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Replicating Stevens et al. (J. Neuroscience, 2013)

This directory includes all the code necessary to re-run all the simulations and regenerate all the figures detailed in Stevens et al. (2013).

author = {Stevens, Jean-Luc R. and Law, Judith S. and
Antol\'{i}k, J\'{a}n and Bednar, James A.},
title = {Mechanisms for Stable, Robust, and Adaptive
Development of Orientation Maps in the Primary Visual Cortex},
journal = {The Journal of Neuroscience},
volume = {33},
number = {40},
pages = {15747-15766},
year = {2013},
doi = {10.1523/JNEUROSCI.1037-13.2013},

Getting Started

To run the model, you will need the Topographica simulator. To install from GitHub, you may follow these instructions which includes the instructions for installing IPython Notebook.

With Topographica installed you can now explore the model from this directory using the Topographica GUI without requiring IPython Notebook:

../../topographica -g gcal.ty

To go further, using IPython notebook to explore how the model is put together and how to put results together into figures, you can run the following command in this directory:

../../topographica -n

Now if you visit localhost:8888 in your browser you should be able to select the 'stevens_jn13' or 'gcal' notebooks. Note that if a port number other than 8888 be required, the appropriate port number will be shown in the terminal. IPython >=1.0 is required.

Running the live notebooks allows you to explore the model iteratively. If you simply wish to view the static contents of these notebooks, you may view the following two HTML versions:

  • Model definition: A notebook that simultaneously defines the model and explores it. Running the live version of this notebook generates the Topographica model file 'gcal.ty' and will regenerate the contents shown in the HTML version.
  • Simulation and Figures: Defines all 842 model simulations needed to reproduce all the figures, allows you to launch them and automatically builds the corresponding SVG figures used in publication. Although running the full set of simulations is computationally expensive, the live notebook allows you to select a small subset before launching the jobs.

Directory organization

There is a README file in every subdirectory of 'jn13_figures'. The overall organization is as follows:

  • jn13_figures/__init__.py: Python code to dynamically generate the SVG figures.
  • jn13_figures/figures: Static SVG figures (experimental data) and symbolic links to dynamically generated figures.
  • jn13_figures/lib: Utilities used by __init__.py, gcal.ipynb and stevens_jn13.ipynb. See the README file for more details about the files in this directory.
  • jn13_figures/output: Simulation output and the figure build directory build_dir.
  • jn13_figures/templates: SVG templates for all the dynamically generated figures. Raster placeholders snapshots are stored in the snapshots subdirectory.