The provided code snippet from a computational neuroscience model focuses on simulating synaptic transmission dynamics at excitatory and inhibitory synapses, which are critical for neuronal communication in the brain. Here, the biological processes are modeled using computational components that mimic the behavior of synaptically activated channels. Let's break down the key biological aspects that are captured in the code: ### Biological Basis #### Excitatory Synapses - **Glutamate Receptors (AMPA Receptors):** The code specifically models the dynamics of AMPA-type glutamate receptors, which are typically found at excitatory synapses. When glutamate is released from the presynaptic neuron, it binds to AMPA receptors on the postsynaptic membrane, causing an influx of ions, primarily Na⁺, which depolarizes the postsynaptic cell. - **Reversal Potential (EGlu):** The reversal potential for glutamatergic synapses is set at 0.0 V, which represents the potential at which there is no net flow of ions through the channel. This is typical for excitatory synapses where the influx of positive ions leads to a depolarizing effect. #### Inhibitory Synapses - **GABA Receptors:** The code includes inhibitory synapses mediated by GABAA receptors, where GABA acts as the neurotransmitter. These receptors conduct Cl⁻ ions when activated, typically causing hyperpolarization of the postsynaptic membrane. - **Reversal Potential (EGABA):** The reversal potential for GABAergic synapses is set at -0.081 V. This potential reflects the hyperpolarizing (inhibitory) effect of GABAergic transmission, which is essential for reducing neuronal excitability. #### Alpha-Function Dynamics - **Synaptically-Activated Channels:** The channels use an alpha-function to mimic the time course of conductance changes upon synaptic activation. This mathematical function captures the rapid rise and slower decay of conductance that occurs after neurotransmitter release and binding, approximating the kinetics of synaptic response. #### NMDA Channel Modulation - **NMDA Receptors (not explicitly present in the make_Ex_chSPIKEAMPA function but implied):** The mention of magnesium concentration (CMg), η (eta), and γ (gamma) parameters suggest modeling of NMDA receptor dynamics elsewhere. NMDA receptors are also glutamate receptors that exhibit voltage-dependent magnesium block and slower kinetics, contributing to synaptic plasticity. #### Conductance Values - **Synaptic Conductance (GGlu and GGABA):** The parameters related to conductance (gmax) represent the maximal conductance change due to synaptic activation. The conductance values are chosen to capture realistic synaptic efficacy. ### Conclusion This code provides a foundation for simulating basic excitatory and inhibitory synaptic transmission using AMPA and GABA receptors, essential for understanding neuronal network behavior and dynamics in computational models. The focus is on capturing the time courses and effects of neurotransmitter-mediated ion flows that drive neuronal communication and processing in the brain.