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New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia

Paolo Finotelli, Caroline Garcia Forlim, Paolo Dulio, Leonie Klock, Alessia Pini, Johanna Bächle, Laura Stoll, Patrick Giemsa, Marie Fuchs, Nikola Schoofs, Christiane Montag, Jürgen Gallinat, Simone Kühn
doi: https://doi.org/10.1101/489997
Paolo Finotelli
aPolitecnico di Milano, Department of Mathematics “F. Brioschi”, Piazza L. da Vinci 32, 20133, Milan, Italy
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Caroline Garcia Forlim
bUniversity Medical Center Hamburg - Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246, Hamburg, Germany
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Paolo Dulio
aPolitecnico di Milano, Department of Mathematics “F. Brioschi”, Piazza L. da Vinci 32, 20133, Milan, Italy
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Leonie Klock
bUniversity Medical Center Hamburg - Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246, Hamburg, Germany
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Alessia Pini
cUniversità Cattolica del Sacro Cuore, Department of Statistical Sciences, Largo A. Gemelli, 1 – 20123 Milan, Italy
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Johanna Bächle
dCharité University Medicine and St. Hedwig-Krankenhaus, Department of Psychiatry and Psychotherapy, Große Hamburger Straße 5-11, 10115 Berlin, Germany
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Laura Stoll
dCharité University Medicine and St. Hedwig-Krankenhaus, Department of Psychiatry and Psychotherapy, Große Hamburger Straße 5-11, 10115 Berlin, Germany
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Patrick Giemsa
dCharité University Medicine and St. Hedwig-Krankenhaus, Department of Psychiatry and Psychotherapy, Große Hamburger Straße 5-11, 10115 Berlin, Germany
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Marie Fuchs
dCharité University Medicine and St. Hedwig-Krankenhaus, Department of Psychiatry and Psychotherapy, Große Hamburger Straße 5-11, 10115 Berlin, Germany
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Nikola Schoofs
dCharité University Medicine and St. Hedwig-Krankenhaus, Department of Psychiatry and Psychotherapy, Große Hamburger Straße 5-11, 10115 Berlin, Germany
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Christiane Montag
dCharité University Medicine and St. Hedwig-Krankenhaus, Department of Psychiatry and Psychotherapy, Große Hamburger Straße 5-11, 10115 Berlin, Germany
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Jürgen Gallinat
bUniversity Medical Center Hamburg - Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246, Hamburg, Germany
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Simone Kühn
bUniversity Medical Center Hamburg - Eppendorf, Clinic and Policlinic for Psychiatry and Psychotherapy, Martinistraße 52, 20246, Hamburg, Germany
eMax Planck Institute for Human Development, Center for Lifespan Psychology, Lentzeallee 94, 14195 Berlin, Germany
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Abstract

Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive and behavioral symptoms in this disorder.

When building brain networks, functional and structural networks are typically modelled independently: functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks.

In this study, we applied a new flexible graph-theoretical-multimodal model called FD (F, the functional connectivity matrix, and D, the structural matrix) to construct brain networks combining functional, structural and topological information of MRI measurements (structural and resting state imaging) to patients with schizophrenia (N=35) and matched healthy individuals (N=41). As a reference condition, the traditional pure functional connectivity (pFC) analysis was carried out.

By using the FD model, we found disrupted connectivity in the thalamo-cortical network in schizophrenic patients, whereas the pFC model failed to extract group differences after multiple comparison correction. We interpret this observation as evidence that the FD model is superior to conventional connectivity analysis, by stressing relevant features of the whole brain connectivity including functional, structural and topological signatures. The FD model can be used in future research to model subtle alterations of functional and structural connectivity resulting in pronounced clinical syndromes and major psychiatric disorders. Lastly, FD is not limited to the analysis of resting state fMRI, and can be applied to EEG, MEG etc.

Authors contribution

Data acquisition: LK, JB, LS, PG, MF, NK, CM, SK, JG

Data analysis: CGF, PF, AP, SK, PD

Manuscript writing: CGF, PF, AP, JG, SK, PD

Footnotes

  • ↵* indicates a shared first-authorship (ordering alphabetically by surname)

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted December 08, 2018.
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New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia
Paolo Finotelli, Caroline Garcia Forlim, Paolo Dulio, Leonie Klock, Alessia Pini, Johanna Bächle, Laura Stoll, Patrick Giemsa, Marie Fuchs, Nikola Schoofs, Christiane Montag, Jürgen Gallinat, Simone Kühn
bioRxiv 489997; doi: https://doi.org/10.1101/489997
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New graph-theoretical-multimodal approach using temporal and structural correlations reveal disruption in the thalamo-cortical network in patients with schizophrenia
Paolo Finotelli, Caroline Garcia Forlim, Paolo Dulio, Leonie Klock, Alessia Pini, Johanna Bächle, Laura Stoll, Patrick Giemsa, Marie Fuchs, Nikola Schoofs, Christiane Montag, Jürgen Gallinat, Simone Kühn
bioRxiv 489997; doi: https://doi.org/10.1101/489997

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