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Summary form only given. The resurgence of artificial neural networks in the past decade has affected basic and applied research in neural and cognitive sciences and has generated numerous models that address centuries old questions confronted by neuroscientists and neural engineers. Computational and silicon based models involving dynamics of neural networks play increasingly larger roles in the quantitative formulation of these questions. Topics such as perception, consciousness, memory and will are no longer quantitatively untouchable subjects. They can be formulated with biologically realistic models and tested experimentally. The emerging discipline of neural network dynamics strives to understand the organizational principles and underlying mechanisms of the biology and behavior of neural systems in nature. It coalesces the new emerging fields in engineering and physical sciences including nonlinear dynamics, chaos, wavelets and time-frequency distributions, informatics, silicon and nanotechnologies with the molecular, cellular, systems physiology, cognitive and behavioral neuroscience. To highlight this emerging discipline, we devote this symposium to the neural network dynamics related research.