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Multimodal neuroimaging computing: a review of the applications in neuropsychiatric disorders

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2015

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Springer Berlin Heidelberg
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Liu, Sidong, Weidong Cai, Siqi Liu, Fan Zhang, Michael Fulham, Dagan Feng, Sonia Pujol, and Ron Kikinis. 2015. “Multimodal neuroimaging computing: a review of the applications in neuropsychiatric disorders.” Brain Informatics 2 (1): 167-180. doi:10.1007/s40708-015-0019-x. http://dx.doi.org/10.1007/s40708-015-0019-x.

Abstract

Multimodal neuroimaging is increasingly used in neuroscience research, as it overcomes the limitations of individual modalities. One of the most important applications of multimodal neuroimaging is the provision of vital diagnostic data for neuropsychiatric disorders. Multimodal neuroimaging computing enables the visualization and quantitative analysis of the alterations in brain structure and function, and has reshaped how neuroscience research is carried out. Research in this area is growing exponentially, and so it is an appropriate time to review the current and future development of this emerging area. Hence, in this paper, we review the recent advances in multimodal neuroimaging (MRI, PET) and electrophysiological (EEG, MEG) technologies, and their applications to the neuropsychiatric disorders. We also outline some future directions for multimodal neuroimaging where researchers will design more advanced methods and models for neuropsychiatric research.

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Multimodal, Neuroimaging, Neuropsychiatric

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