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Graph-based network analysis in schizophrenia
Author(s) -
Sifis Micheloyannis
Publication year - 2012
Publication title -
world journal of psychiatry
Language(s) - Uncategorized
Resource type - Journals
ISSN - 2220-3206
DOI - 10.5498/wjp.v2.i1.1
Subject(s) - schizophrenia (object oriented programming) , diffusion mri , disconnection , network analysis , computer science , cluster analysis , neuroscience , data science , psychology , psychiatry , medicine , artificial intelligence , magnetic resonance imaging , physics , quantum mechanics , political science , law , radiology
Over the last few years, many studies have been published using modern network analysis of the brain. Researchers and practical doctors alike should understand this method and its results on the brain evaluation at rest, during activation and in brain disease. The studies are noninvasive and usually performed with elecroencephalographic, magnetoencephalographic, magnetic resonance imaging and diffusion tensor imaging brain recordings. Different tools for analysis have been developed, although the methods are in their early stages. The results of these analyses are of special value. Studies of these tools in schizophrenia are important because widespread and local network disturbances can be evaluated by assessing integration, segregation and several structural and functional properties. With the help of network analyses, the main findings in schizophrenia are lower optimum network organization, less efficiently wired networks, less local clustering, less hierarchical organization and signs of disconnection. There are only about twenty five relevant papers on the subject today. Only a few years of study of these methods have produced interesting results and it appears promising that the development of these methods will present important knowledge for both the preclinical signs of schizophrenia and the methods' therapeutic effects.

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