update documentation

code/docs/highspeed-glm-docs.Rmd

@@ -11,17 +11,35 @@ if (basename(here::here()) == "highspeed"){
 
 ## Feature selection: First-level GLMs
 
+### Overview
+
+As described above, we used a feature selection approach that combined binarized anatomical ROIs with functional ROIs based on first-level GLMs.
+Below we show which code was used to run the first-level GLMs based on Nipype:
+
+#### Data availability
+
+The data is freely available from https://github.com/lnnrtwttkhn/highspeed-glm and https://gin.g-node.org/lnnrtwttkhn/highspeed-glm.
+
+#### License
+
+The dataset is licensed under Creative Commons Attribution-ShareAlike 4.0.
+Please see https://creativecommons.org/licenses/by-sa/4.0/ for details.
+
 ### Main GLM workflow (`highspeed-glm-main.py`)
 
+The code below shows the main Nipype workflow to run first-level GLMs used for feature selection:
+
 ```{python, echo=TRUE, code=readLines(file.path(path_root, "code", "glm", "highspeed-glm-main.py")), eval=FALSE, python.reticulate=FALSE}
 ```
 
 ### Extra GLM functions (`highspeed-glm-functions.py`)
 
+The main GLM Nipype workflow shown above uses the following custom functions:
+
 ```{python, echo=TRUE, code=readLines(file.path(path_root, "code", "glm", "highspeed_glm_functions.py")), eval=FALSE, python.reticulate=FALSE}
 ```
 
-### Requirements
+### Software: Required packages
 
 The `requirements.txt` file lists the required packages which can be installed e.g., using `pip install -r requirements.txt`