Assessing Individual Neuronal Activity Across the Intact Brain: Using Hybridization Chain Reaction (HCR) to Detect<i>Arc</i>mRNA Localized to the Nucleus in Volumes of Cleared Brain Tissue
Bibliographic record
Abstract
Arc (activity-regulated cytoskeleton-associated protein) is an immediate early gene that may be used to label recently active neurons. Arc is transcribed following neuronal activity, and its mRNA is then rapidly transported to dendrites. This feature allows nuclear-localized Arc mRNA to define ensembles of recently active neurons in systems or circuit neuroscience. However, typical in situ hybridization techniques severely constrain the thickness of the tissue specimen (typically 20-µm brain slices). Here, we describe a protocol for visualizing intranuclear Arc mRNA in large (4 × 4 × 3 mm) volumes of intact mouse brain tissue. We combined a tissue clearing protocol (iDISCO+) with an advanced in situ hybridization technique (hybridization chain reaction [HCR]) to detect nuclear-localized Arc mRNA in whole, intact brain regions without the need for brain sectioning or reconstruction. We successfully applied this protocol to image ensembles of neurons of the basolateral amygdala in mice that are active following the recall of a conditioned fear memory. © 2018 by John Wiley & Sons, Inc.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".