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.

Reviewing Editor

  1. Klaas Enno Stephan, University of Zurich and ETH Zurich, Switzerland

Version history

  1. Received: January 19, 2018
  2. Accepted: May 7, 2018
  3. Accepted Manuscript published: May 11, 2018 (version 1)
  4. Version of Record published: June 1, 2018 (version 2)

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

  • 6,403
    views
  • 827
    downloads
  • 139
    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. Developmental Biology
    2. Neuroscience
    Melody C Iacino, Taylor A Stowe ... Mark J Ferris
    Research Article Updated

    Adolescence is characterized by changes in reward-related behaviors, social behaviors, and decision-making. These behavioral changes are necessary for the transition into adulthood, but they also increase vulnerability to the development of a range of psychiatric disorders. Major reorganization of the dopamine system during adolescence is thought to underlie, in part, the associated behavioral changes and increased vulnerability. Here, we utilized fast scan cyclic voltammetry and microdialysis to examine differences in dopamine release as well as mechanisms that underlie differential dopamine signaling in the nucleus accumbens (NAc) core of adolescent (P28-35) and adult (P70-90) male rats. We show baseline differences between adult and adolescent-stimulated dopamine release in male rats, as well as opposite effects of the α6 nicotinic acetylcholine receptor (nAChR) on modulating dopamine release. The α6-selective blocker, α-conotoxin, increased dopamine release in early adolescent rats, but decreased dopamine release in rats beginning in middle adolescence and extending through adulthood. Strikingly, blockade of GABAA and GABAB receptors revealed that this α6-mediated increase in adolescent dopamine release requires NAc GABA signaling to occur. We confirm the role of α6 nAChRs and GABA in mediating this effect in vivo using microdialysis. Results herein suggest a multisynaptic mechanism potentially unique to the period of development that includes early adolescence, involving acetylcholine acting at α6-containing nAChRs to drive inhibitory GABA tone on dopamine release.

    1. Neuroscience
    Daniel Hoops, Robert Kyne ... Cecilia Flores
    Short Report

    Dopamine axons are the only axons known to grow during adolescence. Here, using rodent models, we examined how two proteins, Netrin-1 and its receptor, UNC5C, guide dopamine axons toward the prefrontal cortex and shape behaviour. We demonstrate in mice (Mus musculus) that dopamine axons reach the cortex through a transient gradient of Netrin-1-expressing cells – disrupting this gradient reroutes axons away from their target. Using a seasonal model (Siberian hamsters; Phodopus sungorus) we find that mesocortical dopamine development can be regulated by a natural environmental cue (daylength) in a sexually dimorphic manner – delayed in males, but advanced in females. The timings of dopamine axon growth and UNC5C expression are always phase-locked. Adolescence is an ill-defined, transitional period; we pinpoint neurodevelopmental markers underlying this period.