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Generative network models identify biological mechanisms of altered structural brain connectivity in schizophrenia [article]

Xiaolong Zhang, Urs Braun, Anais Harneit, Zhenxiang Zang, Lena Geiger, Richard Betzel, Junfang Chen, Janina Schweiger, Kristina Schwarz, Jonathan Rochus Reinwald, Stefan Fritze, Stephanie Witt (+8 others)
2019 bioRxiv   pre-print
Alterations in the structural connectome of schizophrenia patients have been widely characterized, but the mechanisms leading to those alterations remain largely unknown. Generative network models have recently been introduced as a tool to test the biological underpinnings of the formation of altered structural brain networks. Methods: We evaluated different generative network models to investigate the formation of structural brain networks in healthy controls (n=152), schizophrenia patients
more » ... 66) and their unaffected first-degree relatives (n=32), and we identified spatial and topological factors contributing to network formation. We further investigated the association of these factors to cognition and to polygenic risk for schizophrenia. Results: Structural brain networks can be best accounted for by a two-factor model combining spatial constraints and topological neighborhood structure. The same wiring model explained brain network formation for all groups analyzed. However, relatives and schizophrenia patients exhibited significantly lower spatial constraints and lower topological facilitation compared to healthy controls. The model parameter for spatial constraint was correlated with the polygenic risk for schizophrenia and predicted reduced cognitive performance. Conclusions: Our results identify spatial constraints and local topological structure as two interrelated mechanisms contributing to normal brain development as well as altered connectomes in schizophrenia. Spatial constraints were linked to the genetic risk for schizophrenia and general cognitive functioning, thereby providing insights into their biological basis and behavioral relevance.
doi:10.1101/604322 fatcat:om4rnp4kb5ebzlyrm47533tlam

Lateral habenula perturbation reduces default-mode network connectivity in a rat model of depression

Christian Clemm von Hohenberg, Wolfgang Weber-Fahr, Philipp Lebhardt, Namasivayam Ravi, Urs Braun, Natalia Gass, Robert Becker, Markus Sack, Alejandro Cosa Linan, Martin Fungisai Gerchen, Jonathan Rochus Reinwald, Lars-Lennart Oettl (+4 others)
2018 Translational Psychiatry  
Hyperconnectivity of the default-mode network (DMN) is one of the most widely replicated neuroimaging findings in major depressive disorder (MDD). Further, there is growing evidence for a central role of the lateral habenula (LHb) in the pathophysiology of MDD. There is preliminary neuroimaging evidence linking LHb and the DMN, but no causal relationship has been shown to date. We combined optogenetics and functional magnetic resonance imaging (fMRI), to establish a causal relationship, using
more » ... animal model of treatment-resistant depression, namely Negative Cognitive State rats. First, an inhibitory light-sensitive ion channel was introduced into the LHb by viral transduction. Subsequently, laser stimulation was performed during fMRI acquisition on a 9.4 Tesla animal scanner. Neural activity and connectivity were assessed, before, during and after laser stimulation. We observed a connectivity decrease in the DMN following laser-induced LHb perturbation. Our data indicate a causal link between LHb downregulation and reduction in DMN connectivity. These findings may advance our mechanistic understanding of LHb inhibition, which had previously been identified as a promising therapeutic principle, especially for treatment-resistant depression.
doi:10.1038/s41398-018-0121-y pmid:29581421 pmcid:PMC5913319 fatcat:a3edolaxvbcf3bmc6oh4g7jtx4

Network models of aberrant brain connectivity for elucidation of the pathophysiology of schizophrenia

Xiaolong Zhang
2021
Schweiger, Kristina Schwarz, Jonathan Rochus Reinwald, Stefan Fritze, Stephanie Witt, Marcella Rietschel, Markus M.  ... 
doi:10.11588/heidok.00030191 fatcat:onl5adiu3jacpi6hogtcwgdlwa