EHN neurolibre DONE

CITATION.cff

@@ -0,0 +1,66 @@
+cff-version: "1.2.0"
+authors:
+- family-names: Wang
+  given-names: Hao-Ting
+  orcid: "https://orcid.org/0000-0003-4078-2038"
+- family-names: Meisler
+  given-names: Steven L
+  orcid: "https://orcid.org/0000-0002-8888-1572"
+- family-names: Sharmarke
+  given-names: Hanad
+- family-names: Clarke
+  given-names: Natasha
+- family-names: Paugam
+  given-names: François
+- family-names: Gensollen
+  given-names: Nicolas
+  orcid: "https://orcid.org/0000-0001-7199-9753"
+- family-names: Markiewicz
+  given-names: Christopher J
+  orcid: "https://orcid.org/0000-0002-6533-164X"
+- family-names: Thirion
+  given-names: Bertrand
+  orcid: "https://orcid.org/0000-0001-5018-7895"
+- family-names: Bellec
+  given-names: Pierre
+  orcid: "https://orcid.org/0000-0002-9111-0699"
+doi: 10.5281
+message: To reference this work, please cite our reproducible preprint
+  in NeuroLibre.
+preferred-citation:
+  authors:
+  - family-names: Wang
+    given-names: Hao-Ting
+    orcid: "https://orcid.org/0000-0003-4078-2038"
+  - family-names: Meisler
+    given-names: Steven L
+    orcid: "https://orcid.org/0000-0002-8888-1572"
+  - family-names: Sharmarke
+    given-names: Hanad
+  - family-names: Clarke
+    given-names: Natasha
+  - family-names: Paugam
+    given-names: François
+  - family-names: Gensollen
+    given-names: Nicolas
+    orcid: "https://orcid.org/0000-0001-7199-9753"
+  - family-names: Markiewicz
+    given-names: Christopher J
+    orcid: "https://orcid.org/0000-0002-6533-164X"
+  - family-names: Thirion
+    given-names: Bertrand
+    orcid: "https://orcid.org/0000-0001-5018-7895"
+  - family-names: Bellec
+    given-names: Pierre
+    orcid: "https://orcid.org/0000-0002-9111-0699"
+  date-published: 2023-06-19
+  doi: 10.55458/neurolibre.00012
+  journal: NeuroLibre Reproducible Preprints
+  publisher:
+    name: NeuroLibre
+  title: A reproducible benchmark of resting-state fMRI denoising
+    strategies using fMRIPrep and Nilearn
+  type: preprint
+  url: "https://neurolibre.org/papers/10.55458/neurolibre.00012"
+title: A reproducible benchmark of resting-state fMRI denoising
+  strategies using fMRIPrep and Nilearn

README.md

@@ -1,11 +1,12 @@
 # Benchmark denoising strategies on fMRIPrep output
 
-[![Jupyter Book Badge](https://jupyterbook.org/badge.svg)](https://simexp.github.io/fmriprep-denoise-benchmark/)
+[![DOI](https://neurolibre.org/papers/10.55458/neurolibre.00012/status.svg)](https://doi.org/10.55458/neurolibre.00012)
 
 The project is a continuation of [load_confounds](https://github.com/SIMEXP/load_confounds).
 The aim is to evaluate the impact of denoising strategy on functional connectivity data, using output processed by fMRIPrep LTS in a reproducible workflow.
 
-Preprint of this project is now on [biorxiv](https://www.biorxiv.org/content/10.1101/2023.04.18.537240).
+**Preprint of the manuscript is now on [biorxiv](https://www.biorxiv.org/content/10.1101/2023.04.18.537240).
+The reporducible Jupyter Book preprint is on [NeuroLibre](https://neurolibre.org/papers/10.55458/neurolibre.00012).**
 
 ## Quick start
 
@@ -26,20 +27,22 @@ make book
 
 - `content/` is the source of the JupyterBook.
 
-- `data/` is reserved to store data for building the JupyterBook.
+- `data/` is reserved to store data for running analysis.
   To build the book, one will need all the metrics from the study.
   The metrics are here:
   [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7764979.svg)](https://doi.org/10.5281/zenodo.7764979)
+  The data will be automatically downloaded to `content/notebooks/data`.
+  You can by pass this step through accessing the Neurolibre preprint [![DOI](https://neurolibre.org/papers/10.55458/neurolibre.00012/status.svg)](https://doi.org/10.55458/neurolibre.00012)!
 
 - Custom code is located in `fmriprep_denoise/`. This project is installable.
 
-- Preprocessing SLURM scripts are in `script/` 
+- Preprocessing SLURM scripts, and scripts for creating figure for manuscript are in `scripts/`. 
 
 
 ## Poster and presentations
 
 The results will be presented at QBIN science day 2023 as a flash talk, and OHBM 2023 Montreal as a poster :tada:. 
 
-The preliminary results were be presented at OHBM 2022 as a poster.
+The preliminary results were presented at OHBM 2022 as a poster.
 
 ![spoiler](./content/images/ohbm2022_abstract_head.png)