The code provided represents a simulation of a neuron, specifically focusing on the incorporation of both passive and active electrical properties. This approach is typical in computational neuroscience models that aim to replicate and understand the functionality of neurons and neuronal circuits.
The passive properties of neurons include the electrical characteristics that do not depend on voltage-gated ion channels. These properties define how the neuron conducts electrical signals when it is not actively firing action potentials.
Cm): Represents the ability of the cell membrane to store charge. Biological membranes act as capacitors.Rm): Determines how easily ions can passively flow across the membrane, affecting the rate at which electrical signals decay as they move through the neuron.Ri): The resistance to current flow along the interior of the dendrites and axons, affecting signal propagation along the neuron.v_init): The resting membrane potential, which is a typical resting state voltage of a neuron (~ -75 mV).Active properties relate to the presence and functioning of ion channels that are selectively permeable to different ions and are typically gated by voltage or ligand binding. These channels facilitate the complex dynamics of action potentials.
Ek, Ena, Eca): These values represent the equilibrium potentials for potassium, sodium, and calcium ions, respectively.na) Channels: These channels are crucial for the initiation and propagation of action potentials. They are more concentrated in the axon to promote signal transmission along the axon to downstream neurons.kv, km, kca): These channels are involved in repolarizing the neuron following an action potential and setting the resting membrane potential.ca, it): Active in various aspects of neuronal signaling, including neurotransmitter release and secondary messenger pathways.hd): Represents the h channel, often contributing to the sag potential during hyperpolarizations, playing a role in rhythmic activity and excitability in some neurons.nonunif_rm) suggests an emphasis on compartmentalizing electrical properties across dendrites.The model is designed to replicate the behavior of a neuron's electrical activity by combining passive membrane characteristics with active ion channel properties. These characteristics are essential for simulating how neurons process and transmit information. The detailed parameterization of channel conductances and equilibrium potentials helps reflect the complexity of ionic dynamics in biological neurons.