The provided code models synaptic transmission and plasticity using a combination of AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) and NMDA (N-methyl-D-aspartate) receptor dynamics, incorporating presynaptic short-term plasticity mechanisms based on the framework of Fuhrmann et al. (2002). Here’s a breakdown of the biological aspects being modeled: ### 1. **AMPA and NMDA Receptors:** - **AMPA Receptors**: These are ionotropic glutamate receptors that mediate fast synaptic transmission in the central nervous system. Their activation is modeled using a dual-exponential conductance profile, represented by state variables (A_AMPA and B_AMPA), which account for the characteristic rise and decay time constants (`tau_r_AMPA` and `tau_d_AMPA`). - **NMDA Receptors**: These receptors are also ionotropic glutamate receptors but are distinct in their voltage-dependent and slower kinetics property. The model implements them with a similar dual-exponential conductance profile (using `A_NMDA` and `B_NMDA` state variables), along with a magnesium block mechanism dependent on membrane potential (`mggate`). This voltage-dependent block is reduced by depolarization, making NMDA receptors key players in synaptic plasticity. ### 2. **Short-Term Synaptic Plasticity:** - **Facilitation and Depression**: The model includes mechanisms for synaptic facilitation and depression. These forms of short-term plasticity adjust synaptic strength over the timescale of milliseconds to seconds. - **Facilitation (`Fac`)**: Models presynaptic increase in transmitter release probability with successive stimuli. It is represented by the facilitation time constant. - **Depression (`Dep`)**: Accounts for a reduction in synaptic strength due to the depletion of readily available neurotransmitter vesicles after repeated stimulation. ### 3. **Synaptic Probability and Usage Variables:** - **Utilization of Synaptic Efficacy (`Use`)**: Represents the probability of neurotransmitter release per action potential at an initial state. - **Probability of Vesicle Release (`Pv`)**: Represents the potential for a vesicle to be released, decreasing with consecutive stimulations without replenishment. ### 4. **Randomization of Synaptic Activation:** - The inclusion of randomization functions and vectors reflects the biological variability and stochastic nature of synaptic transmission, capturing the probabilistic aspect of neurotransmitter release. ### 5. **Simulation Details:** - The dynamics of synaptic conductance are determined by changes in postsynaptic potential, which influence synaptic transmission efficacy and hence are key to understanding synaptic integration and network function. - Parameters such as reversal potential (`e`) represent the equilibrium potential for ions passing through these receptors, a critical factor in biophysical modeling of synapses. The code effectively captures the complex interplay between neurotransmitter receptors and short-term synaptic dynamics, essential for simulating neural circuits' computational and memory functions in the brain.