nimare-paper

The NiMARE software paper, as a Jupyter Book.

To view the built book, see https://nbclab.github.io/nimare-paper/

Building the book locally

1. Install dependencies

In order to execute the book's code, you will need install all of the Python libraries that are required. The necessary requirements and associated versions are available in binder/requirements.txt.

You can install them with the following:

pip install binder/requirements.txt

2. Download data files

The data files necessary to execute the code in this book are located at https://drive.google.com/uc?id=1LgscyPqnka163hu5mdJ1X7UvX3IvXDJ2 in a zip file. You can either download these files to a data/ folder at the same level as content/, or you can rely on repo2data to download the files automatically during the book build.

3. Build the book

To build:

jupyter-book build content/

The book is configured to rely on the pre-generated cache (execute_notebooks is set to "cache"). If you want to build from scratch, then you can either change that setting in content/_config.yml or you can run jupyter-book clean content/ before building.

Notes

The amygdala mask

To create the amygdala mask, I did:

from nilearn import datasets, image

atlas = datasets.fetch_atlas_harvard_oxford("sub-maxprob-thr25-2mm")
amyg_val = atlas["labels"].index("Right Amygdala")
amygdala_mask = image.math_img(f"img == {amyg_val}", img=atlas["maps"])
amygdala_mask.to_filename(os.path.join(DATA_DIR, "amygdala_roi.nii.gz"))

map_to_decode.nii.gz

This is just the parameter estimate map from the DerSimonianLaird meta-analysis.

Figures

While most of the figures in this manuscript are produced by the executed code, a few of them were manually created with Google Drawings. Here are the links for those figures.

Figure 0: https://docs.google.com/drawings/d/1SMJL6x5UEkr6PjeKPXsh_qG1LXQaQj-ex1Dyjyi5LNY/edit

Figure 1: https://docs.google.com/drawings/d/1qhToDmOCbvpgpqQPH8RxGaOSox4BhKNlSM9hUdMsP-4/edit

Figure 2: https://docs.google.com/drawings/d/1u9xfy8KlThtiK8QuW0t9uyMu_DP32S9W6QcvurSFC2s/edit