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

  1. Casey Paquola  Is a corresponding author
  2. Jessica Royer
  3. Lindsay B Lewis
  4. Claude Lepage
  5. Tristan Glatard
  6. Konrad Wagstyl
  7. Jordan DeKraker
  8. Paule-Joanne Toussaint
  9. Sofie Louise Valk
  10. D Louis Collins
  11. Ali Khan
  12. Katrin Amunts
  13. Alan C Evans
  14. Timo Dickscheid
  15. Boris C Bernhardt  Is a corresponding author
  1. McGill University, Canada
  2. Concordia University, Canada
  3. UCL, United Kingdom
  4. University of Western Ontario, Canada
  5. Max Planck Institute Leipzig, Germany
  6. Montreal Neurological Institute and Hospital, Canada
  7. Heinrich Heine University, Germany
  8. Forschungszentrum Jülich, Germany

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.

Data availability

All data generated or analysed during this study are included in the BigBrainWarp repository (https://github.com/caseypaquola/BigBrainWarp).

The following previously published data sets were used

Article and author information

Author details

  1. Casey Paquola

    Neurology and Neurosurgery, McGill University, Montréal, Canada
    For correspondence
    casey.paquola@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0190-4103
  2. Jessica Royer

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Lindsay B Lewis

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Claude Lepage

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  5. Tristan Glatard

    Concordia University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  6. Konrad Wagstyl

    Wellcome Centre for Human Neuroimaging, UCL, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Jordan DeKraker

    Brain and Mind Institute, University of Western Ontario, London, Canada
    Competing interests
    The authors declare that no competing interests exist.
  8. Paule-Joanne Toussaint

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7446-150X
  9. Sofie Louise Valk

    Cognitive Neurogenetics, Max Planck Institute Leipzig, Leipzig, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2998-6849
  10. D Louis Collins

    McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal Neurological Institute and Hospital, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8432-7021
  11. Ali Khan

    Brain and Mind Institute, University of Western Ontario, London, Canada
    Competing interests
    The authors declare that no competing interests exist.
  12. Katrin Amunts

    Heinrich Heine University, Düsseldorf, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5828-0867
  13. Alan C Evans

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  14. Timo Dickscheid

    Forschungszentrum Jülich, Jülich, Germany
    Competing interests
    The authors declare that no competing interests exist.
  15. Boris C Bernhardt

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    For correspondence
    boris.bernhardt@mcgill.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9256-6041

Funding

Helmholtz Association

  • Casey Paquola
  • Lindsay B Lewis
  • Claude Lepage
  • Jordan DeKraker
  • Paule-Joanne Toussaint
  • Sofie Louise Valk
  • D Louis Collins
  • Katrin Amunts
  • Alan C Evans
  • Timo Dickscheid
  • Boris C Bernhardt

Fonds de Recherche du Québec - Santé

  • Casey Paquola
  • Boris C Bernhardt

National Science and Engineering Research Council of Canada

  • Ali Khan
  • Boris C Bernhardt

Canadian Institutes of Health Research

  • Jessica Royer
  • Ali Khan
  • Boris C Bernhardt

SickKids Foundation

  • Boris C Bernhardt

Azrieli Center for Autism Research

  • Boris C Bernhardt

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Paquola et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,907
    views
  • 395
    downloads
  • 57
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Casey Paquola
  2. Jessica Royer
  3. Lindsay B Lewis
  4. Claude Lepage
  5. Tristan Glatard
  6. Konrad Wagstyl
  7. Jordan DeKraker
  8. Paule-Joanne Toussaint
  9. Sofie Louise Valk
  10. D Louis Collins
  11. Ali Khan
  12. Katrin Amunts
  13. Alan C Evans
  14. Timo Dickscheid
  15. Boris C Bernhardt
(2021)
The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging
eLife 10:e70119.
https://doi.org/10.7554/eLife.70119

Share this article

https://doi.org/10.7554/eLife.70119

Further reading

    1. Neuroscience
    William T Redman, Santiago Acosta-Mendoza ... Michael J Goard
    Research Article

    Although grid cells are one of the most well-studied functional classes of neurons in the mammalian brain, whether there is a single orientation and spacing value per grid module has not been carefully tested. We analyze a recent large-scale recording of medial entorhinal cortex to characterize the presence and degree of heterogeneity of grid properties within individual modules. We find evidence for small, but robust, variability and hypothesize that this property of the grid code could enhance the encoding of local spatial information. Performing analysis on synthetic populations of grid cells, where we have complete control over the amount heterogeneity in grid properties, we demonstrate that grid property variability of a similar magnitude to the analyzed data leads to significantly decreased decoding error. This holds even when restricted to activity from a single module. Our results highlight how the heterogeneity of the neural response properties may benefit coding and opens new directions for theoretical and experimental analysis of grid cells.

    1. Genetics and Genomics
    2. Neuroscience
    Monique Marylin Alves de Almeida, Yves De Repentigny ... Rashmi Kothary
    Research Article

    Spinal muscular atrophy (SMA) is caused by mutations in the Survival Motor Neuron 1 (SMN1) gene. While traditionally viewed as a motor neuron disorder, there is involvement of various peripheral organs in SMA. Notably, fatty liver has been observed in SMA mouse models and SMA patients. Nevertheless, it remains unclear whether intrinsic depletion of SMN protein in the liver contributes to pathology in the peripheral or central nervous systems. To address this, we developed a mouse model with a liver-specific depletion of SMN by utilizing an Alb-Cre transgene together with one Smn2B allele and one Smn1 exon 7 allele flanked by loxP sites. Initially, we evaluated phenotypic changes in these mice at postnatal day 19 (P19), when the severe model of SMA, the Smn2B/- mice, exhibit many symptoms of the disease. The liver-specific SMN depletion does not induce motor neuron death, neuromuscular pathology or muscle atrophy, characteristics typically observed in the Smn2B/- mouse at P19. However, mild liver steatosis was observed, although no changes in liver function were detected. Notably, pancreatic alterations resembled that of Smn2B/-mice, with a decrease in insulin-producing β-cells and an increase in glucagon-producingα-cells, accompanied by a reduction in blood glucose and an increase in plasma glucagon and glucagon-like peptide (GLP-1). These changes were transient, as mice at P60 exhibited recovery of liver and pancreatic function. While the mosaic pattern of the Cre-mediated excision precludes definitive conclusions regarding the contribution of liver-specific SMN depletion to overall tissue pathology, our findings highlight an intricate connection between liver function and pancreatic abnormalities in SMA.