Abstract
A review of the state of the art in dynamical neural network modeling is given. The main experimental facts that are used as the ground for dynamical models are presented. The putative role of oscillations and synchronous neural activity in information processing is discussed. Some examples of the models of feature binding, image segmentation, and selective attention are presented. The difficulties of model development and perspectives for further progress are outlined.
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