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- W2012189712 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." @default.
- W2012189712 created "2016-06-24" @default.
- W2012189712 creator A5007591985 @default.
- W2012189712 creator A5010762686 @default.
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- W2012189712 creator A5033367098 @default.
- W2012189712 date "2012-06-01" @default.
- W2012189712 modified "2023-10-18" @default.
- W2012189712 title "Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception" @default.
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- W2012189712 doi "https://doi.org/10.1152/jn.00737.2011" @default.
- W2012189712 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/22423003" @default.
- W2012189712 hasPublicationYear "2012" @default.
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