Actualizados los modelos de Vavoulis y la sinapsis de activación gradual - #6
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Pull request overview
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This PR updates neuron and synapse templates to better reflect subtype-specific dynamics and integration constraints.
Changes:
- Implement subtype-specific
p/qgating dynamics inVavoulisModel(including N2v dependence on axonal voltageva). - Change electrical coupling conductance inputs in
eval()from state variables to parameters (g_ecs,g_eca). - Update
GradualActivationSynapsistemplate constraints to require an integrator compatible with the serializable system wrapper type.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 3 comments.
| File | Description |
|---|---|
| models/VavoulisModel.h | Adds subtype-aware incr_p/incr_q and switches electrical coupling conductance lookup to params |
| include/GradualActivationSynapsis.h | Tightens integrator concept constraint to match the wrapped/serializable system type |
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| void eval(const Precission *const vars, Precission *const params, | ||
| Precission *const incs) const { | ||
| incs[v] = (-SYNAPTIC_INPUT - il(vars[v]) - | ||
| ix((type)params[n_type], vars[v], vars[p], vars[q]) - | ||
| iec(vars[v], vars[va], vars[g_ecs]))/10; | ||
| iec(vars[v], vars[va], params[g_ecs]))/10; | ||
|
|
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| incs[va] = (-il(vars[va]) - inat(vars[va], vars[h]) - ik(vars[va], vars[n]) - | ||
| iec(vars[va], vars[v], vars[g_eca]))/10; | ||
| iec(vars[va], vars[v], params[g_eca]))/10; |
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| switch (t) { | ||
| case n1m: | ||
| // Tabla 1: p_inf = 1/(1+exp((-38.8-V_S)/10)), tau_p = 250 ms (constante) | ||
| pinf = 1 / (1 + exp((-38.8 - v) / 10.0)); | ||
| tau_p = tau_p_param; | ||
| break; | ||
| case n2v: | ||
| // Tabla 1: p_inf = 1/(1+exp((-51-V_S)/10.3)) | ||
| // tau_p = 28.3 + 44.1 * exp(-((-11.8-V_A)/26.6)^2) | ||
| pinf = 1 / (1 + exp((-51.0 - v) / 10.3)); | ||
| tau_p = 28.3 + 44.1 * exp(-pow((-11.8 - va) / 26.6, 2)); | ||
| break; | ||
| case n3t: | ||
| // Tabla 1: p_inf = 1/(1+exp((-61.6-V_S)/5.6)), tau_p = 4 ms (constante) | ||
| pinf = 1 / (1 + exp((-61.6 - v) / 5.6)); | ||
| tau_p = tau_p_param; | ||
| break; | ||
| case so: | ||
| default: | ||
| // SO es pasivo, no tiene variable p | ||
| return 0; | ||
| } |
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| requires NeuronConcept<TNode1> && NeuronConcept<TNode2> && | ||
| IntegratorConcept<TIntegrator> | ||
| // IntegratorConcept<TIntegrator> | ||
| IntegratorConcept<TIntegrator, SerializableWrapper<SystemWrapper<GradualActivationSynapsisModel<precission>>>> | ||
| class GradualActivationSynapsis |
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Actualización de la librería para poder simular los modelos de Vavoulis con n1, n2, n3 y SO