The provided code is part of a computational model that simulates the electrical properties of neurons using Hodgkin-Huxley (HH) type ion channels. This model is used to understand how neurons generate and propagate electrical signals, specifically action potentials, through their membranes. Below are the key biological aspects that the code is intended to model:
Neuronal Membrane and Channels: The code models a neuronal compartment (soma) with ion channels embedded in it. Each channel type—most commonly sodium (Na) and potassium (K) channels—is crucial for the generation and propagation of action potentials.
Gating Variables:
x/m) and inactivation (y/h) variables correspond to how open a channel is, which determines the flow of ions across the membrane.α) and beta (β) rate variables are used to calculate the dynamics of these gating variables and follow well-established forms: Exponential, Sigmoid, and Linoid.Channel Kinetics:
alpha and beta) between open and closed states of the ion channels. These transition rates are dependent on membrane voltage and described using mathematical functions characterized by different forms (EXPONENTIAL, SIGMOID, LINOID).Membrane Capacitance (Cm): Represented in the model as CM, this describes the membrane's ability to store charge.
Axial Resistance (Ra): This represents the internal resistance of the neuron's axoplasm to the flow of electrical current.
Membrane Resistance (Rm): Represents the leakiness of the membrane due to ion channels that are permanently open.
Resting Membrane Potential (EREST_ACT): Set to -0.070 volts, this reflects the typical resting membrane potential of a neuron under physiological conditions.
g of the channels is calculated as a function of the gating variables and expressed using the formula Gbar*x^Xpower * y^Ypower. For instance, in a sodium channel, the relationship m^3h reflects the kinetics of sodium activation and inactivation.Libraries and Compartments: The code sets up a library component to include these model elements without actively simulating them, enabling the broader simulation to pull and use these specifications as needed.
Lookup Tables: Functions such as setup_table2 and setup_table3 create tables for efficient computation of gating variable dynamics over a range of membrane potentials.
Overall, the code is a classical representation of ion channel dynamics crucial for neuronal electrical activity, mimicking the pioneering Hodgkin-Huxley equations and their extensions for modeling various channel types' biophysics.