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      Insular Dysfunction Reflects Altered Between-Network Connectivity and Severity of Negative Symptoms in Schizophrenia during Psychotic Remission

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          Abstract

          Schizophrenia is characterized by aberrant intrinsic functional connectivity (iFC) within and between intrinsic connectivity networks (ICNs), including the Default Mode- (DMN), Salience- (SN), and Central Executive Network (CEN). The anterior insula (AI) of the SN has been demonstrated to modulate DMN/CEN interactions. Recently, we found that the dependence of DMN/CEN interactions on SN’s right AI activity is altered in patients with schizophrenia in acute psychosis and related to psychotic symptoms, indicating a link between aberrant AI, DMN, CEN, and psychosis. However, since structural alterations of the insula are also present during psychotic remission and associated with negative symptoms, impaired AI interaction might be relevant even for psychotic remission and corresponding symptoms. Twelve patients with schizophrenia during psychotic remission (SR) and 12 healthy controls were assessed using resting-state fMRI and psychometric examination. High-model-order independent component analysis of fMRI data revealed ICNs including DMN, SN, and CEN. Scores of iFC within (intra-iFC) and between (inter-iFC) distinct subsystems of the DMN, SN, and CEN were calculated, compared between groups and correlated with the severity of symptoms. Intra-iFC was altered in patients’ SN, DMN, and CEN, including decreased intra-iFC in the left AI within the SN. Patients’ inter-iFC between SN and CEN was increased and correlated with the severity of negative symptoms. Furthermore, decreased intra-iFC of the left AI correlated with both severity of negative symptoms and increased inter-iFC between SN and CEN. Our result provides first evidence for a relationship between AI dysfunction and altered between-network interactions in schizophrenia during psychotic remission, which is related to the severity of negative symptoms. Together with our previous results, data suggest specific SN/DMN/CEN reorganization in schizophrenia with distinct insular pathways for distinct symptom dimensions.

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          Most cited references29

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          The positive and negative syndrome scale (PANSS) for schizophrenia.

          The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
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            Correspondence of the brain's functional architecture during activation and rest.

            Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is "at rest." In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically "active" even when at "rest."
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              Unified segmentation

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                Author and article information

                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                20 May 2013
                2013
                : 7
                : 216
                Affiliations
                [1] 1Department of Psychiatry, Klinikum Rechts der Isar, Technische Universität München Munich, Germany
                [2] 2Department of Neuroradiology, Klinikum Rechts der Isar, Technische Universität München Munich, Germany
                [3] 3TUM-Neuroimaging Center, Technische Universität München Munich, Germany
                [4] 4Department of Nuclear Medicine, Klinikum Rechts der Isar, Technische Universität München Munich, Germany
                [5] 5Department of Neurology, Klinikum Rechts der Isar, Technische Universität München Munich, Germany
                [6] 6Munich Center for Neurosciences Brain & Mind, Ludwig-Maximilians-Universität München Munich, Germany
                [7] 7Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University Salzburg Salzburg, Austria
                Author notes

                Edited by: Veronika Schöpf, Medical University Vienna, Austria

                Reviewed by: Ayna Baladi Nejad, Brain and Spine Institute, France; Lena Palaniyappan, University of Nottingham, UK

                *Correspondence: Andrei Manoliu, Department of Psychiatry and Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Ismaningerstrasse 22, 81675 München, Germany. e-mail: a.manoliu@ 123456googlemail.com
                Article
                10.3389/fnhum.2013.00216
                3657709
                23730284
                427d92ac-87f0-4ec8-95f8-193bf1fc2c1c
                Copyright © 2013 Manoliu, Riedl, Doll, Bäuml, Mühlau, Schwerthöffer, Scherr, Zimmer, Förstl, Bäuml, Wohlschläger, Koch and Sorg.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 28 February 2013
                : 06 May 2013
                Page count
                Figures: 5, Tables: 8, Equations: 0, References: 55, Pages: 16, Words: 11388
                Categories
                Neuroscience
                Original Research

                Neurosciences
                schizophrenia,remission,anterior insula,salience network,default mode network,central executive network

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