coganlab / IEEG_Pipelines

A repo of current preprocessing methods for the Cogan Lab

Home Page:https://ieeg-pipelines.readthedocs.io/en/latest/

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IEEG_Pipelines

A repo of current preprocessing pipelines for the Cogan Lab

Brain

Documentation

Documentation Status

Lab Wiki

Pipeline Functionality

Python (3.10) on Windows/Linux

MATLAB latest

codecov

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

About

A repo of current preprocessing methods for the Cogan Lab

https://ieeg-pipelines.readthedocs.io/en/latest/

License:MIT License


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