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      NIRSTORM: a Brainstorm extension dedicated to functional near-infrared spectroscopy data analysis, advanced 3D reconstructions, and optimal probe design

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          Abstract.

          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.

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          Most cited references112

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Is Open Access

            FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

            This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.
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              Cortical surface-based analysis. I. Segmentation and surface reconstruction.

              Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.

                Author and article information

                Contributors
                Journal
                Neurophotonics
                Neurophotonics
                NEUROW
                NPh
                Neurophotonics
                Society of Photo-Optical Instrumentation Engineers
                2329-423X
                2329-4248
                15 May 2025
                April 2025
                15 May 2025
                : 12
                : 2
                : 025011
                Affiliations
                [a ]Concordia University , School of Health, PERFORM Centre, Montréal, Quebec, Canada
                [b ]Concordia University , Multimodal Functional Imaging Laboratory, Department of Physics, Montréal, Quebec, Canada
                [c ]Montreal Heart Institute , EPIC Center, Montréal, Quebec, Canada
                [d ]McGill University , Montreal Neurological Institute, Montreal, Quebec, Canada
                [e ]McGill University , Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, Neurology and Neurosurgery Department, Montreal, Quebec, Canada
                [f ]Institut du Cerveau ICM , Centre MEG-EEG, Paris, France
                [g ]Inserm , CNRS, Centre de Recherche en Neurosciences de Lyon, Lyon, France
                [h ]Independent Research Engineer , Grenoble, France
                [i ]McGill University , Montreal Neurological Institute, McConnell Brain Imaging Centre, Montreal, Quebec, Canada
                [j ]Université de Montréal , Department of Medicine, Montréal, Quebec, Canada
                [k ]École de Technologie Supérieure , Electrical Engineering Department, Montréal, Quebec, Canada
                [l ]Sorbonne Université , CNRS, Inserm, Laboratoire d’Imagerie Biomédicale, LIB, CNRS, INSERM, Paris, France
                Author notes
                [* ]Address all correspondence to Édouard Delaire, edouard.delaire@ 123456concordia.ca ; Christophe Grova, christophe.grova@ 123456concordia.ca
                Author information
                https://orcid.org/0000-0003-1421-1071
                https://orcid.org/0000-0002-8557-2934
                https://orcid.org/0000-0001-5726-7126
                https://orcid.org/0000-0003-2775-9968
                Article
                NPh-24077GR 24077GR
                10.1117/1.NPh.12.2.025011
                12081164
                40375973
                3cfa7912-c620-424b-9cc7-a27c3ddd5328
                © 2025 The Authors

                Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

                History
                : 5 September 2024
                : 12 March 2025
                : 2 April 2025
                Page count
                Figures: 9, Tables: 0, References: 114, Pages: 32
                Funding
                Funded by: Natural Sciences and Engineering Research Council of Canada Discovery
                Funded by: Canadian Institutes of Health Research
                Award ID: PJT-159448
                Funded by: Fonds de Recherche du Québec—Nature et technologies (FRQNT) Research team
                Funded by: NSERC Research Tools and Instrumentation Program and the Canadian Foundation for Innovation
                Funded by: NIH grant for USC: “Signal & Image Processing Institute, University of Southern California, Los Angeles, CA USA”
                This study was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery grant), a grant from the Canadian Institutes of Health Research (CIHR) (Grant No. PJT-159448), and the Fonds de Recherche du Québec—Nature et Technologies (FRQNT), research team grants held by CG. fNIRS equipment was acquired using grants from NSERC Research Tools and Instrumentation Program and the Canadian Foundation for Innovation (CG). From 2018 to 2023, FT was supported by the US National Institutes of Health, through the University of Southern California: “Signal & Image Processing Institute, University of Southern California, Los Angeles, California, USA.”
                Categories
                Research Papers
                Paper
                Custom metadata
                Delaire et al.: NIRSTORM: a Brainstorm extension dedicated to functional…

                toolbox,functional near-infrared spectroscopy,conventional functional near-infrared spectroscopy analysis,near-infrared optical tomography,optimal montage,advanced multimodal integration

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