Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception

Paula Sanz Leon (1) , Ivo Vanzetta (2) , Guillaume S. Masson (1) , Laurent Perrinet (1)

1 INT - Institut de Neurosciences de la Timone
2 InVibe

Choosing an appropriate set of stimuli is essential in order 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 which 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.

Mots clés: Motion Clouds; Random Phase Textures; Low-level sensory systems; eye movements; optimal stimulation; natural scenes; motion detection; random textures; Python

Domaines: Sciences cognitives; Neurosciences; Informatique

Paula Sanz Leon, Ivo Vanzetta, Guillaume S. Masson, Laurent Perrinet. Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception. Journal of Neurophysiology, 2012, 107 (11), pp.3217-3226. ⟨10.1152/jn.00737.2011⟩. ⟨hal-02387898⟩