Abstract
Neuroimaging stands to benefit from emerging ultrahigh-resolution 3D histological atlases of the human brain; the first of which is 'BigBrain'. Here, we review recent methodological advances for the integration of BigBrain with multi-modal neuroimaging and introduce a toolbox, 'BigBrainWarp', that combines these developments. The aim of BigBrainWarp is to simplify workflows and support the adoption of best practices. This is accomplished with a simple wrapper function that allows users to easily map data between BigBrain and standard MRI spaces. The function automatically pulls specialised transformation procedures, based on ongoing research from a wide collaborative network of researchers. Additionally, the toolbox improves accessibility of histological information through dissemination of ready-to-use cytoarchitectural features. Finally, we demonstrate the utility of BigBrainWarp with three tutorials and discuss the potential of the toolbox to support multi-scale investigations of brain organisation.
Highlights
Understanding brain anatomy requires a multi-s cale perspective
The BigBrainWarp toolbox supports a range of integrative BigBrain–magnetic resonance imaging (MRI) analyses
A major aim of neuroanatomical research has been to understand the functioning of the human brain
Summary
Understanding brain anatomy requires a multi-s cale perspective. Regional variations in cell types and distributions underlie macro-scale patterns, whether they are reflective of functional dynamics, age, or disease states. For over 150 years (von Gudden, 1886), histological analysis of post mortem tissue has helped to reveal the microscopic architecture of the brain. Neuroanatomists observed a distinctive layered organisation of cells within the cortex (Baillarger, 1840), identified differences in the cellular composition (Betz, 1874), and developed principles of cortical organisation, including the definition of cortical types (Meynert, 1867) and areas (Brodmann, 1908; Von Economo and Koskinas, 1925). Digitisation of post mortem tissue has allowed automated characterisation of cytoarchitecture and the definition of borders between areas (Schleicher et al, 1999)
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