spatially precise targeting of neurons at potentially lower powers. Fig. 1 (a) and (b) show the neural probes, which were fabricated at Advanced Micro Foundry and had a 120nm-thick PECVD SiN waveguide layer.
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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".