# Imaging the neurodevelopmental trajectory of depression and anxiety disorders with HCP protocols

> **NIH NIH R56** · MASSACHUSETTS GENERAL HOSPITAL · 2020 · $1,225,770

## Abstract

Project summary: The main objectives of this project are to perform longitudinal collection of clinical,
behavioral, and neuroimaging data from a cohort of adolescents with depression and anxiety disorders, as well
as healthy controls; and to develop a set of analytical tools that can be used to study the developmental
trajectory of brain structure and function in this population. The project builds on the ongoing collaboration of
our team in a Connectomes Related to Human Disease U01 project, the Boston Adolescent Neuroimaging of
Depression and Anxiety (BANDA) study, where we have been performing extensive clinical characterization
and MRI scanning with Human Connectome Project (HCP) protocols on adolescents with depression and/or
anxiety disorders and healthy controls. These baseline data (current total: N=170; final target: N=225) are set
to become available publicly through the HCP database. Here we propose to collect longitudinal data on this
unique, thoroughly characterized cohort. Following up on these subjects will allow us to investigate the
complex relationship between longitudinal changes in neural circuitry and the onset, persistence, or recurrence
of depression and anxiety disorders. We will tackle this by bringing together an investigative team with strong
expertise in adolescent mood disorders and in neuroimaging data analysis. The MPIs have extensive
experience in developing publicly available software tools for the analysis of brain connections from diffusion
MRI (Yendiki) and functional MRI (Whitfield-Gabrieli). In this project, we propose to develop robust, automated
tools for segmenting deep-brain structures and white-matter pathways that are of interest in psychiatric
disorders. This development will build on our prior work in unbiased methods for longitudinal morphometric and
tractography analyses. We will leverage the proposed longitudinal dataset and tools for accurate delineation of
individual anatomy to perform a number of novel analyses that will go beyond conventional group-wise
comparisons. Specifically, we will focus on analyses that allow us to predict clinical outcomes in individual
subjects based on their neural circuitry. We will use machine-learning techniques to map the normative
developmental trajectory of brain structure and function in healthy adolescents, including our controls and
those from the development HCP. We will then investigate how and when the trajectories of individual
adolescents with depression and/or anxiety disorders deviate from this normative trajectory. The longitudinal
data set that we will collect and the software tools that we will develop will be shared with the research
community. Our analysis methods will be applicable beyond this cohort, and could be used to study disease
mechanisms and predict outcomes in a wide range of brain-related disorders across the human lifespan.

## Key facts

- **NIH application ID:** 10057408
- **Project number:** 1R56MH121426-01
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Susan Whitfield-Gabrieli
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,225,770
- **Award type:** 1
- **Project period:** 2020-01-01 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10057408

## Citation

> US National Institutes of Health, RePORTER application 10057408, Imaging the neurodevelopmental trajectory of depression and anxiety disorders with HCP protocols (1R56MH121426-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10057408. Licensed CC0.

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