An open resource combining multi-contrast MRI and microscopy in the macaque brain

Amy F. D. Howard (), Istvan N. Huszar, Adele Smart, Michiel Cottaar, Greg Daubney, Taylor Hanayik, Alexandre A. Khrapitchev, Rogier B. Mars, Jeroen Mollink, Connor Scott, Nicola R. Sibson, Jerome Sallet, Saad Jbabdi and Karla L. Miller
Additional contact information
Amy F. D. Howard: University of Oxford
Istvan N. Huszar: University of Oxford
Adele Smart: University of Oxford
Michiel Cottaar: University of Oxford
Greg Daubney: University of Oxford
Taylor Hanayik: University of Oxford
Alexandre A. Khrapitchev: University of Oxford
Rogier B. Mars: University of Oxford
Jeroen Mollink: University of Oxford
Connor Scott: University of Oxford
Nicola R. Sibson: University of Oxford
Jerome Sallet: University of Oxford
Saad Jbabdi: University of Oxford
Karla L. Miller: University of Oxford

Nature Communications, 2023, vol. 14, issue 1, 1-18

Abstract: Abstract Understanding brain structure and function often requires combining data across different modalities and scales to link microscale cellular structures to macroscale features of whole brain organisation. Here we introduce the BigMac dataset, a resource combining in vivo MRI, extensive postmortem MRI and multi-contrast microscopy for multimodal characterisation of a single whole macaque brain. The data spans modalities (MRI and microscopy), tissue states (in vivo and postmortem), and four orders of spatial magnitude, from microscopy images with micrometre or sub-micrometre resolution, to MRI signals on the order of millimetres. Crucially, the MRI and microscopy images are carefully co-registered together to facilitate quantitative multimodal analyses. Here we detail the acquisition, curation, and first release of the data, that together make BigMac a unique, openly-disseminated resource available to researchers worldwide. Further, we demonstrate example analyses and opportunities afforded by the data, including improvement of connectivity estimates from ultra-high angular resolution diffusion MRI, neuroanatomical insight provided by polarised light imaging and myelin-stained histology, and the joint analysis of MRI and microscopy data for reconstruction of the microscopy-inspired connectome. All data and code are made openly available.

Date: 2023
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DOI: 10.1038/s41467-023-39916-1

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