Laminar distribution of cortical projection neurons to the pulvinar: A comparative study in cats and mice
Bibliographic record
Abstract
The cortical processing of visual information is thought to follow a hierarchical framework. This framework of connections between visual areas is based on the laminar patterns of direct feedforward and feedback cortico-cortical projections. However, this view ignores the cortico-thalamo-cortical projections to the pulvinar nucleus in the thalamus, which provides an alternative transthalamic information transfer between cortical areas. It was proposed that corticothalamic (CT) pathways follow a similar hierarchical pattern as cortico-cortical connections. Two main types of CT projections have been recognized: drivers and modulators. Drivers originate mainly in Layer 5 whereas modulators are from Layer 6. Little is known about the laminar distribution of these projections to the pulvinar across visual cortical areas. Here, we analyzed the distribution of CT neurons projecting to the lateral posterior (LP) thalamus in two species: cats and mice. Injections of the retrograde tracer fragment B of cholera toxin (CTb) were performed in the LP. The morphology and cortical laminar distribution of CTb-labeled neurons was assessed. In cats, neurons were mostly found in Layer 6 except in Area 17, where they were mostly in Layer 5. In contrast, CT neurons in mice were mostly located in Layer 6 across all areas. Thus, our results demonstrate that CT projections in mice do not follow the same organization as cats suggesting that the transthalamic pathways play distinct roles in these species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".