eLifeNeurosciencePeer-reviewed journal article
BigBrainWarp: Toolbox for integration of BigBrain 3D histology with multimodal neuroimaging
Casey PaquolaiD, Jessica RoyeriD, Lindsay B. LewisiD, Claude Lepage, Tristan GlatardiD, Konrad WagstyliD, Jordan DeKrakeriD, P.-J. ToussaintiD, Sofie Louise ValkiD, D. Louis CollinsiD, ALI RAZA KHANiD, Katrin AmuntsiD, Alan Charles EvansiD, Timo DickscheidiD, Boris C. BernhardtiD
Abstract
AO_SCPLOWBSTRACTC_SCPLOWNeuroimaging 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.
- organism: human
- assay: spatial transcriptomics
- assay: imaging
- research focus: dimensionality reduction
- research focus: database / resource
- research focus: software / tool
- approach: experimental assay
- Citations
- 92
- FWCI
- 4.76
- Field percentile
- top 4%
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