Single-nucleus RNA sequencing of mouse auditory cortex reveals critical period triggers and brakes
Bibliographic record
Abstract
Auditory experience drives neural circuit refinement during windows of heightened brain plasticity, but little is known about the genetic regulation of this developmental process. The primary auditory cortex (A1) of mice exhibits a critical period for thalamocortical connectivity between postnatal days P12 and P15, during which tone exposure alters the tonotopic topography of A1. We hypothesized that a coordinated, multicellular transcriptional program governs this window for patterning of the auditory cortex. To generate a robust multicellular map of gene expression, we performed droplet-based, single-nucleus RNA sequencing (snRNA-seq) of A1 across three developmental time points (P10, P15, and P20) spanning the tonotopic critical period. We also tone-reared mice (7 kHz pips) during the 3-d critical period and collected A1 at P15 and P20. We identified and profiled both neuronal (glutamatergic and GABAergic) and nonneuronal (oligodendrocytes, microglia, astrocytes, and endothelial) cell types. By comparing normal- and tone-reared mice, we found hundreds of genes across cell types showing altered expression as a result of sensory manipulation during the critical period. Functional voltage-sensitive dye imaging confirmed GABA circuit function determines critical period onset, while Nogo receptor signaling is required for its closure. We further uncovered previously unknown effects of developmental tone exposure on trajectories of gene expression in interneurons, as well as candidate genes that might execute tonotopic plasticity. Our single-nucleus transcriptomic resource of developing auditory cortex is thus a powerful discovery platform with which to identify mediators of tonotopic plasticity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".