A synaptic input portal for a mapped clock oscillator model of neuronal electrical rhythmic activity
Bibliographic record
Abstract
Neuronal electrical oscillations play a central role in a variety of situations, such as epilepsy and learning. The mapped clock oscillator (MCO) model is a general model of transmembrane voltage oscillations in excitable cells. In order to be able to investigate the behaviour of neuronal oscillator populations, we present a neuronal version of the model. The neuronal MCO includes an extra input portal, the synaptic portal, which can reflect the biological relationships in a chemical synapse between the frequency of the presynaptic action potentials and the postsynaptic resting level, which in turn affects the frequency of the postsynaptic potentials. We propose that the synaptic input-output relationship must include a power function in order to be able to reproduce physiological behaviour such as resting level saturation. One linear and two power functions (Butterworth and sigmoidal) are investigated, using the case of an inhibitory synapse. The linear relation was not able to produce physiologically plausible behaviour, whereas both the power function examples were appropriate. The resulting neuronal MCO model can be tailored to a variety of neuronal cell types, and can be used to investigate complex population behaviour, such as the influence of network topology and stochastic resonance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.005 | 0.001 |
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".