Imaging Neurons within Thick Brain Sections Using the Golgi-Cox Method
Bibliographic record
Abstract
The Golgi-Cox method of neuron staining has been employed for more than two hundred years to advance our understanding of neuron morphology within histological brain samples. While it is preferable from a practical perspective to prepare brain sections at the greatest thickness possible, in order to increase the probability of identifying stained neurons that are fully contained within single sections, this approach is limited from a technical perspective by the working distance of high-magnification microscope objectives. We report here a protocol to stain neurons using the Golgi-Cox method in mouse brain sections that are cut at 500 μm thickness, and to visualize neurons throughout the depth of these sections using an upright microscope fitted with a high-resolution 30X 1.05 N.A. silicone oil-immersion objective that has an 800 μm working distance. We also report two useful variants of this protocol that may be employed to counterstain the surface of mounted brain sections with the cresyl violet Nissl stain, or to freeze whole brains for long-term storage prior to sectioning and final processing. The main protocol and its two variants produce stained thick brain sections, throughout which full neuron dendritic trees and dendrite spines may be reliably visualized and quantified.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".