Analysis code for Waskom and Wagner (2017) PNAS
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data
lyman
README.md
commands.md
compile_data.py
correlation_analysis.py
decoding_analysis.py
figure_1.py
figure_2.py
figure_3.py
paper_statistics.ipynb
plotutils.py
roi_cache.py
run_script.sh
spatial_analysis.py
sup_figure_1.py
sup_figure_2.py
sup_figure_3.py
sup_figure_4.py
sup_figure_5.py
sup_figure_6.py
sup_figure_7.py
sup_figure_8.py
surfutils.py

README.md

Analyses for Waskom and Wagner (2017) PNAS

This repository contains analysis code for the following paper:

Waskom M.L., Wagner A.D. (2017). Distributed representation of context by intrinsic subnetworks in prefrontal cortex. Proceedings of the National Academy of the Sciences, USA.

The paper can be accessed at the PNAS website.

Data can be accessed at the Stanford Digital Repository.

A high-level overview of the commands that were executed to perform the analyses can be found in commands.md. Some of these commands execute lyman workflows using the parameters defined in the lyman/ subdirectory. Others execute experiment-specific code that are included in this repository. The experiment-specific code falls into a few different categories:

Data extraction

  • roi_cache.py: Extracts timeseries data from the regions of interest that are analyzed in the paper.

Analysis scripts

Data compilation

  • compile_data.py: Reads the individual outputs of the analysis scripts and compiles some summary data into tidy .csv files (stored in the data/ subdirectory).

Statistical analyses

  • paper_statistics.ipynb: The statistical results reported in the paper were produced by analyses performed in this notebook.

Figure scripts

These scripts generate each of the figures in the paper. They are contained in .py files with names corresponding to the relevant figure.

Support libraries

  • surfutils.py: Functions for going between volumetric and surface representations of data.

  • plotutils.py: Functions that are useful for generating consistent figures.

Version information

  • lyman/environment.yml: A conda environment file that should be able to reproduce all relevant software versions used for the analyses in the paper.

License

Copyright (c) 2017, Michael Waskom

All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither the name of the copyright holder nor the names of the software contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.