Ultra-high gradient connectomics and microstructure MRI scanner for imaging of human brain circuits across scales
Defining the connectome, the complete matrix of structural connections between the nervous system nodes, is a challenge for human systems neuroscience due to the range of scales that must be bridged. Here we report the design of the Connectome 2.0 human magnetic resonance imaging (MRI) scanner to perform connectomics at the mesoscopic and microscopic scales with strong gradients for in vivo human imaging. We construct a 3-layer head-only gradient coil optimized to minimize peripheral nerve stimulation while achieving a gradient strength of 500 mT m<sup>-1</sup> and a slew rate of 600 T m<sup>-1</sup> s<sup>-1</sup>, corresponding to a 5-fold greater gradient performance than state-of-the-art research gradient systems, including the original Connectome (Connectome 1.0) scanner. We find that gains in sensitivity of up to two times were achieved by integrating a 72-channel in vivo head coil and a 64-channel ex vivo whole-brain radiofrequency coil with built-in field monitoring for data fidelity. We demonstrate mapping of fine white matter pathways and inferences of cellular and axonal size and morphology approaching the single-micron level, with at least a 30% sensitivity improvement compared with Connectome 1.0.
Authors
- Manuela B. Rösler (ORCID: https://orcid.org/0000-0001-5750-9391)
- Bruce R. Rosen (ORCID: https://orcid.org/0000-0002-8576-0839)
- Lawrence L. Wald (ORCID: https://orcid.org/0000-0001-8278-6307)
- Mirsad Mahmutović (ORCID: https://orcid.org/0000-0001-9178-4194)
- Gudrun Ruyters
- Joseph B. Fischer
- Thomas Witzel (ORCID: https://orcid.org/0000-0002-5806-4897)
- R. Schuster (ORCID: https://orcid.org/0000-0001-8027-5159)
- Peter J. Basser (ORCID: https://orcid.org/0000-0003-4795-6088)
- Hong‐Hsi Lee (ORCID: https://orcid.org/0000-0002-3663-6559)
- Andreas Potthast
- Daniel Park (ORCID: https://orcid.org/0000-0002-7263-9327)
- Mathias Davids (ORCID: https://orcid.org/0000-0003-0217-9123)
- Wei‐Ching Lo (ORCID: https://orcid.org/0000-0002-1893-0500)
- Bryan Clifford (ORCID: https://orcid.org/0000-0002-1966-0581)
- Qiyuan Tian (ORCID: https://orcid.org/0000-0002-8350-5295)
- Elmar Rummert
- Chiara Maffei (ORCID: https://orcid.org/0000-0002-3837-0635)
- Boris Keil (ORCID: https://orcid.org/0000-0003-0805-8330)
- Berkin Bilgic̦ (ORCID: https://orcid.org/0000-0002-9080-7865)
- Stefan Stocker
- Gabriel Ramos‐Llordén (ORCID: https://orcid.org/0000-0003-4020-705X)
- John E. Kirsch (ORCID: https://orcid.org/0000-0002-0389-9475)
- Alina Scholz (ORCID: https://orcid.org/0000-0002-3324-6889)
- Anastasia Yendiki (ORCID: https://orcid.org/0000-0003-1386-3828)
- Thomas Benner
- Susie Y. Huang (ORCID: https://orcid.org/0000-0003-2950-7254)
- Yixin Ma (ORCID: https://orcid.org/0000-0002-2080-9013)
- Hansol Lee (ORCID: https://orcid.org/0000-0003-2112-1197)
- Andreas Krug
- Peter Dietz (ORCID: https://orcid.org/0009-0002-1803-0892)
Institutions
- National Institutes of Health (US)
- Harvard University (US)
- Philipps University of Marburg (DE)
- Massachusetts General Hospital (US)
- Center for Neuro-Oncology (US)
- Athinoula A. Martinos Center for Biomedical Imaging (US)
- Siemens (United States) (US)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (US)
- Siemens Healthineers (Germany) (DE)
- Technische Hochschule Mittelhessen (DE)
Publication Details
- Journal
- Nature Biomedical Engineering
- Published
- 2025-07-16
- DOI
- https://doi.org/10.1038/s41551-025-01457-x
- Citations
- 9
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 12.24
Funders
- Deutsche Forschungsgemeinschaft
- National Institutes of Health