# Using Neuroimaging Markers to Understand Risk Factors and Consequences of Cannabis on Brain Structure and Function

> **NIH NIH K02** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $128,304

## Abstract

Project Summary
This application for an Independent Scientist Award (K02) requests support to develop a program of
brain-based and behavioral research on substance use disorders (SUD), especially cannabis use disorder
(CUD). My laboratory is supported in part by a funded R01 (DA039135) that seeks to understand the effects of
medical marijuana on the brain, cognition, and escalation to CUD. In the next phase of my career, I propose to
learn enhanced analytical techniques (e.g. machine learning and predictive modeling) that can capitalize on
newly-available, large, longitudinal datasets that can answer fundamental questions about the development of
SUD that cannot be answered in small populations. In addition, I propose a secondary training goal of gaining
expertise in developmental neuroscience, to broaden the populations I can study to include children and
adolescents at-risk for SUD. Together, these skillsets will allow me to greatly expand the types of questions I
can ask, by allowing me to answer questions about SUD using both large observational data-sets, and also
targeted experimental manipulations (such as my R01). My goal at the end of this K02 to have the tools to not
only use big data to better understand risk factors and consequences of addiction in large samples, but also to
use this knowledge to inform future experimental studies and clinical trials that I can conduct in my lab.
 The scientific focus of this application is a research project, using the publicly-available Adolescent
Brain and Cognitive Development (ABCD) dataset of 11,877 children scanned longitudinally, to understand
how trajectories of change in impulsivity associate with brain-based abnormalities and SUD risk. The aims for
the ABCD analysis project are to (1) define the factorial structure of impulsivity in the ABCD dataset as it may
portend SUD risk (using a confirmatory factor model which will be applied to the array of behavioral tasks, self-
report measures, and parent reports), (2) determine structural and functional brain measures that correlate with
impulsivity, and (3) examine how longitudinal changes in brain signatures of impulsivity are associated with risk
for SUD. To accomplish these aims, I will participate in courses and train with collaborators with expertise in
developmental neuroscience and in statistical analyses of big data. The skills I learn in the K02 period will be
used not only to query the ABCD dataset, but also to enhance the sophistication of neuroimaging analyses of
my R01 data and any future data collected in my laboratory. This training will enhance my laboratory by
significantly expanding the questions I can address, improving my analytic skills, furthering my ability to
collaborate, and providing a foundation for mentoring junior scientists. In the absence of K02 support, I will
need to cover my salary through teaching and administrative work, which would detract from my research,
training, and mentoring activities. This K02 award w...

## Key facts

- **NIH application ID:** 10468167
- **Project number:** 5K02DA052684-02
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Jodi Gilman
- **Activity code:** K02 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $128,304
- **Award type:** 5
- **Project period:** 2021-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10468167

## Citation

> US National Institutes of Health, RePORTER application 10468167, Using Neuroimaging Markers to Understand Risk Factors and Consequences of Cannabis on Brain Structure and Function (5K02DA052684-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10468167. Licensed CC0.

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