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

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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: installing and running the python scripts

MotionClouds are parameterized stimuli with controlled motion content
and no spatial coherence. They are precisely tuned in the frequency
space.

    A full description can be found in Paula S. Leon, Ivo Vanzetta,
    Guillaume S. Masson, Laurent U. Perrinet. Motion Clouds:
    Model-based stimulus synthesis of natural-like random textures for
    the study of motion perception, URL . Journal of Neurophysiology,
    107(11):3217--3226, 2012, see
    http://www.ncbi.nlm.nih.gov/pubmed/22423003 or
    http://jn.physiology.org/content/107/11/3217 .

The latest changes are available from this web site:

https://github.com/NeuralEnsemble/MotionClouds

Installing and running the python scripts:

This package consists of:

    MotionClouds.py : the API with all the math and display routines,

    test_*.py : different types of stimuli are tested,

    experiment_*py : different experiments.

    fig_*py : different scripts used to generate wiki pages.

    figures : resulting figures of tests and experiments (as set in
    the variable MotionClouds.figpath.

    Makefile : a GNUmake file to edit files make edit, generate
    figures make figures or compile the documentation make doc.

Installation

    Installation of MotionClouds consists simply in downloading the
    MotionClouds.py file which contains all routines to compute and
    use the MotionClouds textures. This script uses python] which
    comes (pre-installed / easy to download and install) on many
    operating systems.  Installation has some dependencies:

        mandatory: numpy is the core library used to compute textures,

        optional: mayavi is used to visualize envelopes,

        optional: ffmpeg is used to generate movies.

        optional: matplotlib, scipy (with PIL support) and imagemagick
        are used to generate figures in the documentation.

        optional: progressbar for displaying progress of encoding. 

installation using custom scripts

    depending on your system you should use in a terminal window

    sh install_dependencies_debian.sh

    or

    sh install_dependencies_macosx.sh

    an alternative is to use a virtual machine such as for instance
    the one provided by the NeuroDebian team.

Installation in Debian-based distributions (such as Ubuntu)

    Use the aptitude front end to install packages: (or alternatively
    apt -get if you feel confident with that tool instead)

    python is supported by most distribution and should already be
    installed. You can check which version is installed :

    python -V

    The same libraries as for MacOsX need to be installed :

    sudo aptitude install python-scipy python-numpy python-matplotlib

    Idem for the progress bar module

    sudo easy_install progressbar 

    Install the ffmpeg encoder to work with mpeg, avi, etc, videos:

    sudo aptitude install ffmpeg

    when creating MoiMoin pages, it is useful to package images in a
    zip file:

    aptitude install zip

Installation on MacOsX: EPD

    Enthought distributes a battery-included installation of
    python. It is recommended to use the i386 version as the 64-bits
    version lacks a proper compilation of MayaVi. You will still need
    ffmpeg to make movies (see HomeBrew or MacPorts section below).

Installation on MacOsX: HomeBrew (for more experienced users)

    install it following their instructions :

    ruby -e "$(curl -fsSL https://raw.github.com/gist/323731)"

    then install the following packages

    # install python through HomeBrew as a framework
    brew install python --framework

    # bootstrap pip
    /usr/local/share/python/easy_install pip
    /usr/local/share/python/pip install --upgrade distribute

    # libraries
    brew install gfortran
    pip install -U ipython

    # useful packages
    pip install -U nose
    pip install -U progressbar
    easy_install pyreport
    easy_install -f http://dist.plone.org/thirdparty/ -U PIL==1.1.7

    # numpy et al
    pip install -U numpy
    pip install -U scipy
    pip install -U -e git+git@github.com:matplotlib/matplotlib.git#egg=matplotlib
    # pip install -f http://downloads.sourceforge.net/project/matplotlib/matplotlib/matplotlib-1.0/matplotlib-1.0.0.tar.gz matplotlib

    # IDE
    pip install -U sphinx pyflakes rope
    brew install sip
    brew install pyqt
    pip install -U spyder

    # mayavi
    brew install vtk --python
    pip install -U traitsbackendqt
    pip install -U configobj
    pip install  -U "Mayavi[app]"

        be sure to install ffmpeg :

        brew install ffmpeg
        brew install zip

Installation on MacOsX: MacPorts (outdated documentation)

On MacOsX, this may be achieved using MacPorts:

    MacPorts is a generic package manager, somewhat related to
    Debian's apt scheme. You will need the XCode package which sits in
    your MacOSX installation DVD or may downloaded on Apple's site or
    even borrowed to me.  Once installed, do the following on the
    command-line

        on Leopard (python 26 works fine too):

        sudo port install python25 python_select 
        sudo python_select python25
        sudo port install  py25-pil py25-numpy py25-scipy py25-ipython py25-matplotlib
        +cairo+latex+tkinter
        sudo port install py25-enthoughtbase py25-mayavi py25-traitsbackendqt

        on Snow Leopard:

        sudo port install python26 python_select 
        sudo python_select python26
        sudo port install  py26-pil py26-numpy py26-scipy py26-ipython py26-matplotlib
        +cairo+latex+tkinter
        sudo port install py26-enthoughtbase py26-mayavi py26-traitsbackendqt
         * then optionally, {{{
        sudo easy_install progressbar pygarrayimage pyglet

        be sure to install ffmpeg :

        sudo port install ffmpeg

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