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Neuroscience:Noise and Chaos in Neural Systems
This chapter discusses two questions (1) how to characterize the dendritic arborization patterns and what could be the mechanism of the generation of dendritic branching trees and (2) what can be the role of environmental noise in the ontogenetic formation of ordered cortical structures. The dendritic arborization can be classified based on (1) randomness versus regularity in regard to branching of the various dendritic segments, resulting in a continuous spectrum ranging from the “radiate” to the “tufted” types of arborization and (2) the degree of deviation of the individual branches from a radiated and rectilinear course. A three-variable extension of the Turing-Gierer-Meinhardt (TGM) model describes network formation based on the diffusible morphogen concept. This model leads to uniform behavior. Accepting the view that neural dendritic branching might have a self-similar character, its development can be modeled by fractal generating growth models.
This chapter discusses two questions (1) how to characterize the dendritic arborization patterns and what could be the mechanism of the generation of dendritic branching trees and (2) what can be the role of environmental noise in the ontogenetic formation of ordered cortical structures. The dendritic arborization can be classified based on (1) randomness versus regularity in regard to branching of the various dendritic segments, resulting in a continuous spectrum ranging from the “radiate” to the “tufted” types of arborization and (2) the degree of deviation of the individual branches from a radiated and rectilinear course. A three-variable extension of the Turing-Gierer-Meinhardt (TGM) model describes network formation based on the diffusible morphogen concept. This model leads to uniform behavior. Accepting the view that neural dendritic branching might have a self-similar character, its development can be modeled by fractal generating growth models.
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