Elements of applied bifurcation theory (2nd ed.)
Elements of applied bifurcation theory (2nd ed.)
Dynamic Neural Field Theory for Motion Perception
Dynamic Neural Field Theory for Motion Perception
Neural models of motion integration and segmentation
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
An overview of the Trilinos project
ACM Transactions on Mathematical Software (TOMS) - Special issue on the Advanced CompuTational Software (ACTS) Collection
Disambiguating Visual Motion Through Contextual Feedback Modulation
Neural Computation
Disambiguating Visual Motion by Form-Motion Interaction--a Computational Model
International Journal of Computer Vision
Neural fields models of visual areas: principles, successes, and caveats
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Journal of Computational Neuroscience
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A computational study into the motion perception dynamics of a multistable psychophysics stimulus is presented. A diagonally drifting grating viewed through a square aperture is perceived as moving in the actual grating direction or in line with the aperture edges (horizontally or vertically). The different percepts are the product of interplay between ambiguous contour cues and specific terminator cues. We present a dynamical model of motion integration that performs direction selection for such a stimulus and link the different percepts to coexisting steady states of the underlying equations. We apply the powerful tools of bifurcation analysis and numerical continuation to study changes to the model's solution structure under the variation of parameters. Indeed, we apply these tools in a systematic way, taking into account biological and mathematical constraints, in order to fix model parameters. A region of parameter space is identified for which the model reproduces the qualitative behaviour observed in experiments. The temporal dynamics of motion integration are studied within this region; specifically, the effect of varying the stimulus gain is studied, which allows for qualitative predictions to be made.