# BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging

> **NIH NIH R01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2020 · $633,469

## Abstract

Project Summary
Electrophysiological recordings in humans and animals play an essential role in developing an understanding of
the human brain. Signal recording technology spans the entire scale from invasive microelectrode single-unit
recordings, through mesoscale macroelectrode measures of local field potentials, to whole-brain monitoring
through measurement of scalp potentials (EEG) and extracranial magnetic fields (MEG). Analysis of these data
presents a host of challenges, from low level noise removal and artifact rejection to sophisticated spatio-temporal
modeling and statistical inference. The multidisciplinary neuroscience research community has an ongoing need
for validated and documented open-source software to perform this analysis and to facilitate reproducible and
large-scale research involving electrophysiological data. This proposal describes our plans to continue to develop
and support Brainstorm, open-source software that meets this need. Brainstorm is a Matlab/Java multi-platform
(Linux, MacOS, Windows) software package for analysis and visualization of electrophysiological data. The
software is extensively documented through a series of detailed tutorials and actively supported through a user
forum and a mailing list. Over the past 8 years we have registered 16,000 distinct users, provided hands on
instruction to 1,200 trainees, and the software has been used and cited in ~600 journal papers. Brainstorm
includes tools for importing MEG/EEG, intracranial EEG, animal electrophysiology, and near-infrared
spectroscopy (NIRS) data from multiple vendors, extensive interactive features for data preprocessing, selection
and visualization, coregistration to volume and surface MRIs and atlases, forward and inverse mapping of
cortical current density, time-series and connectivity analysis, and a range of statistical tools. Data can be
analyzed through a graphical interface or through scripted pipelines. The current proposal represents a plan to
extend Brainstorm in a manner that leverages the unique features of our software and addresses important needs
for large-scale data analysis. In this project we will continue to extend and support our software through the
following three specific aims: (i) we will harness recent developments in distributed and shared data and high
performance computing resources, together with standardization of data organization, to facilitate large-scale,
reproducible analysis of electrophysiological data. (ii) We will also address the need for improved modeling
resulting from the increasing use of both invasive recordings and direct brain stimulation through development
of new modeling software for accurate computation of the intracranial electromagnetic fields produced by brain
stimulation and neuronal activation. (iii) Finally, we will continue to add new functionality and to support the
software through in-person training, online forums, documentation and other resources.

## Key facts

- **NIH application ID:** 9894648
- **Project number:** 5R01EB026299-03
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Richard M Leahy
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $633,469
- **Award type:** 5
- **Project period:** 2018-06-15 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9894648

## Citation

> US National Institutes of Health, RePORTER application 9894648, BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging (5R01EB026299-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9894648. Licensed CC0.

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