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Nat Neurosci. 2017 Feb 23;20(3):314-326. doi: 10.1038/nn.4501.

Studying neuroanatomy using MRI.

Author information

1
Program in Neuroscience and Mental Health, The Hospital for Sick Children, Toronto, Canada.
2
Department of Medical Biophysics, University of Toronto, Toronto, Canada.
3
Athinoula A. Martinos Center for Biomedical Research, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, USA.
4
Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
5
Developmental Neurogenomics Unit, Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland, USA.
6
Rotman Research Institute, Baycrest, Toronto, Canada.
7
Departments of Psychology and Psychiatry, University of Toronto, Toronto, Canada.
8
Center for the Developing Brain, Child Mind Institute, New York, New York, USA.
9
Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK.
10
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

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.

PMID:
28230838
DOI:
10.1038/nn.4501
[Indexed for MEDLINE]

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