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NIDS Machine Learning applied to fMRI data, i.e. Multi-Variate Pattern Analysis (MVPA)

You can either run everything on your computer after following the environment setup below (recommended), or you can access the lecture Jupyter notebook simply by clicking on the "Launch Binder" badge (cf instructions below)).

Running the lecture Jupyter notebook online on Binder

Binder

To run the lecture Jupyter notebook online on Binder:

  • Click on the "Launch binder" badge above (better to right click and then open in a new tab)
  • Once the notebook is ready, display a terminal by:
    • selecting on the top left File --> Open...
    • selecting on the top right of the newly displayed page New --> Terminal
  • You can follow along the notebook, and in the terminal you could type bash commands indicated in the notebook

How to setup your own coding environment at home ?

First part, depending on your OS

Linux

  • Install Visual Studio Code (prefer deb or repository installation)
  • Install Miniconda
  • Please indicate any problem during installation on Slack (after your very first message, please immediately hover on it and click on the chat buble to Reply in thread for all your messages to be in a single thread)

Mac

  • Open a terminal and type echo $0. If the output does not indicate bash this means you need to set your default shell as bash. You can do it by following the instructions here (see section "Using System Preferences" if you prefer using the graphical interface)
  • Install homebrew as indicated here
  • Update bash as described here
  • May be a good idea to restart ? Please let me know if you don't restart and have issues (so that i update these instructions)
  • Install Visual Studio Code
  • Install Miniconda
  • Please indicate any problem during installation on Slack (after your very first message, please immediately hover on it and click on the chat buble to Reply in thread for all your messages to be in a single thread)

Windows 10

  • Make sure you have installed the latest OS updates (Windows menu -> Check for Updates)
  • Install WSL2 as indicated here (you may also need info from here), then install the Ubuntu 20.04 app from the Microsoft store as indicated in the first link (it is recommended to also install the Windows Terminal app as suggested in that link)
  • Install Visual Studio Code
  • Start VS Code, and inside the program accept the suggestion of installing "VS Code Remote Pack" to use with WSL2 (for more information please see these instructions)
  • Start a terminal with WSL 2
    • (Preferred) If you installed the Windows Terminal App as indicated previously:
      • Start this app (search for "Windows Terminal" in the Windows search bar at the bottom left of your screen, and then click on the app)
      • By default you will see a Windows PowerShell, that IS NOT what we want. To open a Linux shell with the Ubuntu 20.04 OS you installed previously, click on the downward arrow head (⌄) next to the tab Title, and choose "Ubuntu 20.04": that IS what we want (see here to change the default profile to Ubuntu so that you don't always have to do this every time you start a terminal)
    • (Alternative) Start the Ubuntu 20.04 app by searching for "Ubuntu" in the Windows search bar at the bottom left of your screen and then clicking on the app
  • Install Miniconda making sure to follow the Linux instructions (so make sure sure to use the link i indicated and not using the instructions for Windows: your WSL 2 terminal is using a Linux kernel and you have to install Miniconda there !). For clarity these instructions are repeated below but may become outdated (the link just provided takes precedence over the instructions below):
    • Go to the terminal you opened in the previous step
    • Via the terminal navigate to the place where you downloaded the miniconda file. Keep in mind that any path to directory and files on a Windows C drive are accessible via WSL 2 at the path /mnt/c, so for example:
      • If your username on Windows is smartuser and you downloaded the file to your Windows Downloads directory, on the WSL 2 terminal you can navigate to that directory with: cd /mnt/c/Users/smartuser/Downloads
      • If for some reason your data is on a Windows drive with letter F and you downloaded the miniconda install script on your Dekstop, you will need to type in your WSL 2 terminal: cd /mnt/f/Users/smartuser/Desktop
      • Etc.
    • Make sure the miniconda install script is indeed in the directory you just navigate (at this time the script is called Miniconda3-latest-Linux-x86_64.sh but it can change later) :
      • ls Miniconda3-latest-Linux-x86_64.sh
      • If the previous command gives you an error, it means you are not in the right directory or you did not provided the correct filename to ls
    • Now follow the Linux instructions on the miniconda link above. For clarity these instructions which are few at this time are repeated here:
      • bash Miniconda3-latest-Linux-x86_64.sh
      • Accept all the default values and the license agreement
  • Please indicate any problem during installation on Slack (after your very first message, please immediately hover on it and click on the chat buble to Reply in thread for all your messages to be in a single thread)

