# Connectome 2.0: A BRAIN Technology Integration and Dissemination Resource for Ultra-High Gradient Magnetic Resonance Imaging of Human Brain Circuits Across Scales

> **NIH NIH U24** · MASSACHUSETTS GENERAL HOSPITAL · 2024 · $1,430,923

## Abstract

SUMMARY
The goal of this proposal is to disseminate Connectome 2.0, the next-generation 3 Tesla human MRI scanner at
the Massachusetts General Hospital designed for imaging human brain circuits across scales, as a unique
resource for neuroscience collaborations around the world. This ultra-high gradient strength, high slew-rate 3T
MRI scanner was expressly developed through the support of the NIH BRAIN Initiative to enable studies of neural
tissue microstructure and brain circuits spanning the microscopic, mesoscopic, and macroscopic scales. The
Connectome 2.0 scanner builds upon our expertise in engineering and disseminating the first human
Connectome MRI scanner for the Human Connectome Project to hundreds of users worldwide. In order to
maximize the resolution of this powerful scanner for studies of tissue structure down to the microscopic level in
the living human brain, we have pushed the diffusion resolution limit to unprecedented levels by (1) achieving
ultra-high gradient strengths up to 500 mT/m and ultra-fast slew rates up to 600 T/m/s; (2) pushing the limits of
the RF receive coils and gradient characterization to enable maximum sensitivity with greatly reduced artifacts
using real-time eddy current corrected MRI acquisitions; (3) developing new pulse sequences to achieve the
highest diffusion- and spatial-resolution ever achieved in vivo; and (4) calibrating the measurements through
systematic validation in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales. As part of
this collaborative, center-wide endeavor, we will create novel advances in image acquisition and reconstruction
to enable maximal use of the Connectome 2.0 gradients for a wide array of neuroscientific applications. The
scanner has been validated in diffusion MRI studies down to sub-millimeter resolution with high-fidelity distortion
correction. The stronger gradients offer considerable improvements in diffusion imaging, reaching high b-values
with significantly shorter echo times. Funding of the current U24 proposal will facilitate the engineering effort and
scientific personnel to support, maintain, and expand the capabilities of this remarkable instrument, enable
efficient data transfer, integration, and analysis, as well as the requisite subject recruitment, user access, training,
and guidance to advance scientific collaborations nationally and internationally. While the major goal of this
project is to provide an innovative resource for unparalleled tissue microstructure and circuit characterization in
the living human brain, the research resource also holds great potential for improving our current understanding
of a wide range of neurological and psychiatric disorders, including multiple sclerosis, traumatic brain injury,
aging, Alzheimer’s disease, and mental disorders. This one-of-a-kind instrument represents the ultimate diffusion
MRI machine capable of addressing the BRAIN 2025 mandate to image across scales, from the microscopic
sc...

## Key facts

- **NIH application ID:** 10875962
- **Project number:** 1U24NS137077-01
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Susie Yi Huang
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,430,923
- **Award type:** 1
- **Project period:** 2024-08-15 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10875962

## Citation

> US National Institutes of Health, RePORTER application 10875962, Connectome 2.0: A BRAIN Technology Integration and Dissemination Resource for Ultra-High Gradient Magnetic Resonance Imaging of Human Brain Circuits Across Scales (1U24NS137077-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10875962. Licensed CC0.

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