Welcome to the IEEG_Pipelines Documentation

This is the main page of the IEEG_Pipelines documentation. Here you will find the table of contents and links to other important resources.

API Reference:

• ieeg
• MATLAB Documentation
• Examples
• External Resources

Developer Information

• Contributing to IEEG_Pipelines
• License

Useful Links

• IEEG_Pipelines @ GitHub
• Issue Tracker

IEEG_Pipelines

A repo of current preprocessing pipelines for the Cogan Lab

Documentation

Lab Wiki

Pipeline Functionality

Installation

MATLAB

1. Install MATLAB

2. Clone this repository into your userpath (Documents/MATLAB by default)

3. Run commands:

   path = fullfile(userpath, 'IEEG_Pipelines', 'MATLAB');
   addpath(genpath(path));
   

Python

Version 3.10 supported

Conda

1. Install Anaconda

2. Clone this repository

3. Open a terminal and cd into this repo’s Python directory

4. Run this command:

   conda env create -f envs/environment.yml
   

5. When it is finished installing run conda activate preprocess to activate the environment

Pip

1. Install Python

2. Clone this repository

3. Open a terminal and cd into this repo’s Python directory

4. Run:

   python -m venv <PATH TO VENV>/preprocess
   python -m pip install -r envs/requirements.txt -e <PATH TO VENV>/preprocess
   

5. When it is finished installing run source activate <PATH TO VENV>/preprocess to activate the environment

Usage

MATLAB (INCOMPLETE)

1. Load .dat file using convert_OpenE_rec2mat.m

2. Create the ieeg data structure from the ieegStructClass.m

3. TBD

Python (INCOMPLETE)

1. Load BIDS files from BIDS directory using pybids

   from bids import BIDSLayout
   import ieeg
   layout = BIDSLayout(BIDS_root)
   data = ieeg.io.raw_from_layout(layout)
   

2. Perform line noise filtering

3. Check Spectrograms

4. Plot the high gamma responses

5. Run the cluster correction and permutation test

Indices and Tables

• Index

• Module Index

• Search Page

• MATLAB Module Index

Thank you for using IEEG_Pipelines!