Multi-Compartmental Modeling for Extracellular Stimulation of Neocortex

Abstract

Aim: To explore the natural origin and changing behavior of neural responses depending on varying conditions, computational modeling of single-neuron or cluster of neurons using multi-compartmental models can provide very consistent predictions integrating with experimental work. Neural electrodes are fundamental therapeutic and diagnostic tools for a large variety of conditions. Understanding, individually or together neuronal responses, is critical for therapeutic and diagnostic techniques while dealing with certain neuropathies like Epilepsy or Parkinson's. The electrodes with different sizes and materials are the only way to interface the nervous system when it is needed to restore sensory or motor functions somehow. Material Method: Multi-compartmental neuron model is prepared by using a neuron with 3D realistic morphology from the neocortex. It is analyzed to see neurons' response to extracellular stimulation using a point source situated in two different locations, one at a time. Ideal conditions are considered for the point source. NEURON v8.0 is used for simulations. The stimulation pulse width, frequency, and amplitude are 1 ms, 20 Hz, and 250 nA respectively. Results: It is seen that the extracellular voltage profile is as expected, then it shifts towards where the stimulation electrode is moved. Closer neural compartments are better targets to generate action potential first. The effect of extracellular stimulation decreases as it moves from the source, but other compartments that are relatively in distance can also generate an action potential in several milliseconds after stimulation onset. Conclusion: Findings confirm multi-compartmental models are well-suited to predict neuronal responses. Different numbers and types of neurons' responses can be examined together with a complex realistic morphology. Parameters related to experimental conditions, like stimulation and recording, can also be analyzed.