COMPUTER MODELING FOR DENDRITIC CONSTRUCTION AND CONNECTIVITY OF NEURAL CELLS

Abstract

A computational stochastic model that describes the growth of neuronal dendrites in a single nerve cell and within neural network; the model supplies the ability to study different growth factors like randomized growth, position of stimulus directing dendrites and boarders of spanning dendritic tree, as well as a full understanding of network connectivity. Quantitative metrics are calculated to verify the model outputs to realistic constructions like dimensional and electrical metrics. The outputs show that the model is considered to be reliable for discipline types of nerve cells.