Integrating BigBrain with multi-modal imaging

BigBrain is a singular dataset that offers an ultra-high-resolution (20µm) volumetric reconstruction of a sliced and stained post-mortem human brain (Amunts et al. 2013). BigBrainWarp aims to enable integration of BigBrain with neuroimaging and other neurobiological modalities, helping a wide range of neuroscientists to utilise the cytoarchitectural information encoded in BigBrain for multi-scale neuroscientific discovery.


In the toolbox, you’ll find preprocessed BigBrain data, scripts to transform between BigBrain and standard MRI spaces, and a selection of histology-derived feature maps already transformed to MRI space.

Additionally, we’ve created a series of tutorials that illustrate potential workflows for BigBrain-MRI integration.

Tips for Getting Started

  • Read the BigBrainWarp preprint https://doi.org/10.1101/2021.05.04.442563
  • Watch a recent talk on the motivations and functionality of BigBrainWarp https://youtu.be/Stg_R63GyVY
  • Check out the tutorials. They are intended to show interesting ways to use BigBrain with multi-modal imaging and contain extra details on what’s under the hood of the BigBrainWarp.
  • Get in touch if you have any questions 🤙

Core developers

  • Casey Paquola, INM-1, Forschungszentrum Jülich & MICA Lab, Montreal Neurological Institute
  • Boris Bernhardt, MICA Lab, Montreal Neurological Institute

Please drop us a line if you’re interested in contributing!