<i>Neurog1</i>and<i>Neurog2</i>Control Two Waves of Neuronal Differentiation in the Piriform Cortex
Bibliographic record
Abstract
The three-layered piriform cortex, an integral part of the olfactory system, processes odor information relayed by olfactory bulb mitral cells. Specifically, mitral cell axons form the lateral olfactory tract (LOT) by targeting lateral olfactory tract (lot) guidepost cells in the piriform cortex. While lot cells and other piriform cortical neurons share a pallial origin, the factors that specify their precise phenotypes are poorly understood. Here we show that in mouse, the proneural genes Neurog1 and Neurog2 are coexpressed in the ventral pallium, a progenitor pool that first gives rise to Cajal-Retzius (CR) cells, which populate layer I of all cortical domains, and later to layer II/III neurons of the piriform cortex. Using loss-of-function and gain-of-function approaches, we find that Neurog1 has a unique early role in reducing CR cell neurogenesis by tempering Neurog2's proneural activity. In addition, Neurog1 and Neurog2 have redundant functions in the ventral pallium, acting in two phases to first specify a CR cell fate and later to specify layer II/III piriform cortex neuronal identities. In the early phase, Neurog1 and Neurog2 are also required for lot cell differentiation, which we reveal are a subset of CR neurons, the loss of which prevents mitral cell axon innervation and LOT formation. Consequently, mutation of Trp73, a CR-specific cortical gene, results in lot cell and LOT axon displacement. Neurog1 and Neurog2 thus have unique and redundant functions in the piriform cortex, controlling the timing of differentiation of early-born CR/lot cells and specifying the identities of later-born layer II/III neurons.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".