Robust optical fiber patch-cords for in vivo optogenetic experiments in rats
Bibliographic record
Abstract
In vivo optogenetic experiments commonly employ long lengths of optical fiber to connect the light source (commonly a laser) to the optical fiber implants in the brain. Commercially available patch cords are expensive and break easily. Researchers have developed methods to build these cables in house for in vivo experiments with rodents [1-4]. However, the half-life of those patch cords is greatly reduced when they are used with behaving rats, which are strong enough to break the delicate cable tip and to bite through the optical fiber and furcation tubing. Based on [3] we have strengthened the patch-cord tip that connects to the optical implant, and we have incorporated multiple layers of shielding to produce more robust and resistant cladding. Here, we illustrate how to build these patch cords with FC or M3 connectors. However, the design can be adapted for use with other common optical-fiber connectors. We have saved time and money by using this design in our optical self-stimulation experiments with rats, which are commonly several months long and last four to eleven hours per session. The main advantages are: •Long half-life.•Resistant to moderate rodent bites.•Suitable for long in vivo optogenetic experiments with large rodents.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".