An investigation into an anomalous pyramidal cell type: atypical morphology and sustained cellular activity to novel stimuli
Bibliographic record
Abstract
Introduction: This research investigates an anomalous pyramidal cell type, dubbed "deep cells" in the subiculum of the hippocampus. Deep cells are structurally unique in that they completely lack radial oblique dendrites. This work will use in-vivo calcium imaging to elucidate how this remarkable change in structure effects neuronal function in vivo in the subiculum and its possible role during behaviour. Methods: Our lab has constructed a transgenic cre line to access this deep cell type. I use this mouse line to image deep cells during spatial navigation and novel object tasks. During these experiments, I use wire-free 1-photon miniscopes to image the dorsal subiculum while mice undergo an open field task with two local objects, repeated over several timepoints. Results: Data from this project show that deep cells act on very slow timescales and have robust, sustained activity that appear to respond to encounters with novel, local objects . Deep cells show large increases in activity after interaction with a novel object on day one and this activity is substantially reduced by day four. Intriguingly, this cellular signature is still reduced 100 days after initial introduction. In comparison to control cells, deep cells show novel object-centered activity and no classic spatial phenotypes expected from pyramidal cells in the subiculum. Conclusion: This data leaves us with intriguing evidence of a seemingly spatially uninvolved, novelty driven and morphologically distinct cell type previously undescribed in the subiculum. Future work will be integral to identifying the role of this cell in memory processes/dysfunction and the role of this novel cell type in other brain regions.
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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 | 0.000 |
| 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".