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Review Article
A Biomedical Imaging Analysis of the Prevalent Neuropsychiatric Disorders
Ayden Jacob1* and Sharon Cohen2
1Oxford Institute for Radiation Oncology; University of Oxford, UK
- Corresponding Author:
- Ayden Jacob
Oxford Institute for Radiation On cology
University of Oxford, UK
E-mail: aydenjacob@berkeley.edu
Received date: June 12, 2013; Accepted date: June 27, 2013; Published date: June 29, 2013
Citation: Jacob A, Cohen S (2013) A Biomedical Imaging Analysis of the Prevalent Neuropsychiatric Disorders. J Alzheimers Dis Parkinsonism 3: 117. doi:10.4172/2161-0460.1000117
Copyright: © 2013 Jacob A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
The utilization of various neuroimaging modalities to illuminate the structural and functional abnormalities detected in neuropsychiatric brain disorders has reached an unprecedented stage of evolvement in the medical community. Advances in structural and functional brain imaging technologies enable the medical community to discover the neurobiological basis of neurological illness in a very precise and dependable manner. Neuroimaging tools such as PET, SPECT and MRI have been better developed in order to further the neuroanatomical and neurophysiological basis of mental illnesses and cognitive disorders. With the advent of radiological innovation in neuroimaging, the focus in the medical community has shifted from the examination and study of single brain regions perhaps responsible for a specific psychiatric illness, to the critical examination of integrated brain systems which may be responsible for the phenotypic expressions of these illnesses. Imaging techniques have now made it quite clear that we must begin to investigate the neural networks involved in the pathophysiology of neuropsychiatric disorders. This paradigm shift, due to the innovations in brain imaging technologies, will likely facilitate the diagnostic reclassification of these complex heterogeneous disorders, enhance our understanding of genetic and environmental causes of the disorders, and improve our ability to treat these patients.
