The provided code aims to model the dynamics of presynaptic short-term plasticity by focusing on two key physiological processes: presynaptic short-term facilitation and presynaptic short-term depression. These processes are crucial for understanding how neurons communicate over short timescales and how synaptic strength is modulated in response to neural activity. ### Biological Basis #### Presynaptic Short-Term Facilitation Short-term facilitation is a temporary increase in synaptic strength that occurs due to an accumulation of calcium ions ([Ca²⁺]) in the presynaptic terminal following repeated stimulation. The code references this concept through the calculation and plotting of steady-state calcium concentration (`Ca_i`) in the presynaptic neuron. The increased [Ca²⁺] enhances neurotransmitter release by affecting the probability of vesicle release, thereby increasing synaptic efficacy during brief periods of high-frequency stimulation. #### Presynaptic Short-Term Depression In contrast, short-term depression is characterized by a decrease in synaptic strength due to the depletion of readily releasable vesicle pools. The code models this by computing the ratio of releasable vesicles (`R_rel`). During repetitive stimulation, the releasable pool of vesicles is used up faster than it can be replenished, leading to decreased neurotransmitter release and thus a reduction in synaptic strength. ### Key Components in the Code 1. **Calcium Dynamics**: The code calculates and visualizes the transient response of calcium concentration (`Ca_i`) in the presynaptic terminal. This is critical for simulating how intracellular calcium dynamics contribute to short-term facilitation. 2. **Vesicle Dynamics**: The ratio of releasable vesicles (`R_rel`) is another focal point, reflecting the dynamics of vesicle availability during neurotransmission. This links directly to short-term depression as it demonstrates how vesicle pool depletion affects the synapse's ability to sustain neurotransmitter release. 3. **Steady-State and Transient Responses**: The simulation uses steady-state values of calcium concentration and vesicle availability to model how presynapses respond to impulses and average conditions over time. These simulations are crucial for understanding the temporal dynamics of synaptic transmission based on biophysical principles. ### Conclusion The code provided is intrinsic to understanding how short-term plasticity affects presynaptic terminal responses during neural communication. By focusing on calcium dynamics and vesicle availability, it models how facilitating and depressing mechanisms shape synaptic transmission and, consequently, neural circuit function over short timescales. This type of modeling provides insights into the complex interplay of factors driving synaptic efficacy, contributing to the broader understanding of neural coding and information processing in the brain.