# BRAIN INITIATIVE RESOURCE: DEVELOPMENT OF A HUMAN NEUROELECTROMAGNETIC DATA ARCHIVE AND TOOLS RESOURCE (NEMAR)

> **NIH NIH R24** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2022 · $881,737

## Abstract

To take advantage of recent and ongoing advances in intensive and large-scale computational methods,
and to preserve the scientific data created by publicly funded research projects, data archives must be
created as well as standards for specifying, identifying, and annotating deposited data. The value of and
interest in such archives among researchers can be greatly increased by adding to them an active
computational capability and framework of analysis and search tools that support further analysis as well
as larger scale meta-analysis and large scale data mining. The OpenNeuro.org archive, begun as a
repository for functional magnetic resonance imaging (fMRI) data, is such an archive. We propose to build
a gateway to OpenNeuro for human electrophysiology data (EEG and MEG, as well as intracranial data
recorded from clinical patients to plan brain surgeries or other therapies) – herein we refer to these
modalities as neuroelectromagnetic (NEM) data. The Neuroelectromagnetic Data Archive and Tools
Resource (NEMAR) at the San Diego Supercomputer Center will act as a gateway to OpenNeuro for NEM
data research. Such data uploaded to NEMAR at SDSC will be deposited in the OpenNeuro archive. Still-
private NEM data in OpenNeuro will, on user request, be copied to the NEMAR gateway for further user
processing using the XSEDE high-performance resources at SDSC in conjunction with The Neuroscience
Gateway (nsgportal.org), a freely available and easy to use portal to use of high-performance computing
resources for neuroscience research. Publicly available OpenNeuro NEM data will be able to be analyzed
by running verified analysis applications on the OpenNeuro system. In this project we will build an
application to evaluate the quality of uploaded NEM data, and another to visualize the data, for EEG and
MEG at both the scalp and brain source levels, including time-domain and frequency-domain dynamics
time locked to sets of experimental events learned from the BIDS- and HED-formatted data annotations.
The NEMAR gateway will take a major step toward applying machine learning methods to a large store
of carefully collected and stored human electrophysiologic brain data to spur new developments in basic
and clinical brain research.

## Key facts

- **NIH application ID:** 10475072
- **Project number:** 5R24MH120037-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Arnaud Delorme
- **Activity code:** R24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $881,737
- **Award type:** 5
- **Project period:** 2019-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10475072

## Citation

> US National Institutes of Health, RePORTER application 10475072, BRAIN INITIATIVE RESOURCE: DEVELOPMENT OF A HUMAN NEUROELECTROMAGNETIC DATA ARCHIVE AND TOOLS RESOURCE (NEMAR) (5R24MH120037-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10475072. Licensed CC0.

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