Journal article
The Digital Brain Bank, an open access platform for post-mortem imaging datasets
- Abstract:
- Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes—Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab’s investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 5.3MB, Terms of use)
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- Publisher copy:
- 10.7554/elife.73153
Authors
- Publisher:
- eLife Sciences Publications
- Journal:
- eLife More from this journal
- Volume:
- 11
- Article number:
- e73153
- Publication date:
- 2022-03-17
- Acceptance date:
- 2022-03-17
- DOI:
- EISSN:
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2050-084X
- Pmid:
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35297760
- Language:
-
English
- Keywords:
- Pubs id:
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1246307
- Local pid:
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pubs:1246307
- Deposit date:
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2022-05-06
- ARK identifier:
Terms of use
- Copyright holder:
- Tendler et al.
- Copyright date:
- 2022
- Rights statement:
- © 2022, Tendler et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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