Distinct Actions of<i>Emx1</i>,<i>Emx2</i>, and<i>Pax6</i>in Regulating the Specification of Areas in the Developing Neocortex
Bibliographic record
Abstract
The mammalian neocortex is organized into subdivisions referred to as areas that are distinguished from one another by differences in architecture, axonal connections, and function. The transcription factors EMX1, EMX2, and PAX6 have been proposed to regulate arealization. Emx1 and Emx2 are expressed by progenitor cells in a low rostrolateral to high caudomedial gradient across the embryonic neocortex, and Pax6 is expressed in a high rostrolateral to low caudomedial gradient. Recent evidence has suggested that EMX2 and PAX6 have a role in the genetic regulation of arealization. Here we use a panel of seven genes (Cad6, Cad8, Id2,RZRβ, p75, EphA7, and ephrin-A5) representative of a broad range of proteins as complementary markers of positional identity to obtain a more thorough assessment of the suggested roles for EMX2 and PAX6 in arealization, and in addition to assess the proposed but untested role for EMX1 in arealization. Orderly changes in the size and positioning of domains of marker expression in Emx2 andPax6 mutants strongly imply that rostrolateral areas (motor and somatosensory) are expanded, whereas caudomedial areas (visual) are reduced in Emx2 mutants and that opposite effects occur in Pax6 mutants, consistent with their opposing gradients of expression. In contrast, patterns of marker expression, as well as the distribution of area-specific thalamocortical projections, appear normal in Emx1mutants, indicating that they do not exhibit changes in arealization. This lack of a defined role for EMX1 in arealization is supported by our finding of similar shifts in patterns of marker expression inEmx1; Emx2 double mutants as in Emx2 mutants. Thus, our findings indicate that EMX2 and PAX6 regulate, in opposing manners, arealization of the neocortex and impart positional identity to cortical cells, whereas EMX1 appears not to have a role in this process.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".