The provided code is a computational model designed to simulate the interactions between extracellular electrodes and neurons through the principle of electrical reciprocity. This approach is useful in computational neuroscience for understanding how neurons respond to electrical stimulation from electrodes and predict the potential generated in and around neurons.
The model focuses on calculating the transfer resistances between extracellular electrodes and neurons. These interactions are critical for both stimulating neurons and recording their activities. The principle of reciprocity, used in the model, is based on the assumption that the extracellular space (composed of tissue and bathing solution) behaves linearly. It implies that the transfer resistance determining the potential change due to a given current density is reciprocal.
Vext(x,y,z)/Is. This model calculates the transfer resistance for different locations in a neuron, essentially modeling how well the electric field from an electrode permeates through the extracellular medium.Monopolar Electrode in Infinite Medium: For biological tissues often assumed as homogeneous, the model computes the potential using classical physics for a spherical electrode in an infinite medium - a simplified yet informative way to approximate stimulation effects.
Bipolar Electrode Configuration: This specific setup models how two electrodes (one positive, one negative) influence an axon, crucial for studies that involve opposing electrode pairs as used in various neuroprosthetic devices.
Parallel Plate Configuration: This simulates a uniform electric field produced by parallel plate electrodes, emphasizing scenarios where a neuron is entirely subject to such fields, often used in laboratory experiments to understand field effects on neurons.
The resistivity (rho) plays a crucial role in determining the extracellular potential. Values are suggested for different biological media, such as squid axon cytoplasm or brain tissue, reflecting the relevance of electrode-tissue models in both invertebrate and vertebrate systems.
Models like these are fundamental in exploring how external electrical fields affect neuronal excitability and conduction. Such research provides insights into developing neuroprosthetics, deep brain stimulators, and other therapeutic devices that rely on precise electrical manipulation of neural circuits. By computationally estimating the effects, researchers can optimize electrode placement and parameters for effective neuromodulation therapies.