A Multimodal Micro-Optrode Combining Field and Single Unit Recording, Multispectral Detection and Photolabeling Capabilities
Bibliographic record
Abstract
Microelectrodes have been very instrumental and minimally invasive for in vivo functional studies from deep brain structures. However they are limited in the amount of information they provide. Here, we describe a, aluminum-coated, fibre optic-based glass microprobe with multiple electrical and optical detection capabilities while retaining tip dimensions that enable single cell measurements (diameter ≤10 µm). The probe enables optical separation from individual cells in transgenic mice expressing multiple fluorescent proteins in distinct populations of neurons within the same deep brain nucleus. It also enables color conversion of photoswitchable fluorescent proteins, which can be used for post-hoc identification of the recorded cells. While metal coating did not significantly improve the optical separation capabilities of the microprobe, the combination of metal on the outside of the probe and of a hollow core within the fiber yields a microelectrode enabling simultaneous single unit and population field potential recordings. The extended range of functionalities provided by the same microprobe thus opens several avenues for multidimensional structural and functional interrogation of single cells and their surrounding deep within the intact nervous system.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".