The provided code models the dynamics of a neural network consisting of subthalamic nucleus (STN) and globus pallidus (GP) neurons. This code simulates how these neurons interact through synaptic connections and respond to external stimulation. Here's a breakdown of the biological basis of the code: ### Neural Components and Dynamics - **Subthalamic Nucleus (STN) Neurons:** - The model includes 10 STN neurons, characterized by voltage-gated ionic currents such as sodium (\(I_{Na}\)), potassium (\(I_K\)), calcium (\(I_{Ca}\)), and afterhyperpolarization (\(I_{AHP}\)). - Various gating variables (e.g., \(m\), \(h\), \(n\), \(r\)) represent the probabilistic states of ion channel components, determining their conductance. - Calcium dynamics are important for the STN neurons as they influence the \(I_{AHP}\) and \(I_{Ca}\) currents. - **Globus Pallidus (GP) Neurons:** - The GP neurons in the model also exhibit dynamics defined by sodium, potassium, and calcium currents, among others. - These neurons influence STN neurons through inhibitory synaptic currents, contributing to the network's oscillatory behavior. ### Synaptic Interactions - **Synaptic Currents:** - Both STN and GP neurons interact via synaptic currents (\(I_{syn}\)), which are influenced by conductance parameters and membrane potential differences. - The synaptic dynamics (mediated by variables like \(s\) and \(sg\)) incorporate standard sigmoid activation functions reflecting neurotransmitter release and binding. ### Stimulation Protocol - **Stimulation Application:** - The model incorporates external stimulation currents applied to specific STN neurons (5th, 7th, and 9th), representing electrical stimulation, possibly mimicking deep brain stimulation. - The parameters \(w1\) and \(w2\) control the local or non-local spread of stimulation, altering neural activity in targeted regions and potentially affecting oscillatory patterns. ### Local Field Potentials (LFP) - **LFP Calculation:** - LFPs are computed for the 5th, 7th, and 9th STN neurons, capturing the summed electrical activity in these regions as influenced by synaptic interactions and external stimulation. - These LFPs provide insights into the network dynamics and synchronization of neural populations, key aspects often examined in experimental and computational studies of neural circuits. ### Biological Implications - **Oscillatory Behavior:** - The dynamics of STN-GP circuits are critical in understanding the generation and modulation of oscillatory activity in the brain, especially related to movement disorders like Parkinson's disease. - The interaction between excitatory STN and inhibitory GP contributes to pathological oscillations, often explored in studies using computational models to test therapeutic interventions. The biological basis of this code centers around simulating the electrical activity of interconnected neural circuits involving STN and GP neurons, with a focus on their biophysical properties and how they are modulated through external inputs. This provides insights into the underlying mechanisms of basal ganglia function and its impact on neural oscillations and synchronization.