# Neuroimaging Core (D)

> **NIH NIH P50** · PRINCETON UNIVERSITY · 2024 · $403,247

## Abstract

CORE D – Neuroimaging Core
Functional MRI (fMRI) and advanced multivariate analysis techniques are essential methods for achieving the
aims of this Conte Center proposal. The overarching aim of Core D (Neuroimaging Core) is to support,
optimize and harmonize neuroimaging data collection across the Princeton and Rutgers neuroimaging sites
in order to maximize data quality and to assist with the implementation of advanced imaging analyses to
facilitate hypothesis testing for Projects 1-3. Each of these projects employ fMRI data collection in conjunction
with computational modelling of behavioral tasks (supported by Core C) to determine the neural substrates of
latent cause inference and their relation to key features of mental health.
The Core's specific aims are as follows: Aim 1) Optimize and harmonize MRI sequences and data acquisition
across sites, including optimization of multiband multiecho sequences to improve data quality in key brain
regions involved in latent cause inference that normally suffer from signal dropout; Aim 2) Implement
optimized data preprocessing pipelines with an emphasis on using reproducible, standardized methods;
Aim 3) Implement advanced data analysis methods to meet the aims of Projects 1-3, including multivariate
predictive modeling, representational similarity analyses, advanced functional connectivity analyses, and real-
time fMRI analysis for neurofeedback; Aim 4) Provide education to Center members regarding MRI
methodologies including advanced analytic techniques; and Aim 5) Share neuroimaging data and processing
pipelines in keeping with the Center's open science objectives.
Core D will utilize the state-of-the-art research dedicated neuroimaging facilities housed in the Princeton
University Scully Center for the Neuroscience of Mind and Behavior and in the Rutgers University Center for
Advanced Human Brain Imaging Research (CAHBIR). Harmonization across the two sites will be aided by the
use of the same scanners (3T Siemens Prisma scanners) and the already existing sharing of quality control and
technical expertise across the two neuroimaging facilities. Analysis and educational aims are facilitated by the
expertise of the Core Leads, who have led development of pipelines for individualized functional connectivity
analysis and software packages such as the BrainIAK toolkit that provides the basis for multivoxel pattern
analysis and representational similarity analyses that will be used in Projects 1-3. Existing data management
and high-performance computing infrastructure across the two sites provide the basis for archiving and
analysis of the Center's data. In coordination with Core A, a strong framework for communication with Project
and Core Leads will ensure that the scanning and analytic needs of Center Projects are met in order to fulfill
the goals of the Center.

## Key facts

- **NIH application ID:** 10862344
- **Project number:** 1P50MH136296-01
- **Recipient organization:** PRINCETON UNIVERSITY
- **Principal Investigator:** DAVID HAROLD ZALD
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $403,247
- **Award type:** 1
- **Project period:** 2024-08-12 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10862344

## Citation

> US National Institutes of Health, RePORTER application 10862344, Neuroimaging Core (D) (1P50MH136296-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10862344. Licensed CC0.

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