It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
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.
Linking microscale cellular structures to macroscale features of the brain is required to fully understand its structure and function. Here, the authors present a resource which combines multi-contrast microscopy and MRI of a single whole macaque brain to facilitate multimodal analyses.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details








1 University of Oxford, Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
2 University of Oxford, Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948); University of Oxford, Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
3 University of Oxford, Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
4 University of Oxford, Department of Oncology, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)
5 University of Oxford, Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948); Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands (GRID:grid.5590.9) (ISNI:0000000122931605)
6 University of Oxford, Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, Oxford, UK (GRID:grid.4991.5) (ISNI:0000 0004 1936 8948)