The MATLAB code provided simulates certain aspects of the membrane potential response of neural tissue to extracellular electrical stimulation. ### Biological Basis 1. **Membrane Potential:** The code models membrane potential (denoted as \( V_M \)) changes due to external electrical stimulation. Membrane potential is the voltage difference across the neuron's cell membrane, essential for the conduction of nerve impulses. 2. **Neurite Geometry:** The code uses parameters \(a\) and \(b\), representing the inner (axonal) and outer radii of a cylindrical neuritic process (axon or dendrite). This represents the geometry of neural fibers, a critical aspect of understanding how geometry affects electrical properties and signal conduction. 3. **Electrical Properties:** - **Resistivities (\( \rho_e \) and \( \rho_i \)):** These parameters represent the extracellular and intracellular resistivities, respectively. They determine how easily the electric fields can penetrate the extracellular space and the inside of the neuron. - **Membrane Resistance (\( R_M \)):** This represents the resistance per unit length posed by the membrane, which is crucial for determining how currents flow across the membrane. 4. **Longitudinal and Transverse Length Constants (LTJ, LTV):** - These constants are derived from the resistances and provide measures of how far electrical signals can travel longitudinally along the neurite (LTJ) and across the membrane (LTV) before attenuating. 5. **Gaussian Sources and Potentials:** - The Gaussian distribution used (with a standard deviation \(\Sigma\)) models how electrical signals decay over space, influenced by the neuron's membrane and surrounding medium. The Gaussian is employed to approximate how potential changes propagate, affecting \( V_M \). 6. **Stimulation Influence (Figures 11, 12, 13):** - The figures generated by the code aim to provide theoretical insights into membrane potential changes under different scenarios. The effect of the external voltage boundary conditions on the membrane potential, as influenced by neurite radius (\(b/a\)) and coupling strength (\(d/\Sigma\)), is analyzed. ### Key Aspects Highlighted in the Code - **Plotting of Membrane Potential Profiles:** The simulation outcome details how membrane potential varies with distance along the neurite under different conditions, allowing the evaluation of how effective external stimulation might be in modulating neural activity. - **Legend and Axes Labels:** These clearly specify the modes and scenarios being tested, such as the analytic nature of the results and the conditions applied, facilitating understanding of the stimulatory effects in the context of biophysical neural modeling. In summary, this code focuses on the computational modeling of how external electrical fields influence neural fibers characterized by specific geometrical and electrical properties. The models aim to simulate membrane potentials under varying conditions that are important for applications such as neural stimulation in prosthetics or medical devices.