McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada; Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany
Jessica Royer
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada
Lindsay B Lewis
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada
Claude Lepage
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada
Tristan Glatard
Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada
Konrad Wagstyl
Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
Jordan DeKraker
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montréal, Canada; Brain and Mind Institute, University of Western Ontario, Ontario, Canada
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
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.
