001     905776
005     20231123201913.0
024 7 _ |a 2128/30631
|2 Handle
037 _ _ |a FZJ-2022-00999
100 1 _ |a Paquola, Casey
|0 P:(DE-Juel1)187055
|b 0
|e Corresponding author
245 _ _ |a BigBrainWarp: Toolbox for integration of BigBrain 3D histology with mutlimodal neuroimaging
260 _ _ |c 2021
336 7 _ |a Preprint
|b preprint
|m preprint
|0 PUB:(DE-HGF)25
|s 1700732257_2649
|2 PUB:(DE-HGF)
336 7 _ |a WORKING_PAPER
|2 ORCID
336 7 _ |a Electronic Article
|0 28
|2 EndNote
336 7 _ |a preprint
|2 DRIVER
336 7 _ |a ARTICLE
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336 7 _ |a Output Types/Working Paper
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520 _ _ |a Neuroimaging stands to benefit from emerging ultrahigh-resolution histological atlases of the human brain; the first of which is "BigBrain". Ongoing research aims to characterise regional differentiation of cytoarchitecture with BigBrain and to optimise registration of BigBrain with standard neuroimaging templates. Together, this work paves the way for multi-scale investigations of brain organisation. However, working with BigBrain can present new challenges for neuroimagers, including dealing with cellular resolution neuroanatomy and complex transformation procedures. To simplify workflows and support adoption of best practices, we developed BigBrainWarp, a toolbox for integration of BigBrain with multimodal neuroimaging. The primary BigBrainWarp function wraps multiple state-of-the-art deformation matrices into one line of code, allowing users to easily map data between BigBrain and standard MRI spaces. Additionally, the toolbox contains ready-to-use cytoarchitectural features to improve accessibility of histological information. The present article discusses recent contributions to BigBrain-MRI integration and demonstrates the utility of BigBrainWarp for further investigations.
536 _ _ |a 5251 - Multilevel Brain Organization and Variability (POF4-525)
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536 _ _ |a HIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)
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700 1 _ |a Royer, Jessica
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Lewis, Lindsay B
|0 P:(DE-HGF)0
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700 1 _ |a Lepage, Claude
|0 P:(DE-HGF)0
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700 1 _ |a Glatard, Tristan
|0 P:(DE-HGF)0
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700 1 _ |a Wagstyl, Konrad
|0 P:(DE-HGF)0
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700 1 _ |a DeKraker, Jordan
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700 1 _ |a Toussaint, Paule-J
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700 1 _ |a Valk, Sofie Louise
|0 P:(DE-Juel1)173843
|b 8
700 1 _ |a Collins, D Louis
|0 P:(DE-HGF)0
|b 9
700 1 _ |a Khan, Ali
|0 P:(DE-HGF)0
|b 10
700 1 _ |a Amunts, Katrin
|0 P:(DE-Juel1)131631
|b 11
700 1 _ |a Evans, Alan C
|0 P:(DE-HGF)0
|b 12
700 1 _ |a Dickscheid, Timo
|0 P:(DE-Juel1)165746
|b 13
700 1 _ |a Bernhardt, Boris
|0 P:(DE-HGF)0
|b 14
856 4 _ |u https://juser.fz-juelich.de/record/905776/files/2021.05.04.442563.full.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:905776
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a Forschungszentrum Jülich
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910 1 _ |a Forschungszentrum Jülich
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913 1 _ |a DE-HGF
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914 1 _ |y 2022
915 _ _ |a OpenAccess
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915 _ _ |a Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0
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920 _ _ |l yes
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980 _ _ |a preprint
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)INM-7-20090406
980 _ _ |a I:(DE-Juel1)INM-1-20090406
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts


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