The code is modeling a synaptic current in the context of a neuron that incorporates both AMPA and NMDA receptor-mediated components, providing a simplified representation of synaptic transmission.
In the nervous system, synaptic transmission is the process by which neurons communicate with each other. When an action potential reaches the presynaptic terminal, it leads to the release of neurotransmitters into the synaptic cleft. These neurotransmitters then bind to receptors on the postsynaptic neuron, inducing a synaptic current.
This model specifically represents two types of glutamate receptors: AMPA and NMDA receptors, which are critical for excitatory synaptic transmission in the central nervous system.
AMPA Receptors: These are ionotropic receptors that mediate fast synaptic transmission. When glutamate binds to AMPA receptors, it results in an immediate influx of cations like Na⁺, producing a rapid and transient excitatory postsynaptic current (EPSC). This is represented by gA in the code, which models the conductance due to the fast AMPA component.
NMDA Receptors: In contrast, NMDA receptors are mainly known for their voltage-dependent, slower kinetics. They require both glutamate binding and postsynaptic depolarization to relieve the Mg²⁺ block from their pore, allowing the flow of ions, primarily Ca²⁺ and Na⁺. This property of NMDA receptors is crucial for synaptic plasticity mechanisms, such as Long-Term Potentiation (LTP). The conductance associated with NMDA receptors is modeled by gN, incorporating an Mg²⁺ block, which is dependent on membrane potential (v) and the concentration of Mg²⁺ (Mg).
The dual exponential function used here characterizes the time course of synaptic conductance changes. It accounts for both the rise (tau1 or Ntau1) and decay (tau2 or Ntau2) phases of the synaptic conductance, reflecting the dynamics of synaptic events. The exponential terms (tau1, tau2 for AMPA; Ntau1, Ntau2 for NMDA) simulate the temporal evolution of the conductance based on receptor kinetics.
Agmax) and NMDA (Ngmax) components determine the strength of the synaptic response.e): Sets the directionality of synaptic current flow based on the difference between the membrane potential (v) and the reversal potential.Mg) and the membrane voltage, illustrating its unique voltage-dependent properties.Overall, the model captures the essence of synaptic integration of excitatory signals through these receptor subtypes, demonstrating the dual nature of fast and slow excitatory postsynaptic potentials critical for neural computation and plasticity.