# BRAIN Initiative: Assessing development of event-related cortical network dynamics

> **NIH NIH RF1** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $1,114,819

## Abstract

Project Summary
The Child Mind Institute’s Healthy Brain Network (HBN) is an ongoing initiative focused on creating and
sharing a biobank of brain and behavioral data now being collected from 10,000 New York City area children
and adolescents (ages 5-21). In response to RFA-MH-120-20 (‘Integration and analysis of BRAIN Initiative
data’), we will collect their high-density EEG and continuous eye tracking data, recorded from now over 3,000
young participants while they watch movies and rest, plus participant MR head images, to create a
developmental EEG and eye tracking data and analysis resource within the BRAIN Initiative-funded NEMAR
portal (NEMAR.org) to the OpenNeuro human neuroimaging resource (OpenNeuro.org). We will store the data
in accord with the latest advances in the Brain Imaging Data Standard (BIDS), including innovative
co-registration of eye-tracking information and EEG, extraction of anonymized Leadfield matrices for advanced
participant-based source localization, and Hierarchical Event Descriptor (HED) annotation of movie and eye
tracking events in the data, to enable sophisticated exploratory and model-based analyses by any user of the
Neuroscience Gateway (nsgportal.org), which offers processing of complex tasks on the U.S. XSEDE
computer network (XSEDE.org) for users of standard neuroscience software. We propose to build on the large
existing and readily extensible set of tools for analysis, modeling, and visualization of human EEG data in the
world leading EEGLAB software environment for electrophysiological signal processing we develop and
maintain (5R01-NS047293-15) (sccn.ucsd.edu/eeglab), to process the large corpus of innovative EEG and
synchronous eye tracking data recorded during movie viewing by the HBN project. We will then apply
source-resolved event-related analysis models to cortical EEG network dynamics associated with movie
watching, will model their changes across development, and will compare the time course of these changes
with changes in eye gaze patterns at the same age levels. We will use cortical source-resolved, event-related
functional EEG connectivity measures implemented in the Source Information Flow Toolbox (SIFT) to model
event-related EEG dynamics of individual participants, and will apply advanced hierarchical Bayes-based
methods and statistical assessment to perform statistical testing on subject group models. We will study the
development of event-related cortical information flow during movie watching and rest across the large HBN
developmental (5-21 years) sample, and compare it to the developmental trajectory of changes in eye gaze
patterns during movie viewing.

## Key facts

- **NIH application ID:** 10190670
- **Project number:** 1RF1MH125934-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Arnaud Delorme
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,114,819
- **Award type:** 1
- **Project period:** 2021-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10190670

## Citation

> US National Institutes of Health, RePORTER application 10190670, BRAIN Initiative: Assessing development of event-related cortical network dynamics (1RF1MH125934-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10190670. Licensed CC0.

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