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        "author": "Jun Zhuang @ Allen Institute for Brain Science",
        "author_email": "junz@alleninstitute.org",
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        "description": "# retinotopic_mapping package\r\n\r\nby Jun Zhuang\r\n&copy; 2016 Allen Institute\r\nemail: junz&lt;AT&gt;alleninstitute&lt;DOT&gt;org\r\n\r\nFor a more thorough introduction and explanation of the module please\r\nsee our [documentation](http://retinotopic-mapping.readthedocs.io/).\r\nIf the online version of documentation looks incomplete. Please refer\r\nto the locally built html version in `/doc/build/html/` folder under\r\n`doc` branch.\r\n\r\nThe retinotopic mapping package is a self-contained module\r\nfor display visual stimuli in visual physiology experiments and\r\nfor data analysis on the results of those experiments. This package is\r\nused to display visual stimulus and to analyze data for the study\r\nZhuang et al., 2017 (7)\r\n\r\nThe visual stimuli generation and display is implemented in the modules\r\n`MonitorSetup.py`, `StimulusRoutines.py` and `DisplayStimulus.py`.\r\nThese modules allow you to display flashing circle, sparse noise,\r\nlocally sparse noise, drifting grading circle, static grading circle\r\nand others with spherical correction. The method for spherical\r\ncorrection is the same as Marshel et al. 2011 (2). These stimulus\r\nroutines are highly customizable and designed to give the user\r\nsignificant flexibility and control in creative experimental design.\r\n\r\nPlease check the '\\examples\\visual_stimulation' folder for\r\nexample script `example_stimulation.py` of visual stimulation.\r\n\r\nOne specific analysis this package can perform is automated\r\nsegmentation of the mouse visual cortex, which is implemented in\r\n`RetinotopicMapping.py` module.\r\nThe experimental setup and analysis routine was\r\nmodified from Garrett et al. 2014 (1), and closely follows\r\nthe protocols and procedures documented in Juavinett et al. 2016\r\n(2).\r\n\r\nThe analysis takes visual altitude and azimuth maps of mouse cortex\r\nas inputs, calculates the visual sign of each pixel and auto-segments\r\nthe cortical surface into primary visual cortex and multiple higher\r\nvisual cortices. Ideally, the visual altitude and azimuth maps can be\r\ngenerated by fourier analysis of population cortical responses to\r\nperiodic sweeping checker board visual stimuli (3, 4).\r\n\r\nThe package also provides some useful plotting functions to visualize\r\nthe results.\r\n\r\nPlease check the '\\examples\\signmap_analysis' folder for a [jupyter\r\nnotebook](https://github.com/zhuangjun1981/retinotopic_mapping/blob/master/retinotopic_mapping/examples/signmap_analysis/retinotopic_mapping_example.ipynb)\r\nshowing automated visual area segmentation of mouse cortex.\r\n\r\n### Contributors:\r\n* Jun Zhuang @zhuangj\r\n* John Yearseley @yearsj\r\n* Derric Williams @derricw\r\n\r\n### Level of support\r\nWe are planning on occasional updating this tool with no fixed schedule. Community involvement is encouraged through both issues and pull requests.\r\n\r\n#### Language:\r\n\r\n1. python 2.7\r\n\r\n\r\n#### Install:\r\n```\r\ncd <package_path>\r\nconda env create -f environment.yml (this will take a while)\r\nactivate retinotopic_mapping (Windows)\r\nsource activate retinotopic_mapping (Mac or Linux)\r\npython setup.py install\r\n```\r\n\r\n\r\n#### Dependencies:\r\n\r\n1. numpy, version 1.13.1 or later\r\n2. scipy, version 0.17.1 or later\r\n3. matplotlib, version 1.5.1 or later\r\n4. psychopy, version 1.85.2 or later\r\n5. pyglet, version 1.2.4 or later\r\n6. OpenCV-Python, version >= 2.4.8, <= 2.4.10\r\n7. scikit-image, version 0.12.3 or later\r\n8. PIL, version 4.3.0 or later\r\n9. PyDAQmx, version 1.3.2 or later\r\n   * requires National Instruments DAQmx driver, version 15.0 or later\r\n\r\n#### References:\r\n\r\n1. Garrett ME, Nauhaus I, Marshel JH, Callaway EM (2014) Topography and areal organization of mouse visual cortex. J Neurosci 34:12587-12600.\r\n\r\n2. 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.\r\n\r\n3. Kalatsky VA, Stryker MP (2003) New paradigm for optical imaging: temporally encoded maps of intrinsic signal. Neuron 38:529-545.\r\n\r\n4. Marshel JH, Kaye AP, Nauhaus I, Callaway EM (2012) Anterior-posterior direction opponency in the superficial mouse lateral geniculate nucleus. Neuron 76:713-720.\r\n\r\n5. 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.\r\n\r\n6. Sereno MI, McDonald CT, Allman JM (1994) Analysis of retinotopic maps in extrastriate cortex. Cereb Cortex 4:601-620.\r\n\r\n7. Zhuang J, Ng L, Williams D, Valley M, Li Y, Garrett M, Waters J (2017) An extended retinotopic map of mouse cortex. eLife 6: e18372.\r\n\r\n\r\n#### Issues:\r\n\r\n1. Most image analysis parameters are defined as number of pixels, not microns.\r\n2. Works in windows, but not fully tested on Mac and Linux.\r\n\r\n",
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