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Arch Gen Psychiatry. 2012 Mar;69(3):231-42. doi: 10.1001/archgenpsychiatry.2011.1349.

Disordered corticolimbic interactions during affective processing in children and adolescents at risk for schizophrenia revealed by functional magnetic resonance imaging and dynamic causal modeling.

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  • 1Division of Brain Research and Imaging Neuroscience, Department of Psychiatry and Behavioral Neuroscience, Wayne State University School of Medicine, Detroit, MI 48201, USA.



Disordered functional architecture of brain networks may contribute to the well-documented increased risk for psychiatric disorders in offspring of patients with schizophrenia.


To investigate aberrant interactions between regions associated with affective processing in children and adolescent offspring of patients with schizophrenia (HR-SCZ group) and healthy control subjects using dynamic causal modeling of functional magnetic resonance imaging data.


Subjects participated in a continuous affective processing task during which positive, negative, and neutral valenced faces were presented. Interactions between regions in the brain's face- and emotion-processing network were modeled using dynamic causal modeling. Multiple competing models were evaluated by a combinatorial approach and distinguished at the second level using Bayesian model selection before parameter inference.


Participants were recruited from the community.


Twenty-four controls with no family history of psychosis (to the second degree) and 19 children and adolescent offspring of a parent with schizophrenia (age range, 8 to 20 years).


Bayesian model selection revealed a winning model, the architecture of which revealed bidirectional frontolimbic connections that were modulated by valence. Analyses of parameter estimates revealed that HR-SCZ group members were characterized by (1) decreased driving inputs to the visual cortex; (2) decreased intrinsic coupling, most robustly between frontolimbic regions; and (3) increased modulatory inhibition by negative valence of frontolimbic connections (all P < .01, Bonferroni corrected).


These results are the first demonstration of network analyses techniques for functional magnetic resonance imaging data in children and adolescents at risk for schizophrenia. Dysfunctional interactions within the emotional processing network provide evidence of latent vulnerabilities that may confer risk for disordered adolescent development and eventually the emergence of the manifest disorder.

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