Spatially patterned excitatory neuron subtypes and circuits within the claustrum
Bibliographic record
Abstract
uthorDespite being implicated in various functions, the structural organization of the claustrum remains largely unknown. It is crucial that we first understand the intrinsic neural organization of the claustrum to better elucidate its functional complexity. Thus, we sought to investigate the transcriptomic breakdown of the claustrum through single cell RNA-sequencing (scRNA-seq). In our analysis, we uncovered a previously unknown excitatory neuronal subtype, suggesting the claustrum is composed of 2 transcriptomically distinct excitatory neurons. To investigate the spatial organization of these subtypes, we used multiplexed single-molecule fluorescence in situ hybridization (smFISH), targeting RNA from 12 different marker genes in individual brain sections. We found that the gene expression patterns of the claustral neurons correlated strongly with the scRNA-seq predictions, organizing into a "core-shell" spatial configuration that was consistent across the anterior-posterior axis. To determine if these transcriptomic signatures corresponded to specific projection neuron populations within the claustrum, multicolour retrograde tracing in conjunction with smFISH was performed. Here, we found the core and shell subtypes correlated with distinct projection targets from the retrosplenial cortex and lateral entorhinal cortex, respectively. Thus, the claustrum exhibits a "core-shell" spatial organization with distinct molecular and circuit properties, which may drive its functional complexity. This spatial heterogeneity can be used in the future to examine subtype-specific function.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".