Metadata-Version: 1.1
Name: PyMapRetinotopic
Version: 1.0.0
Summary: retinotopic mapping tools
Home-page: https://github.com/zhuangjun1981/retinotopic_mapping
Author: Jun Zhuang @ Allen Institute for Brain Science
Author-email: junz@alleninstitute.org
License: GNU
Description: # retinotopic_mapping package  
        
        by Jun Zhuang  
        &copy; 2016 Allen Institute  
        email: junz&lt;AT&gt;alleninstitute&lt;DOT&gt;org  
        
        For a more thorough introduction and explanation of the module please 
        see our [documentation](http://retinotopic-mapping.readthedocs.io/en/latest/).
        
        The retinotopic mapping package is a self-contained module
        for performing automated segmentation of the mouse
        visual cortex. The experimental setup and analysis routine was
        modified from Garrett et al. 2014 (1), and closely follows
        the protocols and procedures documented in Juavinett et al. 2016
        (2).
        
        The code base contains several stimulus routines which are
        highly customizable and designed to give the user significant
        flexibility and control in creative experimental design. There
        are two distinct but connected aspects to the package:
        
        1. an online experimental component comprised of the
        `MonitorSetup`, `StimulusRoutines`, and
        `DisplayStimulus` modules
        
        2. an offline automated analysis component provided
        by the `RetinotopicMapping` module
        
        The analysis takes visual altitude and azimuth maps of mouse cortex as inputs, calculates the visual 
        sign of each pixel and auto-segments the cortical surface into primary visual cortex and multiple higher
        visual cortices. Ideally, the visual altitude and azimuth maps can be generated by fourier analysis of
        population cortical responses to periodic sweeping checker board visual stimuli (3, 4). 
        
        The package also provides some useful plotting functions to visualize the results.
        
        Please check the jupyter notebook in the '\examples' folder for a documented that takes an experimental
        data set generated from the `StimulusRoutine.py` module and then performs an automated visual segmentation
        of the mouse cortex using the `Retinotopic.py` module
        
        https://github.com/zhuangjun1981/retinotopic_mapping/blob/master/retinotopic_mapping/examples/retinotopic_mapping_example.ipynb
        
        ### Contributors:
        * Jun Zhuang @zhuang1981
        * John Yearseley @yearsj
        * Derric Williams @derricw
        
        #### Language:
        
        1. python 2.7
        
        
        #### Install:
        ```
        cd <package_path>
        python setup.py install
        ```
        
        
        #### Dependencies:
        
        1. numpy, version 1.10.4 or later
        2. scipy, version 0.17.0 or later
        3. OpenCV-Python, version 2.4.8 or later
        4. scikit-image, version 0.12.3 or later
        5. matplotlib, version 1.5.1 or later
        6. tifffile, version 0.7.0 or later
        7. PsychoPy, version 1.7 or later
        8. PyDAQmx, version 1.2 or later 
           * requires National Instruments DAQmx driver, version 15.0 or later
        
        #### References:
        
        1. Garrett ME, Nauhaus I, Marshel JH, Callaway EM (2014) Topography and areal organization of mouse visual cortex. J Neurosci 34:12587-12600.
        
        2. Juavinett AL, Nauhaus I, Garrett ME, Zhuang J, Callaway EM (2017). Automated identification of mouse visual areas with intrinsic signal imaging. Nature Protocols. 12: 32-43.
        
        3. Kalatsky VA, Stryker MP (2003) New paradigm for optical imaging: temporally encoded maps of intrinsic signal. Neuron 38:529-545.
        
        4. Marshel JH, Kaye AP, Nauhaus I, Callaway EM (2012) Anterior-posterior direction opponency in the superficial mouse lateral geniculate nucleus. Neuron 76:713-720.
        
        5. Sereno MI, Dale AM, Reppas JB, Kwong KK, Belliveau JW, Brady TJ, Rosen BR, Tootell RB (1995) Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science 268:889-893.
        
        6. Sereno MI, McDonald CT, Allman JM (1994) Analysis of retinotopic maps in extrastriate cortex. Cereb Cortex 4:601-620.
        
        
        #### Issues:
        
        1. Most image analysis parameters are defined as number of pixels, not microns.
        2. Works in windows, but not fully tested on Mac and Linux.
Keywords: retinotopic visual neuroscience
Platform: any
Classifier: Programming Language :: Python
Classifier: Development Status :: 4 - Beta
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
