title: Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception.
abstract: Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional dimension, such as the eye movement following the motion of a visual scene. Here, we describe a framework to generate random texture movies with controlled information content, i.e., Motion Clouds. These stimuli are defined using a generative model that is based on controlled experimental parametrization. We show that Motion Clouds correspond to dense mixing of localized moving gratings with random positions. Their global envelope is similar to natural-like stimulation with an approximate full-field translation corresponding to a retinal slip. We describe the construction of these stimuli mathematically and propose an open-source Python-based implementation. Examples of the use of this framework are shown. We also propose extensions to other modalities such as color vision, touch, and audition.
authors.affiliation: Institut de Neurosciences de la Timone, Centre National de la Recherche Scientifique/Aix-Marseille University, Marseille, France.
authors.forename: Paula Sanz
authors.initials: PS
authors.lastname: Leon
authors.forename: Ivo
authors.initials: I
authors.lastname: Vanzetta
authors.forename: Guillaume S
authors.initials: GS
authors.lastname: Masson
authors.forename: Laurent U
authors.initials: LU
authors.lastname: Perrinet
mesh_terms: D003118:Color Perception / Q000502:physiology; D008959:Models, Neurological; D009039:Motion Perception / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods*; D011897:Random Allocation; D014110:Touch / Q000502:physiology*