Dynamic Neural Field Theory for Motion Perception

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.