Long‐range projections from sparse populations of GABAergic neurons in murine subplate
Bibliographic record
Abstract
Abstract The murine subplate contains some of the earliest generated populations of neurons in the cerebral cortex, which play an important role in the maturation of cortical inhibition. Here we present multiple lines of evidence, that the subplate itself is only very sparsely populated with GABAergic neurons at postnatal day (P)8. We used three different transgenic mouse lines, each of which labels a subset of GABAergic, ganglionic eminence derived neurons. Dlx5/6‐eGFP labels the most neurons in cortex (on average 11% of NEUN+ cells across all layers at P8) whereas CGE‐derived Lhx6‐Cre::Dlx1‐Venusfl cells are the sparsest (2% of NEUN+ cells across all layers at P8). There is significant variability in the layer distribution of labeled interneurons, with Dlx5/6‐eGFP and Lhx6‐Cre::R26R‐YFP being expressed most abundantly in Layer 5, whereas CGE‐derived Lhx6‐Cre::Dlx1‐Venusfl cells are least abundant in that layer. All three lines label at most 3% of NEUN+ neurons in the subplate, in contrast to L5, in which up to 30% of neurons are GFP+ in Dlx5/6‐eGFP. We assessed all three GABAergic populations for expression of the subplate neuron marker connective tissue growth factor (CTGF). CTGF labels up to two‐thirds of NEUN+ cells in the subplate, but was never found to colocalize with labeled GABAergic neurons in any of the three transgenic strains. Despite the GABAergic neuronal population in the subplate being sparse, long‐distance axonal connection tracing with carbocyanine dyes revealed that some Gad65‐GFP+ subplate cells form long‐range axonal projections to the internal capsule or callosum.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".