Generation of excitatory and inhibitory neurons from common progenitors via Notch signaling in the cerebellum
Bibliographic record
Abstract
Brain neurons arise from relatively few progenitors generating an enormous diversity of neuronal types. Nonetheless, a cardinal feature of mammalian brain neurogenesis is thought to be that excitatory and inhibitory neurons derive from separate, spatially segregated progenitors. Whether bi-potential progenitors with an intrinsic capacity to generate both lineages exist and how such a fate decision may be regulated are unknown. Using cerebellar development as a model, we discover that individual progenitors can give rise to both inhibitory and excitatory lineages. Gradations of Notch activity determine the fates of the progenitors and their daughters. Daughters with the highest levels of Notch activity retain the progenitor fate, while intermediate levels of Notch activity generate inhibitory neurons, and daughters with very low levels of Notch signaling adopt the excitatory fate. Therefore, Notch-mediated binary cell fate choice is a mechanism for regulating the ratio of excitatory to inhibitory neurons from common progenitors.
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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 | 0.000 | 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) | 0.000 | 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".