NIRSTORM

Current features include:

• classical within-subject analysis comprising motion correction, MBLL, and window-averaging.
• statistical analysis using GLM
• optimal montages that optimize the sensitivity to a given cortical region of interest
• source reconstruction (cMEM, MNE)
• precomputed fluence template based on Colin27

Main developers:

• Edouard Delaire, PERFORM Centre and Physics dpt., Concordia University, Montreal, Canada
• Thomas Vincent, EPIC Center, Montreal Heart Institute, Montreal, Canada
• Zhengchen Cai, PERFORM Centre, and Physics dpt., Concordia University, Montreal, Canada
• Robert Stojan, Sportpsychology, Chemnitz University of Technology, Germany
• Alexis Machado, Multimodal Functional Imaging Lab., Biomedical Engineering Dpt, McGill University, Montreal, Canada

Collaborators:

• Amanda Spilkin, PERFORM Centre and Physics dpt., Concordia University, Montreal, Canada
• Jean-Marc Lina, Electrical Engineering Dpt, Ecole de Technologie Supérieure, Montréal, Canada
• Christophe Grova, PERFORM Centre and physics dpt., Concordia University, Montreal, Canada
• Louis Bherer, EPIC Center, Montreal Heart Institute, Montreal, Canada

Usage

The primary documentation is available on the nirstorm GitHub project wiki.

Installation

Nirstorm is available in two forms: an open-source Matlab plugin for Brainstorm (Matlab license required) and is included in the Brainstorm standalone version (Java executable)

Matlab version can be installed using the Brainstorm plugin system :

This required the Brainstorm version 3.210414 (14 April 2021) or higher. To use nirstorm with a previous version of Brainstorm, refer to this tutorial https://github.com/Nirstorm/nirstorm/wiki/Installation (Note: We recommend you to always use the latest version of Brainstorm)

A standalone version is directly included in Brainstorm standalone version. Follow Brainstorm tutorials for more information: https://neuroimage.usc.edu/brainstorm/Installation