The provided code models neurotransmitter (NT) diffusion within the synaptic cleft, focusing on the dynamics of neurotransmitter concentration and its distribution over time. Here is the biological basis of the code: ### Synaptic Cleft and Neurotransmitter Diffusion 1. **Synaptic Cleft**: The synaptic cleft is the narrow space between the presynaptic and postsynaptic neurons. Neurotransmitters are released into this space in response to an action potential arriving at the axon terminal of the presynaptic neuron. 2. **Neurotransmitter Dynamics**: This model deals with the diffusion of neurotransmitters, likely glutamate, across the synaptic cleft, which is critical for synaptic transmission. The release, diffusion, and resulting concentration of neurotransmitters in the synaptic cleft influence the postsynaptic neuron's response. 3. **Diffusivity and Cleft Width**: Parameters such as `Diffusivity` and `CleftWidth` reflect the biophysical properties of neurotransmitter movement in the cleft, akin to the diffusivity coefficient of molecules and the actual physical gap between neurons, respectively. 4. **Radius and Receptor Interaction**: The `Radius` variable represents the distance or position of receptors on the postsynaptic neuron from the release site. This reflects how neurotransmitter concentration diminishes with distance from the release point. 5. **Concentration Dynamics**: `NTConcentration` represents the neurotransmitter concentration within the synaptic cleft. It changes over time based on diffusion dynamics and neurotransmitter uptake or degradation processes. 6. **Analytic Solution to Diffusion**: The code employs an analytical approach (as per the reference to Savtchenko et al., 2007) for solving the diffusion problem, providing an optimized framework for understanding neurotransmitter movement through the synaptic cleft. ### Synaptic Transmission Events 1. **Event Handling**: Neurotransmitter events are modeled by `NET_RECEIVE` mechanisms, capturing the arrival of action potentials and subsequent neurotransmitter release. This is represented in the `tr` array capturing release times, and `NTi` (intracellular neurotransmitter). 2. **Neurotransmitter Usage**: `Nused` tracks the number of active neurotransmitter events. It ensures the model accommodates multiple releases and their cumulative effects on receptor activation. 3. **Temporal Dynamics**: `tDiff` and other temporal variables track how neurotransmitter concentration changes over time relative to the timing of release events. This is important for mimicking the transient nature of synaptic transmissions. ### Implications and Applications - **Synaptic Efficacy**: The model reflects on synaptic efficacy influenced by neurotransmitter availability and timely delivery to receptors, which are critical for synaptic plasticity and neural communication. - **Pathways**: This framework might be especially relevant to glutamatergic synapses, where precise neurotransmitter dynamics dictate processes such as long-term potentiation (LTP) or depression (LTD), fundamental to learning and memory. Overall, the code provides a sophisticated attempt to model neurotransmitter diffusion, capturing essential biophysical and temporal processes that underlie synaptic transmission in the brain.