# NeuroMAP Phase II - Data Management and Statistics Core

> **NIH NIH P20** · LAUREATE INSTITUTE FOR BRAIN RESEARCH · 2024 · $163,046

## Abstract

PROJECT SUMMARY: Data Management and Statistics Core
A 3-year project for a Research Project Leader (RPL) to conduct experimental human subjects research with
psychiatric target populations and to obtain pilot data for an R-level grant can be challenging from a design,
data management and processing, and statistical analysis perspective. The Data Management and Statistics
(DMS) Core will ensure the highest rigor of study design, the implementation of community-standard data
management and processing protocols, and the application of cutting-edge data science algorithms that
maximize out-of-sample prediction performance and power for assessing mechanisms of action. The Core will
work with RPLs and pilot project investigators to facilitate identifying and validating disease-modifying
processes (DMPs) that are relevant for mood and anxiety disorders. This will greatly enhance the utility of the
research produced by RPLs for use in formulating aims and developing hypotheses based on these
preliminary data and for designing future studies, thereby making R01-level applications more likely to succeed
as well as being more competitive and fundable. Services provided by this Core consist of: (1) consultations
with expert data scientists who will work with investigators to develop and instantiate an operating environment
that optimizes data use and analytics; and (2) procedures and programs developed by this Core to
accommodate users' stimulus presentation, data management and statistical needs. The data management
component will be instrumental in guaranteeing that data are acquired and processed reliably and efficiently
using our scalable data management infrastructure. Services will begin at study setup and include
implementation and configuration of behavioral paradigms, pipelines to convert raw data into standard (e.g.,
Brain Imaging Data Structure: BIDS) format, periodic auditing and sharing as needed. This Core will provide
standard pipelines to extract common data elements and quality metrics and to facilitate access and usage of
the institute's computing infrastructure. The statistics component of the Core will focus on developing study
designs and analytic procedures applicable to assessing unbiased effects and predictive performance of DMPs
(e.g., threat sensitivity, avoidance during aversive interoception, repetitive negative thinking) on mental health
outcomes. As these DMPs will be examined on several levels of analysis (symptoms, behavior, physiology,
circuits, and molecules), study designs and analyses will need to integrate complex multi-method associations
and will need to account for potential biases in associations, e.g., due to selection, measurement error, and/or
confounding. This Core will focus on multilevel models, causal inference and machine learning prediction that
account for sources of variation (e.g., nested data) and confounding (e.g., confounding bias) while providing
maximal explanatory and out-of-sample prediction perfor...

## Key facts

- **NIH application ID:** 10894851
- **Project number:** 5P20GM121312-07
- **Recipient organization:** LAUREATE INSTITUTE FOR BRAIN RESEARCH
- **Principal Investigator:** Wesley Kurt Thompson
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $163,046
- **Award type:** 5
- **Project period:** 2017-09-15 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10894851

## Citation

> US National Institutes of Health, RePORTER application 10894851, NeuroMAP Phase II - Data Management and Statistics Core (5P20GM121312-07). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10894851. Licensed CC0.

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