A multifaceted architectural framework of the mouse claustrum complex
Bibliographic record
Abstract
Accurate anatomical characterizations are necessary to investigate neural circuitry on a fine scale, but for the rodent claustrum complex (CC) this has yet to be fully accomplished. The CC is generally considered to comprise two major subdivisions, the claustrum (CL) and the dorsal endopiriform nucleus (DEn), but regional boundaries to these areas are highly debated. To address this, we conducted a multifaceted analysis of fiber- and cyto-architecture, genetic marker expression, and connectivity using mice of both sexes, to create a comprehensive guide for identifying and delineating borders to the CC. We identified four distinct subregions within the CC, subdividing both the CL and the DEn into two. Additionally, we conducted brain-wide tracing of inputs to the entire CC using a transgenic mouse line. Immunohistochemical staining against myelin basic protein (MBP), parvalbumin (PV), and calbindin (CB) revealed intricate fiber-architectural patterns enabling precise delineations of the CC and its subregions. Myelinated fibers were abundant in dorsal parts of the CL but absent in ventral parts, while parvalbumin labelled fibers occupied the entire CL. Calbindin staining revealed a central gap within the CL, which was also visible at levels anterior to the striatum. Furthermore, cells in the CL projecting to the retrosplenial-cortex were located within the myelin sparse area. By combining our own experimental data with digitally available datasets of gene expression and input connectivity, we could demonstrate that the proposed delineation scheme allows anchoring of datasets from different origins to a common reference framework. Significance statement Mice are a highly tractable model for studying the claustrum complex (CC). However, without a consensus on how to delineate the CC in rodents, comparing results between studies is challenging. It is therefore important to expand our anatomical knowledge of the CC, to match the level of detail needed to study its functional properties. Using multiple strategies for identifying claustral borders, we created a comprehensive guide to delineate the CC and its subregions. This anatomical framework will allow researchers to anchor future experimental data into a common reference space. We demonstrated the power of this new structural framework by combining our own experimental data with digitally available data on gene expression and input connectivity of the CC.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".