# Biological Basis of the Model The code provided models synaptic transmission incorporating both AMPA and NMDA receptors with presynaptic short-term plasticity. Here is the biological context for each element in the model: ## **AMPA and NMDA Receptors** - **AMPA Receptors**: - These are fast-acting ionotropic glutamate receptors that mediate most of the fast excitatory synaptic transmission in the central nervous system. They allow the flow of Na⁺ and K⁺ ions, contributing to depolarization of the postsynaptic neuron. - In the code, AMPA receptor dynamics are modeled using a dual-exponential decay, characterized by two time constants, `tau_r` (rise time constant) and `tau_d` (decay time constant), to mimic the rapid onset and offset of AMPA receptor-mediated currents. - **NMDA Receptors**: - These are slower ionotropic receptors that allow the flow of Na⁺, K⁺, and importantly, Ca²⁺ ions. NMDA receptors are voltage-dependent and require both ligand binding (glutamate) and membrane depolarization to relieve Mg²⁺ block. - Although the NMDA receptor conductance dynamics are not explicitly modeled individually, the code assumes similar dynamics to AMPA receptors, incorporating NMDA receptor contribution through a shared `gmax` parameter. ## **Presynaptic Short-Term Plasticity** - **Utilization of Synaptic Efficacy (`Use`)**: - This parameter indicates the probability of neurotransmitter release upon an action potential arrival. It reflects the idea of how ready the synaptic vesicles are for releasing their neurotransmitter content. - **Depression and Facilitation**: - **Depression** (`Dep`): It represents the reduction in synaptic strength due to the depletion of readily releasable vesicles after repeated activations. It's modeled with a decay constant, indicating how quickly neurotransmitter resources recover. - **Facilitation** (`Fac`): It represents an increase in synaptic efficacy due to the residual Ca²⁺ levels from previous stimuli, modeled by a parameter that affects the probability of release, considering the time elapsed since last synaptic activity. ## **Synaptic Grouping** - **Multiple Synapses (`Nsyns`)**: - The `Nsyns` parameter represents a group of synapses that are modeled as a single unit in this probabilistic framework. This mimics the biological scenario where multiple synapses may act as a group in terms of combined efficacy on the postsynaptic neuron. - **Random Selection of Activation**: - Synapse activation involves a stochastic process using a random number generator to determine if neurotransmitter release occurs, which represents the probabilistic nature of vesicle release at synapses. ## **Conductance and Current Dynamics** - **Dual-exponential Profile**: - The model uses a dual-exponential profile to simulate the postsynaptic conductances that follow a neurotransmitter release. This reflects the biological observation that synaptic currents exhibit a rapid onset followed by a slower decay. - **Driving Force Calculation**: - The code calculates synaptic currents using the conductance and the difference between the membrane potential and the reversal potential (`e`), reflecting the biophysical mechanism of ion flow driven by electrochemical gradients. In summary, the model captures key aspects of synaptic transmission by integrating receptor kinetics of AMPA and NMDA receptors and presynaptic short-term plasticity mechanisms. These elements together aim to represent the dynamic and probabilistic nature of synaptic integration observed in biological neural circuits.