The code provided is designed to simulate a specific aspect of neuronal behavior—the relative refractory period of a neuron—using a computational model. The model represents this phase as a passive, high-conductance process following the occurrence of an action potential. ### Biological Basis 1. **Refractory Periods in Neurons**: - After a neuron fires an action potential, it undergoes a refractory period during which it is less likely or unable to fire another action potential. This period consists of two phases: the absolute refractory period and the relative refractory period. - The **absolute refractory period** is when a neuron cannot fire another action potential regardless of the stimulus strength, primarily due to the inactivation of voltage-gated sodium channels. - The **relative refractory period** follows the absolute phase, during which a neuron requires a stronger-than-normal stimulus to elicit another action potential. This is mainly because of the continued outflow of potassium ions and the resettling of sodium channel inactivation. 2. **Modeling the Relative Refractory Period**: - In the provided code, the relative refractory period is primarily modeled through an increase in membrane conductance (`g`), which reflects the biological concept of increased potassium channel activity during this phase. Potassium channels typically facilitate the return to resting membrane potential by allowing potassium ions to leave the cell, thus hyperpolarizing it. - The parameter `gr` represents the maximal conductance associated with this refractory state, signifying how the neuron's membrane becomes more "leaky" or conductive. - The reversal potential `e` is set to -65 mV, approximating the resting membrane potential or the equilibrium potential for potassium ions under physiological conditions. 3. **Decay of Conductance**: - The model uses an exponential decay (represented by `tau`) to simulate how the increased conductance slowly reduces back to its baseline. This reflects the biological process where potassium conductance gradually returns to its normal level, allowing the neuron to eventually regain its full excitability. 4. **Integration with Neuronal Activity**: - The model employs an external event to trigger the onset of the refractory period (`g = g + gr`), mirroring how an action potential sets off a cascade that temporarily alters membrane properties. Overall, this computational model captures the essential characteristics of the relative refractory period seen in neurons by adjusting membrane conductance post-action potential to reflect biological processes like increased ion permeability, particularly related to potassium efflux, and its gradual return to baseline conductance levels.