Artificial Synaptic Conductances Reduce Subthreshold Oscillations and Periodic Firing in Stellate Cells of the Entorhinal Cortex
Bibliographic record
Abstract
Previous work has established that stellate cells of the medial entorhinal cortex produce prominent intrinsic subthreshold oscillations in the voltage response concentrated within the theta range (3-7 Hz). It has been speculated that these oscillations play an important role in vivo in establishing network behavior both in the entorhinal cortex and hippocampus. Consequently, it is important to investigate under what conditions theta oscillations in stellate cells can be generated and whether the spike-train power spectral density (PSD) also carries power at theta. We investigated the ability of stellate cells to generate theta oscillations in the presence of generic in vivo-like patterns of stimulation. Inputs were Poisson process-driven excitatory and inhibitory synaptic conductances or currents, introduced via dynamic clamp. We analyzed the subthreshold membrane oscillations and spike-train behavior in the presence of comparable synaptic conductance- or current-mediated membrane fluctuations. In the presence of conductance-based synapses, subthreshold oscillations are highly attenuated or entirely eliminated. Conversely, with current-based synapses stellate cells retain their ability to generate subthreshold oscillations in the theta band. These results also extend into the spiking regime, where only under current-based synapses does the PSD of the spike train show a prominent peak at theta. Furthermore, the peak in the spike-train PSD and spike clustering results from an increased probability of firing after a spike afterhyperpolarization and not directly from subthreshold oscillatory dynamics as has been previously suggested. Our results suggest that subthreshold oscillations may contribute less to in vivo response properties than has been hypothesized.
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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 | 0.000 |
| 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 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".