# Connectome Coordination Facility II

> **NIH NIH R24** · WASHINGTON UNIVERSITY · 2020 · $1,304,218

## Abstract

Project Summary
This project will continue operation of the Connectome Coordination Facility (CCF) by capitalizing on the
successes of the Human Connectome Project (HCP), which acquired, analyzed, and shared multimodal
neuroimaging data and behavioral data on a large population of healthy adults. Major advances by the HCP
include (i) the establishment of data acquisition protocols that yield high quality data across multiple modalities;
(ii) the implementation of preprocessing pipelines that take full advantage of the high quality imaging data; and
(iii) the establishment of a robust informatics infrastructure that has allowed widespread sharing of the HCP
data within the neuroimaging and neuroscience communities. The CCF builds on these accomplishments and
serves the human neuroimaging community in three ways. One aim is to provide consultation and support
services to the research community for the primary purpose of harmonizing image acquisition protocols with
those of the HCP. To this end, we have established a help desk whose support functions include transfer of
data acquisition sequences and image reconstruction algorithms; providing updates and improvements for
these sequences and algorithms; harmonization of imaging protocols and image reconstruction support for
different software platforms and versions; and consultation for potential problems (e.g. image artifacts). A
second aim is to provide services that maximize comparability of data acquired by CCF contributors. These
services include pre-data acquisition guidance to contributors to ensure that each project’s behavioral data are
obtained using HCP-compatible methods. This entails coordination with data contributors to develop and
maitain mechanisms to streamline transfers of de-identified data from the study sites to the CCF database.
The data from each study include the acquired images and all data associated with the project’s behavioral
battery. Manual and automated quality control procedures based on existing HCP methods are executed to
generate quality metrics that are published with the data. A standardized set of pipelines are then run in order
to produce minimally preprocessed data that is fully harmonized with the other data sets in the CCF database.
A third aim is to maintain the existing data repository infrastructure for Human Connectome Data and expand it
to include connectome data from other research laboratories that are funded under the Connectomes Related
to Human Diseases program. Together, these three aims enable the CCF to serve a central hub for
connectomics data aggregation and harmonization. The CCF’s suite of harmonization services from data
acquisition through data sharing ensure an unprecedented level of compatibility across data sets. The
resulting database enables the scientific community to conduct novel analyses to better understand brain
function in health and disease.

## Key facts

- **NIH application ID:** 9964050
- **Project number:** 1R24MH122820-01
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Daniel Scott Marcus
- **Activity code:** R24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,304,218
- **Award type:** 1
- **Project period:** 2020-04-15 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9964050

## Citation

> US National Institutes of Health, RePORTER application 9964050, Connectome Coordination Facility II (1R24MH122820-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9964050. Licensed CC0.

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