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  Abnormal connectional fingerprint in schizophrenia: A novel network analysis of diffusion tensor imaging data

Edwin Thanarajah, S., Han, C. E., Rotarska-Jagiela, A., Singer, W., Deichmann, R., Maurer, K., et al. (2016). Abnormal connectional fingerprint in schizophrenia: A novel network analysis of diffusion tensor imaging data. Front Psychiatry, 7: 114. doi:10.3389/fpsyt.2016.00114.

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EdwinThanaraja_2016_AbnormalConnectional.pdf (Publisher version), 2MB
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EdwinThanaraja_2016_AbnormalConnectional.pdf
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2016
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Copyright © 2016 Edwin Thanarajah, Han, Rotarska-Jagiela, Singer, Deichmann, Maurer, Kaiser and Uhlhaas

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 Creators:
Edwin Thanarajah, Sharmili, Author
Han, Cheol E., Author
Rotarska-Jagiela, Anna, Author
Singer, Wolf1, 2, Author                 
Deichmann, Ralf, Author
Maurer, Konrad, Author
Kaiser, Marcus, Author
Uhlhaas, Peter J., Author
Affiliations:
1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstr. 46, 60528 Frankfurt, DE, ou_2074314              
2Singer Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, DE, ou_3381220              

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Free keywords: connectional fingerprint diffusion tensor imaging graph theory neuroinformatics schizophrenia
 Abstract: The graph theoretical analysis of structural magnetic resonance imaging (MRI) data has received a great deal of interest in recent years to characterize the organizational principles of brain networks and their alterations in psychiatric disorders, such as schizophrenia. However, the characterization of networks in clinical populations can be challenging, since the comparison of connectivity between groups is influenced by several factors, such as the overall number of connections and the structural abnormalities of the seed regions. To overcome these limitations, the current study employed the whole-brain analysis of connectional fingerprints in diffusion tensor imaging data obtained at 3 T of chronic schizophrenia patients (n = 16) and healthy, age-matched control participants (n = 17). Probabilistic tractography was performed to quantify the connectivity of 110 brain areas. The connectional fingerprint of a brain area represents the set of relative connection probabilities to all its target areas and is, hence, less affected by overall white and gray matter changes than absolute connectivity measures. After detecting brain regions with abnormal connectional fingerprints through similarity measures, we tested each of its relative connection probability between groups. We found altered connectional fingerprints in schizophrenia patients consistent with a dysconnectivity syndrome. While the medial frontal gyrus showed only reduced connectivity, the connectional fingerprints of the inferior frontal gyrus and the putamen mainly contained relatively increased connection probabilities to areas in the frontal, limbic, and subcortical areas. These findings are in line with previous studies that reported abnormalities in striatal-frontal circuits in the pathophysiology of schizophrenia, highlighting the potential utility of connectional fingerprints for the analysis of anatomical networks in the disorder.

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 Dates: 2016-06-30
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.3389/fpsyt.2016.00114
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Title: Front Psychiatry
  Alternative Title : Frontiers in psychiatry
Source Genre: Journal
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Pages: - Volume / Issue: 7 Sequence Number: 114 Start / End Page: - Identifier: ISBN: 1664-0640 (Electronic)1664-0640 (Linking)