Continue with conversion

Author: mvdoc

doc/references.rst

@@ -44,4 +44,8 @@ parse:
     - amsmath
     - dollarmath
 
-  
+sphinx:
+  config:
+    bibtex_reference_style: author_year
+    # bibtex_bibfiles: references.bib
+

tutorials/_config.yml

@@ -5,7 +5,7 @@ format: jb-article
 root: index
 sections:
 - file: voxelwise_modeling
-  title: Voxelwise modeling framework
+  title: Overview of the VEM framework
 - file: voxelwise_package
   title: Helper Python package
 - file: notebooks/shortclips/README

tutorials/_toc.yml

@@ -0,0 +1,48 @@
+# Voxelwise Encoding Model (VEM) tutorials
+
+Welcome to the tutorials on the Voxelwise Encoding Model framework from the
+[GallantLab](https://gallantlab.org).
+
+If you use these tutorials for your work, consider citing the corresponding paper:
+
+> T. Dupré La Tour, M. Visconti di Oleggio Castello, and J. L. Gallant. The voxelwise modeling framework: a tutorial introduction to fitting encoding models to fMRI data. psyRxiv, 2024. [doi:10.31234/osf.io/t975e.](https://doi.org/10.31234/osf.io/t975e)
+
+You can find a copy of the paper [here](https://github.com/gallantlab/voxelwise_tutorials/blob/main/paper/voxelwise_tutorials_paper.pdf).
+
+## Getting started
+
+This website contains tutorials describing how to use the
+[Voxelwise Encoding Model framework](voxelwise_modeling.html).
+
+To explore these tutorials, one can:
+
+- read the rendered examples in the tutorials
+  [gallery of examples](_auto_examples/index.html) (recommended)
+- run the Python scripts ([tutorials](https://github.com/gallantlab/voxelwise_tutorials/tree/main/tutorials) directory)
+- run the Jupyter notebooks ([tutorials/notebooks
+  ](https://github.com/gallantlab/voxelwise_tutorials/tree/main/tutorials/notebooks)
+  directory)
+- run the notebooks in Google Colab: 
+  [all notebooks](https://colab.research.google.com/github/gallantlab/voxelwise_tutorials/blob/main/tutorials/notebooks/shortclips/merged_for_colab.ipynb) or
+  [only the notebooks about model fitting](https://colab.research.google.com/github/gallantlab/voxelwise_tutorials/blob/main/tutorials/notebooks/shortclips/merged_for_colab_model_fitting.ipynb) -->
+
+The tutorials are best explored in order, starting with the [Shortclips
+tutorial](_auto_examples/index.html).
+
+The project is available on GitHub at [gallantlab/voxelwise_tutorials
+](https://github.com/gallantlab/voxelwise_tutorials). On top of the tutorials
+scripts, the GitHub repository contains a Python package called
+`voxelwise_tutorials`, which contains useful functions to download the data
+sets, load the files, process the data, and visualize the results. Install
+instructions are available [here](voxelwise_package.html).
+
+## Cite as
+
+If you use one of our packages in your work (`voxelwise_tutorials`
+{cite}`dupre2023`, `himalaya` {cite}`dupre2022`, `pycortex`
+{cite}`gao2015`, or `pymoten` {cite}`nunez2021software`), please cite the
+corresponding publications.
+
+If you use one of our public datasets in your work 
+(`shortclips` {cite}`huth2022data`, `vim-2` {cite}`nishimoto2014data`), 
+please cite the corresponding publications.