The provided code is a GENESIS (neuronal simulator software) script designed to model synaptic transmission within a neural network framework. The code describes several types of synaptic channels, focusing on excitatory glutamatergic synapses (AMPA and NMDA) and inhibitory GABAergic synapses (GABAA). Each of these synapses represents a crucial component of synaptic communication in the brain.

Biological Basis

Excitatory Synapses:

1. Glutamatergic Synapses:

   • AMPA Receptors:

     • The AMPA receptor is an ionotropic receptor for glutamate, the primary excitatory neurotransmitter in the brain. AMPA receptors mediate fast synaptic transmission.
     • In the code, AMPA receptors are modeled with rapid activation and deactivation times (tau1 and tau2), suggesting a quick synaptic response.
     • The script sets the reversal potential, Ek, for AMPA to 0.0 V, reflecting the typical glutamatergic excitatory nature and aiming to depolarize the postsynaptic neuron.

   • NMDA Receptors:

     • NMDA receptors are another type of ionotropic glutamate receptor that are crucial for synaptic plasticity and learning mechanisms. They have slower kinetics compared to AMPA receptors and are permeable to Ca2+ ions.
     • The conductance of NMDA receptors is modulated by extracellular magnesium ([Mg2+]), leading to a voltage-dependent block that is lifted during depolarization. This characteristic is reflected in the parameters CMg, eta, and gamma in the code.
     • NMDA's reversal potential is also set to 0.0 V, common for excitatory synapses, promoting depolarizing effects that facilitate Ca2+ entry.

Inhibitory Synapses:

2. GABAergic Synapses (GABAA Receptors):
   • GABAA receptors are ionotropic receptors for gamma-aminobutyric acid (GABA), the primary inhibitory neurotransmitter. These receptors mediate fast inhibitory transmission by allowing Cl- ions to flow into the neuron, leading to hyperpolarization.
   • The script assigns a reversal potential for GABAA receptors at -0.075 V, corresponding to the typically inhibitory nature, which moves the membrane potential away from the action potential threshold.

Synaptic Properties:

• Conductance Changes:
  • Each synapse type is modeled using an alpha function to simulate conductance changes during synaptic events. This function mimics the time course of neurotransmitter binding and resulting ion flow through receptor channels.
  • Parameters tau1 and tau2 represent the rise and decay time constants for the synaptic currents. These values indicate how quickly a synapse activates and deactivates in response to neurotransmitter release.

Conclusion:

The model simulates synaptic channels based on biologically relevant parameters to replicate the dynamic behavior of neuronal communication via AMPA, NMDA, and GABAA receptors. This implementation allows researchers to study synaptic integration and the effects of synaptic inputs on neuronal excitability and network behavior, highlighting key biological processes such as excitatory/inhibitory balance and synaptic plasticity.