Dynamic field theory provides an explanation for how the brain gives rise to behavior via the coordinated activity of populations of neurons. Dynamic Neural Field models use differential equations to abstract and describe the activity patterns and interactions of such neural populations. In this way, one can simulate and visualize processes such as attention, memory, and change detection, across one or more dimensions such as spatial position or color. These models have been used in a variety of disciplines - from Psychology and Physiology to Robotics. In this talk, I will introduce the motivation, fundamental concepts, and positive results of Dynamic Neural Field modeling as experienced during my PhD research.
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