1 Introduction -- I Basic Concepts -- 2 Visual perception of motion -- 3 Basic principles of the dynamic approach -- 4 Dynamic neural fields -- II Model for Motion Perception -- 5 Dynamic neural field model for motion perception -- 6 Necessity of the concepts: Model for the motion quartet -- 7 Sufficiency of the concepts: Field model for 2D-motion perception -- 8 Relationships: neural fields and computational algorithms -- 9 Identification of field models from neurophysiological data -- III Other Applications of Neural Fields -- 10 Neural field model for the motor planning of eye movements -- 11 Technical applications of neural fields -- 12 Discussion -- Appendices -- A Appendix of chapter 3 -- A.1 Relationship: Eye-Position and Relative Phase Dynamics -- B Appendix of chapter 6 -- B.1 Geometry Dependence of Feed-Forward Input -- B.2 Stochastic Bistable Dynamics -- B.3 Parameters of the Model for the Motion Quartet -- C Appendix of chapter 7 -- C.1 Properties of the Interaction Function -- C.2 One-Dimensional Neural Field Model for Motion Direction -- C.3 Parameters of the Neural Field Model -- D Appendix of chapter 8 -- D.1 Proof of Theorem 4 -- D.2 Proof of Lemma 1 -- D.3 Proof of Theorem 5 -- E Appendix of chapter 9 -- E.2 Least Squares Estimation of Kernel Functions -- E.3 Equivalent Feed-Forward System for a Linear Threshold -- F Appendix of chapter 11 -- F. 1 Transformation between Robot and World Coordinates -- F.2 Transformations between the Perceptive Spaces -- F.3 Learning of the Parameters of the Approximation Dynamics -- List of Symbols.