Skip to content

python code for stimulus presentation, data acquisition, and analysis for retinotopic mapping experiments

License

Notifications You must be signed in to change notification settings

julianarhee/retinotopy-mapper

Repository files navigation

retinotopy-mapper package

Code for retinotopic mapping of rat visual cortex using wide-field imaging. Stimulus presentation, data acquisition, and data processing uses custom Python code. All software developed for imaging experiments in the Cox Lab, Harvard University.

NOTE: Current (final) version in cleanup branch.

Basic Setup

Install anaconda. Then, create the conda environment (python2.7)

	conda create env -f retino-opencv.yml
	source activate retinodev

After Installing:

  1. Setup monitor.

    python setupMonitor.py
    
  • This will prompt you for information about the monitor. Input the info for each question directly in the command line.
  • You will be prompted to save at the end.
  1. Run a stimulus protocol with the selected monitor.

    python PROTOCOL.py --monitor='MONITORNAME'
    

    If you forget which monitors have been set on the computer, you can use the -h flag to get the list of saved monitor configs:

    python PROTOCOL.py -h
    
  2. Neural data will be ignored with the --no-camera option. To save image data, add the --save-images option. If no pvapi camera is found, the default is the built-in camera on the computer. For now, use the png output-format option:

    python PROTOCOL.py --monitor='MONITOR-NAME' --save-images --output-format='png' --output-path='DATA-DIR-NAME'
    
  3. For more options, their uses, and default settings, go to help.

    python PROTOCOL.py -h
    

Sources and Contributors

This package uses a phase-encoding paradigm adapted from a number of different studies in mouse visual cortex (1-4). Stimulus parameters were determined experimentally for imaging in rats. In addition to custom code based on previously published methods, we found additional guidance from zhuangjun1981/retinotopic_mapping to be particularly helpful for area segmentation (2-4).

Code contributors Juliana Rhee (julianarhee) Cesar Echavarria (cechava) David Cox (davidcox)

Tips and Troubleshooting:

  • Error with 'gcc' during pygame install:

      export CC='/usr/bin/gcc' 
    
  • Import error with 'cv2' module:

      conda install opencv
    
  • fwpy should go somewhere on your path. You can start the psychopy UI by calling

      fwpy `which psychopyApp.py`
    

References

  1. Kalatsky VA, Stryker MP (2003) New paradigm for optical imaging: temporally encoded maps of intrinsic signal. Neuron 38:529-545.

  2. Garrett ME, Nauhaus I, Marshel JH, Callaway EM (2014) Topography and areal organization of mouse visual cortex. J Neurosci 34:12587-12600.

  3. 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.

  4. 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.

About

python code for stimulus presentation, data acquisition, and analysis for retinotopic mapping experiments

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published