Second part, OS independent (almost)

  • Now on the command line in a terminal (WSL 2 for Windows):
    • Update your local environment:
      source ~/.bashrc
    • Configure the conda-forge channel to be BEFORE any defaults in ~/.condarc:
      conda config --prepend channels conda-forge
    • Update your conda version to the latest:
      conda update -n base -c defaults conda
    • Install Jupyter notebook in the base environment (this is the "core" conda environment where I would advise not to install any other packages than essential ones and always create other environments for your projects):
      conda install -n base nb_conda_kernels jupyter
      • Note: when creating a new environment, cf example below, you will need to install the ipykernel module in each other conda python environment for Jupyter to find your environments automatically
    • Create a neuroimaging data science environment, for example as below: 
      conda create -n ni38 python=3.8
conda install -n ni38 numpy cython ipython scipy scikit-learn \
               pandas xlrd matplotlib seaborn lxml ipykernel \
               yapf sphinx numpydoc mypy pytest imageio pylint \
               nilearn heudiconv
    • FOR WINDOWS ONLY
      • Make sure you are in the base conda environment
        conda activate base
      • Generate Jupyter notebook configuration
        jupyter notebook --generate-config
      • Edit ~/.jupyter/jupyter_notebook_config.py (for example with VS Code) to make sure to have the following two configuration statements (no # in front) inside that file (asuming you have Chrome installed, otherwise change the path below to the location of your Internet browser executable):
        • c.NotebookApp.use_redirect_file = False
        • c.NotebookApp.browser = u'/mnt/c/Program\ Files\ \(x86\)/Google/Chrome/Application/chrome.exe %s'
  • For all OS, to start a new project, you could do something like:
    • Create a new project directory my_proj inside a parent directory my_projects 
      cd
mkdir my_projects
cd my_projects
mkdir my_proj
    • Start Visual Studio code, create a new file, save it inside my_proj as a Python file (i.e. with .py extension, e.g. analysis.py)
    • In a terminal (a linux terminal but not the one provided by VS Code to keep it free), start a Jupyter notebook after making sure you are in the default base conda environment: 
      conda activate base
jupyter notebook
    • A page should automatically open in your internet browser. If you cannot find it or it does not happen, read the output on the terminal and copy the URL indicated inside a tab of your internet browser
    • To start a new notebook, in the Jupyter page in your browser, click in the top right on New and then choose the conda environment you want (the python process which will interpret your commands is called a kernel)
  • For all OS, to run the examples from the course, you could do something like:
    • Create a directory NIDS then clone the python lectures inside it 
      cd
mkdir NIDS
cd NIDS
git clone https://github.com/NIDS2020-instructor/ml-task-fmri.git
    • Start Visual Studio code, click on File --> Open Folder and then choose preproc (inside NIDS), click OK
    • In a terminal (a linux terminal but not the one provided by VS Code to keep it free), start a Jupyter notebook after making sure you are in the default base conda environment: 
      cd
cd NIDS
cd glm
conda activate base
jupyter notebook
    • A page should automatically open in your internet browser. If you cannot find it or it does not happen, read the output on the terminal and copy the URL indicated inside a tab of your internet browser
    • To start a Python lecture notebook, click on its name in the list of files which is displayed in the Jupyter page of your browser (e.g. choose ml-task.ipynb)
    • Then choose the right conda environment by clicking on Kernel -> Change Kernel and selecting an environment with all the required packages

In case of any problem or if you have any question, please ask on Slack (after your very first message, please immediately hover on it and click on the chat buble to Reply in thread for all your messages to be in a single thread), thank you !