A Theta Gamma Analysis Repository hosted at the
Genzel Lab
This repository is a culmination of all the techniques and methods used to discover the properties of the Theta-Gamma code. Currently, we're working on a combination of techniques used in two papers (Lopes-dos-Santos et al., 2018 & Zhang et al., 2019). An ongoing project at the Donders Institute for Brain Cognition and Behaviour, Radboud Univeristy, this project will periodically go through updates as the analysis is being refined, stay tuned for more developments.
Most of the analysis is carried out within Python environments, tutorial notebooks can be loaded independently using Google Colab or locally,except for Tutorial 4. The following steps will guide you through the installation process
- For Windows, it's recommended to download and install Python directly from the official Python website.
Make sure to check the "Add Python to PATH" option during installation so that you can run Python from the command prompt.
- For macOS (using Homebrew):
brew install python
python --version-
Download the repository from the github repo web address
-
OR Clone it using the terminal.
Navigate to the directory where you want to clone the repository:
cd /path/to/your/desired/directorygit clone https://github.com/AbdelRayan/ThetaGammaAnalysis.git
cd ThetaGammaAnalysis- Through the
requirements.txtfile
pip install -r requirements.txt- OR Through the
setup.pyfile
python setup.py installPlease go through Tutorials 1 through 4 on how the code is implemented and patched together. This section will be further detailed with more usage scenarios and implementations
- 1. Lopes-dos-Santos, V., van de Ven, G. M., Morley, A., Trouche, S., Campo-Urriza, N., & Dupret, D. (2018). Parsing hippocampal theta oscillations by nested spectral components during spatial exploration and memory-guided behavior. Neuron, 100(4). doi:10.1016/j.neuron.2018.09.031
- 2. Zhang, L., Lee, J., Rozell, C., & Singer, A. C. (2019). Sub-second dynamics of theta-gamma coupling in hippocampal CA1. eLife, 8. doi:10.7554/elife.44320