A simple implantation method for flexible, multisite microelectrodes into rat brains
Bibliographic record
Abstract
A long term functional and reliable coupling between neural tissue and implanted microelectrodes is the key issue in acquiring neural electrophysiological signals or therapeutically excite neural tissue. The currently often used rigid micro-electrodes are thought to cause a severe foreign body reaction resulting in a thick glial scar and consequently a poor tissue-electrode coupling in the chronic phase. We hypothesize, that this adverse effect might be remedied by probes compliant to the soft brain tissue, i.e., replacing rigid electrodes by flexible ones. Unfortunately, this flexibility comes at the price of a low stiffness, which makes targeted low trauma implantation very challenging. In this study, we demonstrate an adaptable and simple method to implant extremely flexible microprobes even to deep areas of rat's brain. Implantation of flexible probes is achieved by rod supported stereotactic insertion fostered by a hydrogel (2% agarose in PBS) cushion on the exposed skull. We were thus able to implant very flexible micro-probes in 70 rats as deep as the rodent's subthalamic nucleus. This work describes in detail the procedures and steps needed for minimal invasive, but reliable implantation of flexible probes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".