The code provided models synaptic transmission dynamics in a computational neuroscience framework, focusing on two key components: AMPA and NMDA receptors with presynaptic short-term plasticity. ### AMPA and NMDA Receptors - **AMPA Receptors**: The model simulates the synaptic conductance through AMPA receptors, which are crucial for fast excitatory synaptic transmission in the central nervous system. AMPA receptors are glutamate-gated ion channels that allow Na+ and K+ ions to pass, contributing to the post-synaptic depolarization necessary for synaptic signaling. The dual-exponential conductance profile in the code reflects the rise and decay kinetics of AMPA receptor-mediated currents, characterized by the `tau_r` and `tau_d` parameters. - **NMDA Receptors**: Although not explicitly detailed in the code snippet, NMDA receptors are also glutamate-gated but involve a more complex ion channel permeable to Na+, K+, and Ca2+ ions. NMDA receptors are voltage-dependent due to their Mg2+ block, which is removed upon sufficient depolarization. The shared reversal potential (`e`) and the indication in the comment that the weights are equal for both NMDA and AMPA suggest the model jointly considers their contributions to synaptic transmission. NMDA receptors play a crucial role in synaptic plasticity, contributing to both short-term and long-term changes in synaptic strength. ### Presynaptic Short-Term Plasticity - **Short-Term Plasticity**: The code implements forms of presynaptic plasticity, specifically facilitation and depression, as described by Fuhrmann et al. 2002. These mechanisms reflect dynamic changes in neurotransmitter release probability and synaptic efficacy over short timescales (milliseconds to seconds). - **Facilitation (Fac)**: This is characterized by a transient increase in synaptic strength following synaptic activity. In the model, facilitation is governed by a time constant (`Fac`), affecting the neurotransmitter release probability (`u`), which builds up when successive action potentials occur in quick succession. - **Depression (Dep)**: This represents a temporary reduction in synaptic strength following high-frequency activity, often due to vesicle depletion or receptor desensitization. The code captures this through a time constant (`Dep`), affecting the availability of synaptic resources (`Pv`). ### Randomness in Synaptic Transmission - **Stochastic Nature**: Biological synapses demonstrate inherent variability in neurotransmitter release. The randomness in the synapse activation process is modeled using random number generation (`erand()`), simulating the probabilistic nature of synaptic transmission, e.g., whether synaptic vesicles release their neurotransmitter content. In summary, this code portrays a biologically detailed model of synaptic transmission focusing on AMPA and NMDA receptor function with modifiers of presynaptic short-term plasticity, capturing essential dynamics inherent to neuronal communication in the brain.