title: A neural model of feature attention in motion perception.
abstract: We utilize a model of motion perception to link a physiological study of feature attention in cortical motion processing to a psychophysical experiment of motion perception. We explain effects of feature attention by modulatory excitation of neural activity patterns in a framework of biased competition. Our model allows us to qualitatively replicate physiological data concerning attentional modulation and to generate model behavior in a decision experiment that is consistent with psychophysical observations. Furthermore, our investigation makes predictions for future psychophysical experiments.
authors.affiliation: University of Ulm, Department of Neural Information Processing, Oberer Eselsberg, D-89069 Ulm, Germany. pierre.bayerl@uni-ulm.de
authors.forename: Pierre
authors.initials: P
authors.lastname: Bayerl
authors.forename: Heiko
authors.initials: H
authors.lastname: Neumann
mesh_terms: D008959:Models, Neurological; D009038:Motion; D009474:Neurons / Q000502:physiology*; D014796:Visual Perception