Introduction to Dynamic Modeling of Neuro-Sensory Systems presents the mathematical tools and methods that can describe and predict the dynamic behavior of single neurons, small assemblies of neurons devoted to a single tasks, as well as larger sensory arrays and their underlying neuropile. Focusing on small and medium-sized biological neural networks, the author pays particular attention to visual feature extraction, especially the compound eye visual system and the vertebrate retina. For computational efficiency, the ...
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Introduction to Dynamic Modeling of Neuro-Sensory Systems presents the mathematical tools and methods that can describe and predict the dynamic behavior of single neurons, small assemblies of neurons devoted to a single tasks, as well as larger sensory arrays and their underlying neuropile. Focusing on small and medium-sized biological neural networks, the author pays particular attention to visual feature extraction, especially the compound eye visual system and the vertebrate retina. For computational efficiency, the treatment avoids molecular details of neuron function and uses the locus approach for medium-scale modeling of arrays. The author uses the general, nonlinear ordinary differential equation solver Simnon (trademark) for all examples and exercises.
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