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

> **NIH NIH R01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2023 · $372,552

## Abstract

PROJECT SUMMARY
We are requesting a supplement to R01 EB026299 (Brainstorm: Highly Extensible Software for Advanced
Electrophysiology and MEG/EEG Imaging) under NOT-AG-22-025 to extend our Brainstorm software to develop
an open-source Alzheimer's Disease (AD) analytical toolkit (AD Toolbox). The new software features will be
designed to promote the use of multimodal electrophysiology (in conjunction with other imaging and data
collection methods) in staging, understanding, and treating Alzheimer's Disease. R01 EB026299 provides
support for developing Brainstorm, a Matlab/Java multi-platform (Linux, macOS, Windows) software environment
for analysis and visualization of electrophysiological (e-phys) data. This open-source software plays an
increasingly enabling role in clinical and cognitive neuroscience research as reflected in the following: 2,300
published articles reporting analyses using Brainstorm, >36,000 user accounts, 18,000 downloads/month,
45,000 posts on the online forum, and 2,500 researchers who have attended in-person or online Brainstorm
training events. The research proposed here is fully within the scope of the current grant, as summarized in the
Specific Aims of the competing renewal for R01 EB026299: “Under this renewal, we will continue to provide
support, documentation, and training to Brainstorm users while exploring and developing innovative
methodologies, computational tools, and integrated software-solutions relevant to current analysis and research
involving e-phys data.” The neuropathology of AD is characterized by staged spreading of neuronal cell loss,
neurofibrillary tangles, and plaques in multiple cortical and subcortical brain regions. The build-up of tau protein
has now become another hallmark of AD pathophysiology. The development of PET ligands for both tau and -
amyloid has resulted in increasingly sensitive tests for early-stage and preclinical AD. However, PET studies are
expensive and do not shed direct light on the impact of the build-up of these proteins, or AD in general, on
neuronal function. We will leverage current and planned computational tools within Brainstorm to develop
methodologies for the use of EEG/MEG data in the early detection of AD and in understanding its
neurophysiological impact on behavior and cognition as the disease progresses. We will use the longitudinal
PREVENT-AD database (which includes MRI, -amyloid and tau PET, and MEG studies, plus medical records
and extensive cognitive testing) to develop and test methodology and software. The AD Toolbox developed
under this supplement will include the following two major components: (i) Computational methods for data
processing, statistical analysis, and machine learning (ML) at the whole-brain level that will allow users to extract
spatio-temporal features from MEG and EEG data and study their relationship with spatial protein maps of beta-
amyloid and tau (PET), as well as relevant structural measures, such as cortical thickness and re...

## Key facts

- **NIH application ID:** 10716047
- **Project number:** 3R01EB026299-06S1
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Richard M Leahy
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $372,552
- **Award type:** 3
- **Project period:** 2018-06-15 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10716047

## Citation

> US National Institutes of Health, RePORTER application 10716047, BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging (3R01EB026299-06S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10716047. Licensed CC0.

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