# Biological Basis of the Computational Model This code models a simple multicompartmental spiking neuron using the **iaf_cond_alpha_mc model** in the NEST simulator. The model simulates the dynamic behavior of a neuron with compartments that represent distinct regions of a neuron's structure: the soma (cell body), the proximal dendrite, and the distal dendrite. Here are the key biological concepts being modeled: ## Neuronal Compartmentalization - **Soma (Cell Body):** The central part of the neuron containing the cell nucleus and is the site where inputs to the neuron are integrated to decide whether to propagate an action potential. - **Proximal and Distal Dendrites:** These are the input regions of the neuron that receive synaptic signals. Dendrites closer to the soma (proximal) and those further away (distal) can have different electrical properties and influences on the soma. This is represented in the code with different parameters for each compartment. ## Synaptic Inputs The model incorporates synaptic inputs in two forms: - **Excitatory and Inhibitory Synaptic Conductances:** The model includes stimulation paradigms with synaptic inputs affecting excitatory (`g_ex`) and inhibitory (`g_in`) conductances. These conductances are key to how neurons process and respond to synaptic inputs, influencing the membrane potential. - **Spike Generators:** Biological neurons receive inputs in the form of spikes from presynaptic neurons, which this model emulates using spike generators to deliver timed trains of spikes to each compartment. ## Electrical Properties - **Membrane Potential:** The model simulates the membrane potential dynamics (`V_m`) of each compartment. This is crucial for determining whether the neuron will fire an action potential. - **Synaptic and Leaky Conductances:** The model includes conductances like `g_sp` (somato-proximal coupling conductance) and `g_L` (leak conductance), reflecting the passive properties of the neuron's membrane that influence how subthreshold inputs spread within the neuron. - **Capacitance and Time Constants:** Parameters like `C_m` (capacitance) and `tau_syn` (synaptic time constants) define how quickly the membrane potential responds to inputs, reflecting biological properties of neuronal membranes and synapses. ## Stimulation Paradigms - **Current Injections:** The use of direct current inputs in the soma, proximal, and distal compartments simulates external stimulation experiments where current is injected into neurons to study their response. - **Rheobase Current:** The "rheobase" refers to the minimum current required to elicit an action potential in excitable tissues. Injecting a constant current to cause soma firing mirrors such electrophysiological investigations. ## Receptor Types - **Receptor Specification:** The code lists receptor types (`soma_curr`, `proximal_curr`, `distal_curr`, etc.), aligning with biological receptors found at various locations on neuron membranes that mediate different types of synaptic input. Overall, this model captures key aspects of cellular neuroscience, aiming to represent how different dendritic compartments integrate synaptic and external stimuli to produce neuronal output, a fundamental question in understanding how information is processed in the brain.