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      What Can Different Motor Circuits Tell Us About Psychosis? An RDoC Perspective

      , ,
      Schizophrenia Bulletin
      Oxford University Press (OUP)

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          Abstract

          <p id="d6858577e192">Signs of motor dysfunction are evidenced across a range of psychiatric disorders including schizophrenia. Historically, these features have been neglected but emerging theoretical and methodological advancements have shed new light on the utility of considering movement abnormalities. Indeed, the National Institute of Mental Health Research Domain Criteria initiative has recently met to develop a <i>Motor Systems</i> Domain. This reflects a growing appreciation for the enhanced reliability and validity that can come along with evaluating disturbances relevant to psychiatric illnesses from multiple levels of analysis, and conceptualizing these domains with respect to the complexity of their role in a broader integrated system (ie, weighing contributions and interactions between the cognitive, affective, and motor domains). This article discusses motor behaviors and seeks to explain how research into basal ganglia, cerebellar, and cortico-motor circuit function/dysfunction, grounded in brain circuit-motor behavior relationships, can elucidate our understanding of pathophysiology, provide vital links to other key systems of interest, significantly improve identification and classification, and drive development of targeted individualized treatments. </p>

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          Most cited references67

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          Research domain criteria (RDoC): toward a new classification framework for research on mental disorders.

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            Large-scale brain networks and psychopathology: a unifying triple network model.

            The science of large-scale brain networks offers a powerful paradigm for investigating cognitive and affective dysfunction in psychiatric and neurological disorders. This review examines recent conceptual and methodological developments which are contributing to a paradigm shift in the study of psychopathology. I summarize methods for characterizing aberrant brain networks and demonstrate how network analysis provides novel insights into dysfunctional brain architecture. Deficits in access, engagement and disengagement of large-scale neurocognitive networks are shown to play a prominent role in several disorders including schizophrenia, depression, anxiety, dementia and autism. Synthesizing recent research, I propose a triple network model of aberrant saliency mapping and cognitive dysfunction in psychopathology, emphasizing the surprising parallels that are beginning to emerge across psychiatric and neurological disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              Control of mental activities by internal models in the cerebellum.

              Masao ITO (2008)
              The intricate neuronal circuitry of the cerebellum is thought to encode internal models that reproduce the dynamic properties of body parts. These models are essential for controlling the movement of these body parts: they allow the brain to precisely control the movement without the need for sensory feedback. It is thought that the cerebellum might also encode internal models that reproduce the essential properties of mental representations in the cerebral cortex. This hypothesis suggests a possible mechanism by which intuition and implicit thought might function and explains some of the symptoms that are exhibited by psychiatric patients. This article examines the conceptual bases and experimental evidence for this hypothesis.
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                Author and article information

                Journal
                Schizophrenia Bulletin
                Oxford University Press (OUP)
                0586-7614
                1745-1701
                September 2017
                September 01 2017
                July 04 2017
                September 2017
                September 01 2017
                July 04 2017
                : 43
                : 5
                : 949-955
                Article
                10.1093/schbul/sbx087
                5581904
                28911048
                e198be1f-7e52-4460-a360-820dc46c8f37
                © 2017
                History

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