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Review
. 2012 Nov;33(10):1845-50.
doi: 10.3174/ajnr.A2799. Epub 2011 Dec 15.

Functional and structural MR imaging in neuropsychiatric disorders, Part 1: imaging techniques and their application in mild cognitive impairment and Alzheimer disease

S Mueller  1 , D Keeser, M F Reiser, S Teipel, T Meindl
Affiliations
Review

Functional and structural MR imaging in neuropsychiatric disorders, Part 1: imaging techniques and their application in mild cognitive impairment and Alzheimer disease

S Mueller et al. AJNR Am J Neuroradiol. 2012 Nov.

Abstract

During the past decade, the application of advanced MR imaging techniques in neuropsychiatric disorders has seen a rapid increase. Disease-specific alterations in brain function can be assessed by fMRI. Structural GM and WM properties are increasingly investigated by DTI and voxel-based approaches like VBM. These methods provide neurobiologic correlates for brain architecture and function, evaluation tools for therapeutic approaches, and potential early markers for diagnosis. The aim of this review was to provide insight into the principles of functional and structural imaging and to delineate major findings in MCI, AD (Part 1), autism, and schizophrenia (Part 2), which are common psychiatric disorders covering different stages of the life span. Part 2 will conclude by summarizing current applications, limitations, and future prospects in the field of MR imaging-based neuroimaging.

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Figures

Fig 1.
Fig 1.
MR imaging−based modalities in neuroimaging research discussed in this review. In rsfMRI, the DMN of healthy subjects is shown. In DTI, the skeleton (green) is overlaid on the average FA image of healthy subjects. In VBM of healthy subjects, GM (blue-light blue), WM (white), and CSF (pink) can be extracted from T1-weighted structural data. All images are schematic representations of our own data, processed with Functional MR Imaging of the Brain Software Library, Version 1.7 (http://www.fmrib.ox.ac.uk).
Fig 2.
Fig 2.
DMN connectivity of the ACC/medial prefrontal cortex and the PCC in healthy elderly subjects, those with MCI, and those with AD. A recent study by Koch et al demonstrated high classification accuracy by using multivariate analysis approaches.
See this image and copyright information in PMC

References

    1. Ogawa S, Tank DW, Menon R, et al. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A 1992;89:5951–55 - PMC - PubMed
    1. Friston KJ, Frith CD, Liddle PF, et al. Functional connectivity: the principal-component analysis of large (PET) data sets. J Cereb Blood Flow Metab 1993;13:5–14 - PubMed
    1. Fox MD, Snyder AZ, Vincent JL, et al. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 2005;102:9673–78. Epub 2005 Jun 23 - PMC - PubMed
    1. van de Ven VG, Formisano E, Prvulovic D, et al. Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest. Hum Brain Mapp 2004;22:165–78 - PMC - PubMed
    1. Mantini D, Perrucci MG, Del Gratta C, et al. Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci U S A 2007;104:13170–75 - PMC - PubMed

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