Abstract

Comparing the brains of related species faces the challenges of establishing homologies whilst accommodating evolutionary specializations. Here we propose a general framework for understanding similarities and differences between the brains of primates. The approach uses white matter blueprints of the whole cortex based on a set of white matter tracts that can be anatomically matched across species. The blueprints provide a common reference space that allows us to navigate between brains of different species, identify homologous cortical areas, or to transform whole cortical maps from one species to the other. Specializations are cast within this framework as deviations between the species' blueprints. We illustrate how this approach can be used to compare human and macaque brains.

Data availability

The human diffusion MRI data was obtained from the Human Connectome Project (www.humanconnectome.org.). Tractography protocols for building the blueprints, code, and results are available for download from Gitlab at https://git.fmrib.ox.ac.uk/rmars/comparing-connectivity-blueprints.git.

The following previously published data sets were used

Article and author information

Author details

  1. Rogier B Mars

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    For correspondence
    rogier.mars@psy.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6302-8631
  2. Stamatios N Sotiropoulos

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4735-5776
  3. Richard E Passingham

    Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Jerome Sallet

    Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7878-0209
  5. Lennart M Verhagen

    Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Alexandre A Khrapitchev

    Department of Oncology, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7616-6635
  7. Nicola Sibson

    Department of Oncology, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Saad Jbabdi

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

Funding

Biotechnology and Biological Sciences Research Council (BB/N019814/1)

  • Rogier B Mars

Medical Research Council (MR/L009013/1)

  • Saad Jbabdi

Wellcome (203139/Z/16/Z)

  • Rogier B Mars
  • Jerome Sallet
  • Saad Jbabdi

Nederlandse Organisatie voor Wetenschappelijk Onderzoek (452-­13-­015)

  • Rogier B Mars

Cancer Research UK (C5255/A15935)

  • Alexandre A Khrapitchev
  • Nicola Sibson

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

Copyright

© 2018, Mars 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

  • 6,901
    views
  • 863
    downloads
  • 156
    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. Rogier B Mars
  2. Stamatios N Sotiropoulos
  3. Richard E Passingham
  4. Jerome Sallet
  5. Lennart M Verhagen
  6. Alexandre A Khrapitchev
  7. Nicola Sibson
  8. Saad Jbabdi
(2018)
Whole brain comparative anatomy using connectivity blueprints
eLife 7:e35237.
https://doi.org/10.7554/eLife.35237

Share this article

https://doi.org/10.7554/eLife.35237

Further reading

    1. Neuroscience
    Yisi Liu, Pu Wang ... Hongwei Zhou
    Short Report

    The increasing use of tissue clearing techniques underscores the urgent need for cost-effective and simplified deep imaging methods. While traditional inverted confocal microscopes excel in high-resolution imaging of tissue sections and cultured cells, they face limitations in deep imaging of cleared tissues due to refractive index mismatches between the immersion media of objectives and sample container. To overcome these challenges, the RIM-Deep was developed to significantly improve deep imaging capabilities without compromising the normal function of the confocal microscope. This system facilitates deep immunofluorescence imaging of the prefrontal cortex in cleared macaque tissue, extending imaging depth from 2 mm to 5 mm. Applied to an intact and cleared Thy1-EGFP mouse brain, the system allowed for clear axonal visualization at high imaging depth. Moreover, this advancement enables large-scale, deep 3D imaging of intact tissues. In principle, this concept can be extended to any imaging modality, including existing inverted wide-field, confocal, and two-photon microscopy. This would significantly upgrade traditional laboratory configurations and facilitate the study of connectomes in the brain and other tissues.

    1. Evolutionary Biology
    2. Neuroscience
    Jenny Chen, Phoebe R Richardson ... Hopi E Hoekstra
    Research Article

    Genetic variation is known to contribute to the variation of animal social behavior, but the molecular mechanisms that lead to behavioral differences are still not fully understood. Here, we investigate the cellular evolution of the hypothalamic preoptic area (POA), a brain region that plays a critical role in social behavior, across two sister species of deer mice (Peromyscus maniculatus and P. polionotus) with divergent social systems. These two species exhibit large differences in mating and parental care behavior across species and sex. Using single-nucleus RNA-sequencing, we build a cellular atlas of the POA for males and females of both Peromyscus species. We identify four cell types that are differentially abundant across species, two of which may account for species differences in parental care behavior based on known functions of these cell types. Our data further implicate two sex-biased cell types to be important for the evolution of sex-specific behavior. Finally, we show a remarkable reduction of sex-biased gene expression in P. polionotus, a monogamous species that also exhibits reduced sexual dimorphism in parental care behavior. Our POA atlas is a powerful resource to investigate how molecular neuronal traits may be evolving to give rise to innate differences in social behavior across animal species.