The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging

eLife

Tristan Glatard¹  Ali R Khan²  Katrin Amunts³  Timo Dickscheid³  Boris Bernhardt⁴  Jessica Royer⁴  Alan C Evans⁴  Paule-J Toussaint⁴  Lindsay B Lewis⁴  Claude Lepage⁴  Louis Collins⁴  Jordan DeKraker⁵  Casey Paquola⁶  Sofie L Valk⁷  Konrad Wagstyl⁸ 

[1] Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada;Department of Medical Biophysics, Schulich School of Medicine & Dentistry, University of Western Ontario, London, Canada;Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany;McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada;McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada;Brain and Mind Institute, University of Western Ontario, Ontario, Canada;McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada;Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany;Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany;Institute of Neuroscience and Medicine (INM-7), Forschungszentrum Jülich, Jülich, Germany;Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom;

关键词: neuroimaging;    histology;    multi-modal;    anatomy;    Human;   

DOI  :  10.7554/eLife.70119

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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.

【 授权许可】

CC BY