Somatodendritic HCN channels in hippocampal OLM cells revealed by a convergence of computational models and experiments
Bibliographic record
Abstract
Abstract Determining details of spatially extended neurons is a challenge that needs to be overcome. The oriens-lacunosum/moleculare (OLM) interneuron has been implicated as a critical controller of hippocampal memory making it essential to understand how its biophysical properties contribute to function. We previously used computational models to show that OLM cells exhibit theta spiking resonance frequencies that depend on their dendrites having hyperpolarization-activated cation channels (h-channels). However, whether OLM cells have dendritic h-channels is unknown. We performed a set of whole-cell recordings of OLM cells from mouse hippocampus and constructed multi-compartment models using morphological and electrophysiological parameters extracted from the same cell. The models matched experiments only when dendritic h-channels were present. Immunohistochemical localization of the HCN2 subunit confirmed dendritic expression. These models can be used to obtain insight into hippocampal function. Our work shows that a tight integration of model and experiment tackles the challenge of characterizing spatially extended neurons.
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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 | 0.001 | 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".