Code for omission frontiers
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
FieldTrip
MNE-Python
README.md

README.md

Omission Frontiers

Reference

If you use the data or the analysis pipeline, please refer to:
Andersen, L.M., 2018. Group Analysis in MNE-Python of Evoked Responses from a Tactile Stimulation Paradigm: A Pipeline for Reproducibility at Every Step of Processing, Going from Individual Sensor Space Representations to an across-Group Source Space Representation. Front. Neurosci. 12. https://doi.org/10.3389/fnins.2018.00006 or to: Andersen, L. M. Group Analysis in FieldTrip of Time-Frequency Responses: A Pipeline for Reproducibility at Every Step of Processing, Going From Individual Sensor Space Representations to an Across-Group Source Space Representation. Front. Neurosci. 12, (2018). https://10.3389/fnins.2018.00261

Synopsis

This project is intended for facilitating group-level analysis in magnetoencephalography (MEG) using the open toolboxes MNE-Python and FieldTrip. The code is accompanied by an article for each of the toolboxes in an upcoming Frontiers Special Issue.
Intended to be compatible with both Python 2.7 and Python 3.x, but hasn't been extensively tested for Python 3. Testing was done with 0.15 of MNE-Python

For instructions and context of the code please refer to the article called: Group analysis in MNE-Python of evoked responses from a tactile stimulation paradigm: a pipeline for reproducibility at every step of processing, going from individual sensor space representations to an across-group source space representation
The DOI is: 10.3389/fnins.2018.00006

A similar article for the FieldTrip pipeline is called: Group Analysis in FieldTrip of Time-Frequency Responses: A Pipeline for Reproducibility at Every Step of Processing, Going From Individual Sensor Space Representations to an Across-Group Source Space Representation The DOI is: 10.3389/fnins.2018.00261

Motivation

Most tutorials on MEG analysis are at the single-subject level. This is an attempt at remedying that situation by providing a comphehensive collection of functions that can all be accessed from a single pipeline script (MNE-Python) or several pipeline scripts (FieldTrip)

Installation

No installation is required. Simply download the scripts and get the data at the following DOI:10.5281/zenodo.998518 or URL:https://zenodo.org/record/998518

API Reference

To be added

Tests

To be added

Contributors

Marijn van Vliet, added Python 3 support
git: wmvanvliet

Licence

CC BY 4.0