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Motion Clouds: Synthesis of random textures for motion perception (Leon et al. 2012)
 
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Model Information
Model File
Citations
Accession:
146953
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.
Reference:
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):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
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;
Implementer(s):
/
MotionClouds_modeldb
data
competing.pickle
lup_Dec_12_1003.npy
lup_Dec_12_1013.npy
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