Motion Clouds: Synthesis of random textures for motion perception (Leon et al. 2012)

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We describe a framework to generate random texture movies with controlled information content. In particular, these stimuli can be made closer to naturalistic textures compared to usual stimuli such as gratings and random-dot kinetograms. We simplified the definition to parametrically define these "Motion Clouds" around the most prevalent feature axis (mean and bandwith): direction, spatial frequency, orientation.
1 . Leon PS, Vanzetta I, Masson GS, Perrinet LU (2012) Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception. J Neurophysiol 107:3217-26 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Simulation Environment: Python;
Model Concept(s): Pattern Recognition; Temporal Pattern Generation; Spatio-temporal Activity Patterns; Parameter Fitting; Methods; Perceptual Categories; Noise Sensitivity; Envelope synthesis; Sensory processing; Motion Detection;
# installing dependencies on Debian for MotionClouds
# --------------------------------------------------
# A script for the impatient:
# uncomment to fit your installation preference
# others should read the README.txt doc.

# 1) minimal install 
# sudo aptitude install python-numpy python-scipy 

# 2) minimal install with visualization
# sudo aptitude install python-numpy python-scipy mayavi2 python-matplotlib ffmpeg

# 3) full install with python editor and libraries for various export types
sudo aptitude install python-numpy python-scipy mayavi2 python-matplotlib ffmpeg spyder liblzo2-2 python-tables imagemagick

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