Multimodal precision MRI of the individual human brain at ultra-high fields

Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7 T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply "gradients" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.

Authors

Institutions

Publication Details

Journal
Scientific Data
Published
2025-03-29
DOI
https://doi.org/10.1038/s41597-025-04863-7
Citations
15
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
20.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multimodal precision MRI of the individual human brain at ultra-high fields

Boris C. Bernhardt, Nicole Eichert, Oualid Benkarim, Casey Paquola et al.
15 citations
Scientific Data
Advanced MRI Techniques and Applications
20.40
article

Multimodal precision MRI of the individual human brain at ultra-high fields

Boris C. Bernhardt, Nicole Eichert, Oualid Benkarim, Casey Paquola, Raúl Rodríguez‐Cruces, Jessica Royer, Christine Tardif, Jordan DeKraker, Donna Gift Cabalo, Shahin Tavakol, Julien Doyon, Youngeun Hwang, Yezhou Wang, Risavarshni Thevakumaran, Valeria Kebets, David A. Rudko, Jonathan Smallwood, Ilana R. Leppert, Yigu Zhou
article en
15 citations

Abstract

Multimodal neuroimaging, in particular magnetic resonance imaging (MRI), allows for non-invasive examination of human brain structure and function across multiple scales. Precision neuroimaging builds upon this foundation, enabling the mapping of brain structure, function, and connectivity patterns with high fidelity in single individuals. Highfield MRI, operating at magnetic field strengths of 7 Tesla (T) or higher, increases signal-to-noise ratio and opens up possibilities for gains spatial resolution. Here, we share a multimodal Precision Neuroimaging and Connectomics (PNI) 7 T MRI dataset. Ten healthy individuals underwent a comprehensive MRI protocol, including T1 relaxometry, magnetization transfer imaging, T2*-weighted imaging, diffusion MRI, and multi-state functional MRI paradigms, aggregated across three imaging sessions. Alongside anonymized raw MRI data, we release cortex-wide connectomes from different modalities across multiple parcellation scales, and supply "gradients" that compactly characterize spatial patterning of cortical organization. Our precision MRI dataset will advance our understanding of structure-function relationships in the individual human brain and is publicly available via the Open Science Framework.

Scientific DataVol. 12(1)
Montreal Neurological Institute and Hospital (CA), Forschungszentrum Jülich (DE), Queen's University (CA), University of Oxford (GB), McGill University (CA)
Openalex Percentile: Top 0%
Advanced MRI Techniques and Applications
20.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.