BrainNet

Setup

To run the project, you first need to set up the environment. You can do this using either pip or conda by following the steps below:

Using Conda

1. Create the Conda environment from the environment.yml file:

   conda env create -f environment.yml

2. Activate the Conda environment:

   conda activate brainnet

   Replace your_env_name with the name specified in your environment.yml file, or simply use the default environment name.

Using Pip

1. Create a virtual environment (optional but recommended):

   python -m venv env

2. Activate the virtual environment:

   • On macOS/Linux:

     source env/bin/activate

   • On Windows:

     .\env\Scripts\activate

3. Install the required packages from the requirements.txt file:

   pip install -r requirements.txt

Running the Project

After setting up the environment, you can run the project using the following files:

• Main Script: The primary executable file is located at:

  classification/NeuroGraph/GNNs_ADNI.ipynb
  

• Utilities: The utility functions required by the main script are located at:

  classification/NeuroGraph/utils.py
  

Open the Jupyter Notebook GNNs_ADNI.ipynb to start running the analysis.

Data

The edge data of ADNI is located in data/ADNI/fmri_edge. On GitHub, only cosine and pearson correlation data are provided. For more data, refer to the following link: Google Drive - Additional Data