The code provided represents a computational model in the NEURON simulation environment, focusing on the synaptic dynamics of glutamatergic synapses, specifically those involving AMPA and NMDA receptor types. Here's a summary of the biological basis of this model: ### **Biological Basis of the Model** #### **1. Glutamatergic Synapses** - This model simulates the release and effects of the neurotransmitter glutamate at a synapse, which activates both AMPA and NMDA receptors on the postsynaptic membrane. Such synapses are primarily excitatory in the central nervous system and are crucial for synaptic plasticity, learning, and memory. #### **2. Receptor Dynamics** - **AMPA Receptors**: These receptors are ionotropic and mediate fast synaptic transmission. The `gAMPAsingle` parameter represents the conductance of a single AMPA receptor, while `tauAMPA` denotes its deactivation time constant. The model includes mechanisms for AMPA receptor activation and subsequent ion flow, creating transient postsynaptic potentials. - **NMDA Receptors**: NMDA receptors are also ionotropic but have slower kinetics compared to AMPA receptors. They have a unique voltage-dependent behavior requiring co-activation by glutamate and removal of a magnesium block at depolarized potentials. Parameters such as `tau1NMDA` and `tau2NMDA` define their complex activation and deactivation kinetics. The model calculates NMDA receptor conductance (`gNMDA`) with voltage dependence reflected in `n` and `gama`, accounting for calcium permeability and other voltage-sensitive properties. #### **3. Synaptic Vesicle Dynamics** - The model simulates vesicle release within the presynaptic terminal. Parameters like `maxves` (total vesicles) and `newves` (vesicle replenishment rate) reflect the dynamics of synaptic vesicle availability and recycling critical for sustained neurotransmitter release under different stimuli. - **Release Probability**: A function (`releasefunc`) controls the stochastic release of vesicles. This function can release neurotransmitters in response to presynaptic voltage (`Vpre`), akin to the biological action potential triggering neurotransmitter release. #### **4. Voltage Dynamics** - **Presynaptic Voltage**: The depolarization characteristics of the presynaptic compartment are modeled using parameters like `Vamp`, `Vdel`, and `Vdur`, simulating a scenario where electrical signals provoke neurotransmitter release over specific time frames. - **Voltage Dependence**: `Voff`, `Vset`, and the computation of `local_v` capture instances of voltage independence (e.g., clamping techniques in experimental setups) and influence receptor activation, particularly for NMDA receptors which are sensitive to local membrane potential dynamics due to their voltage-dependent gating. #### **5. Calcium Contribution** - Though commented out, the model includes consideration of calcium (`icaconst`) tied to NMDA activity, acknowledging the role of calcium in synaptic plasticity and as a secondary messenger in various cellular processes. In summary, the code models a neuromorphic approximation of a glutamatergic synapse, emphasizing the kinetics and interplay between AMPA and NMDA receptor-mediated conductance changes based on presynaptic stimulation voltages and vesicular dynamics. This model captures essential features that influence synaptic strength and plasticity, mirroring biological processes involved in excitatory neurotransmission.