The provided code models synaptic transmission involving AMPA and NMDA receptors with an emphasis on capturing the dynamics of presynaptic short-term plasticity. This code represents a computational model aimed at simulating the behavior of excitatory synapses in the central nervous system, specifically focusing on how these synapses manage to exhibit various forms of plasticity and conductance dynamics. ### Biological Basis #### 1. **AMPA and NMDA Receptors** - **AMPA Receptor**: Represented in this model with rapid activation and deactivation kinetics captured by dual-exponential conductance. The variables `A_AMPA` and `B_AMPA` represent state variables that map onto the rise and decay phases of the receptor's conductance after synaptic glutamate binding. - **NMDA Receptor**: Known for slower activation and deactivation compared to AMPA receptors. This conductance is also modeled with a dual-exponential function through state variables `A_NMDA` and `B_NMDA`. A unique aspect of NMDA receptor operation is its voltage-dependent magnesium block, modeled here by the `mggate` variable. This block is relieved upon sufficient postsynaptic depolarization. #### 2. **Synaptic Plasticity** - The model incorporates presynaptic short-term plasticity mechanisms described in Fuhrmann et al., 2002. It simulates facilitation and depression dynamics, which are crucial for temporal modulation of synaptic strength. - **Facilitation**: Modeled by the parameter `Fac`. It reflects the increased probability of neurotransmitter release with closely spaced synaptic activity, controlled by calcium-dependent potentiation mechanisms at the presynaptic terminal. - **Depression**: Represented by the parameter `Dep`. Synaptic depression reduces neurotransmitter release probability, often due to vesicle depletion following high-frequency activation. #### 3. **Utilization of Synaptic Efficacy** - The parameter `Use` represents the initial probability of synaptic vesicle release, a component of presynaptic plasticity reflecting the baseline efficacy of synaptic transmission under resting conditions. #### 4. **Conductance and Current Dynamics** - **Conductance**: The conductance for both AMPA and NMDA receptors is computed as the difference between two state variables (`B_A - A_A`), which derive from the solution of a set of differential equations describing the exponential rise and decay of synaptic conductance. - **Current**: The synaptic current for each receptor type (AMPA and NMDA) is calculated as the product of conductance, the membrane potential (`v`), and the difference between the membrane potential and the reversal potential (`e`). For NMDA receptors, an additional voltage and magnesium dependency is accounted for by `mggate`. This model leverages these biological mechanisms to replicate the temporal dynamics of synaptic responses and how they adapt based on presynaptic activity, which is crucial for understanding synaptic computation in neural circuits. Through this approach, the model can help dissect the contributions of post-synaptic receptor kinetics and presynaptic plasticity to the integrative properties of neurons.