Patch Clamp Recordings from Embryonic Zebrafish Mauthner Cells
Bibliographic record
Abstract
Mauthner cells (M-cells) are large reticulospinal neurons located in the hindbrain of teleost fish. They are key neurons involved in a characteristic behavior known as the C-start or escape response that occurs when the organism perceives a threat. The M-cell has been extensively studied in adult goldfish where it has been shown to receive a wide range of excitatory, inhibitory and neuromodulatory signals(1). We have been examining M-cell activity in embryonic zebrafish in order to study aspects of synaptic development in a vertebrate preparation. In the late 1990s Ali and colleagues developed a preparation for patch clamp recording from M-cells in zebrafish embryos, in which the CNS was largely intact(2,3,4). The objective at that time was to record synaptic activity from hindbrain neurons, spinal cord neurons and trunk skeletal muscle while maintaining functional synaptic connections within an intact brain-spinal cord preparation. This preparation is still used in our laboratory today. To examine the mechanisms underlying developmental synaptic plasticity, we record excitatory (AMPA and NMDA-mediated)(5,6) and inhibitory (GABA and glycine) synaptic currents from developing M-cells. Importantly, this unique preparation allows us to return to the same cell (M-cell) from preparation to preparation to carefully examine synaptic plasticity and neuro-development in an embryonic organism. The benefits provided by this preparation include 1) intact, functional synaptic connections onto the M-cell, 2) relatively inexpensive preparations, 3) a large supply of readily available embryos 4) the ability to return to the same cell type (i.e. M-cell) in every preparation, so that synaptic development at the level of an individual cell can be examined from fish to fish, and 5) imaging of whole preparations due to the transparent nature of the embryos.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".