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Studying neuroanatomy using MRI

Nature Neuroscience volume 20, pages 314–326 (2017)Cite this article

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Abstract

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging and disease. Developments in MRI acquisition, image processing and data modeling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and for inferring microstructural properties; we also describe key artifacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, although methods need to improve and caution is required in interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works.

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Figure 1: Coronal slices of multimodal images of brain structure acquired in members of a birth cohort when they reached 20 years of age.
Figure 2: Voxel-based morphometry (VBM).
Figure 3: Surface-based analyses.
Figure 4
Figure 5: The dura and the cortex.
Figure 6: Overview of diffusion modeling advances.

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Acknowledgements

We thank C. Hammill for his assistance in the preparation of Figures 2 and 3, which contain data from The Ontario Brain Institutes' POND grant (to J.P.L.), and we thank L. Wald (Massachusetts General Hospital) for providing the images in Figure 6. Figure 1 contains data from R01MH085772-01A1 (to T.P.).

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  1. jason.lerch@utoronto.ca

Authors and Affiliations

  1. Program in Neuroscience and Mental Health, The Hospital for Sick Children, Toronto, Canada

    Jason P Lerch

  2. Department of Medical Biophysics, University of Toronto, Toronto, Canada

    Jason P Lerch

  3. Department of Radiology, Athinoula A. Martinos Center for Biomedical Research, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA

    André J W van der Kouwe & Bruce Fischl

  4. Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    André J W van der Kouwe & Bruce Fischl

  5. Developmental Neurogenomics Unit, Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland, USA

    Armin Raznahan

  6. Rotman Research Institute, Baycrest, Toronto, Canada

    Tomáš Paus

  7. Departments of Psychology and Psychiatry, University of Toronto, Toronto, Canada

    Tomáš Paus

  8. Center for the Developing Brain, Child Mind Institute, New York, New York, USA

    Tomáš Paus

  9. Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK

    Heidi Johansen-Berg, Karla L Miller, Stephen M Smith & Stamatios N Sotiropoulos

  10. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Bruce Fischl

  11. Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK.,

    Stamatios N Sotiropoulos

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Contributions

J.P.L., A.J.W.v.d.K., A.R., T.P., H.J.B., K.L.M., S.M.S., B.F. and S.N.S. conceptualized this review. J.P.L., A.J.W.v.d.K., A.R., T.P., B.F. and S.N.S. wrote the initial draft. J.P.L., A.J.W.v.d.K., A.R., T.P., H.J.B., K.L.M., S.M.S., B.F. and S.N.S. edited the final manuscript.

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Lerch, J., van der Kouwe, A., Raznahan, A. et al. Studying neuroanatomy using MRI. Nat Neurosci 20, 314–326 (2017). https://doi.org/10.1038/nn.4501

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