1 Concordia University, School of Health, PERFORM Centre, Montréal, Quebec, Canada.
2 Concordia University, Multimodal Functional Imaging Laboratory, Department of Physics, Montréal, Quebec, Canada.
3 Montreal Heart Institute, EPIC Center, Montréal, Quebec, Canada.
4 McGill University, Montreal Neurological Institute, Montreal, Quebec, Canada.
5 McGill University, Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, Neurology and Neurosurgery Department, Montreal, Quebec, Canada.
6 Institut du Cerveau ICM, Centre MEG-EEG, Paris, France.
7 Inserm, CNRS, Centre de Recherche en Neurosciences de Lyon, Lyon, France.
8 Independent Research Engineer, Grenoble, France.
9 McGill University, Montreal Neurological Institute, McConnell Brain Imaging Centre, Montreal, Quebec, Canada.
10 Université de Montréal, Department of Medicine, Montréal, Quebec, Canada.
11 École de Technologie Supérieure, Electrical Engineering Department, Montréal,

Significance: Understanding the brain's complex functions requires multimodal approaches that combine data from various neuroimaging techniques. Functional near-infrared spectroscopy (fNIRS) offers valuable insights into hemodynamic responses, complementing other modalities such as electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance imaging. However, there is a lack of comprehensive and accessible toolboxes able to integrate fNIRS advanced analyses with other modalities. NIRSTORM addresses this gap by offering a unified platform for multimodal neuroimaging analysis.

Aim: NIRSTORM aims to provide a user-friendly and comprehensive environment for multimodal analysis while supporting the entire fNIRS analysis pipeline, from experiment planning to the reconstruction of hemodynamic fluctuations on the cortex.

Approach: Developed in MATLAB^®, NIRSTORM operates as a Brainstorm plugin, enhancing Brainstorm's capabilities for analyzing fNIRS data. Brainstorm is a widely used, GUI-based software originally designed for statistical analysis and source imaging of EEG and MEG data.

Results: NIRSTORM supports conventional fNIRS preprocessing and statistical analyses while introducing new advanced features such as optimal montage for planning optode placement and maximum entropy on the mean (MEM) for reconstructing hemodynamic fluctuations on the cortical surface.

Conclusion: As an open-access and user-friendly plugin, NIRSTORM extends Brainstorm's functionality to fNIRS, bridging the gap between EEG/MEG and hemodynamic analyses.