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      Striatal dysfunction during reversal learning in unmedicated schizophrenia patients

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          Abstract

          Subjects with schizophrenia are impaired at reinforcement-driven reversal learning from as early as their first episode. The neurobiological basis of this deficit is unknown. We obtained behavioral and fMRI data in 24 unmedicated, primarily first episode, schizophrenia patients and 24 age-, IQ- and gender-matched healthy controls during a reversal learning task. We supplemented our fMRI analysis, focusing on learning from prediction errors, with detailed computational modeling to probe task solving strategy including an ability to deploy an internal goal directed model of the task. Patients displayed reduced functional activation in the ventral striatum (VS) elicited by prediction errors. However, modeling task performance revealed that a subgroup did not adjust their behavior according to an accurate internal model of the task structure, and these were also the more severely psychotic patients. In patients who could adapt their behavior, as well as in controls, task solving was best described by cognitive strategies according to a Hidden Markov Model. When we compared patients and controls who acted according to this strategy, patients still displayed a significant reduction in VS activation elicited by informative errors that precede salient changes of behavior (reversals). Thus, our study shows that VS dysfunction in schizophrenia patients during reward-related reversal learning remains a core deficit even when controlling for task solving strategies. This result highlights VS dysfunction is tightly linked to a reward-related reversal learning deficit in early, unmedicated schizophrenia patients.

          Highlights

          • Probabilistic reversal learning was examined in unmedicated schizophrenia patients.

          • Computational modeling assessed subjects ability to use the latent task structure.

          • SZ patients showed lower reinforcement sensitivity and higher switch tendency.

          • Blunted striatal prediction error signal in unmedicated schizophrenia patients.

          • PFC activation during reversal errors intact in SZ patients able to do the task.

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          Most cited references65

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          The assessment and analysis of handedness: The Edinburgh inventory

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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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              Psychosis as a state of aberrant salience: a framework linking biology, phenomenology, and pharmacology in schizophrenia.

              The clinical hallmark of schizophrenia is psychosis. The objective of this overview is to link the neurobiology (brain), the phenomenological experience (mind), and pharmacological aspects of psychosis-in-schizophrenia into a unitary framework. Current ideas regarding the neurobiology and phenomenology of psychosis and schizophrenia, the role of dopamine, and the mechanism of action of antipsychotic medication were integrated to develop this framework. A central role of dopamine is to mediate the "salience" of environmental events and internal representations. It is proposed that a dysregulated, hyperdopaminergic state, at a "brain" level of description and analysis, leads to an aberrant assignment of salience to the elements of one's experience, at a "mind" level. Delusions are a cognitive effort by the patient to make sense of these aberrantly salient experiences, whereas hallucinations reflect a direct experience of the aberrant salience of internal representations. Antipsychotics "dampen the salience" of these abnormal experiences and by doing so permit the resolution of symptoms. The antipsychotics do not erase the symptoms but provide the platform for a process of psychological resolution. However, if antipsychotic treatment is stopped, the dysregulated neurochemistry returns, the dormant ideas and experiences become reinvested with aberrant salience, and a relapse occurs. The article provides a heuristic framework for linking the psychological and biological in psychosis. Predictions of this hypothesis, particularly regarding the possibility of synergy between psychological and pharmacological therapies, are presented. The author describes how the hypothesis is complementary to other ideas about psychosis and also discusses its limitations.
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                Author and article information

                Contributors
                Journal
                Neuroimage
                Neuroimage
                Neuroimage
                Academic Press
                1053-8119
                1095-9572
                01 April 2014
                01 April 2014
                : 89
                : 100
                : 171-180
                Affiliations
                [a ]Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité — Universitätsmedizin Berlin, Germany
                [b ]Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
                [c ]Gatsby Computational Neuroscience Unit and Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK
                [d ]Translational Neuromodeling Unit, Department of Biomedical Engineering, ETH Zurich and University of Zurich, Switzerland
                [e ]Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich, Zurich, Switzerland
                [f ]Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, USA
                [g ]Leibniz Institute for Neurobiology, Otto-von-Guericke University, Magdeburg, Germany
                [h ]Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
                [i ]Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK
                [j ]Humboldt-Universität zu Berlin School of Mind and Brain, Berlin, Germany
                [k ]Cluster of Excellence NeuroCure, Charité-Universitätsmedizin Berlin, Berlin, Germany
                Author notes
                [* ]Corresponding author at: Department of Psychiatry and Psychotherapy, Charité — Universitätsmedizin Berlin, Campus Mitte, Charitéplatz 1, 10117 Berlin, Germany. Fax: + 49 30 450 517944. florian.schlagenhauf@ 123456charite.de
                [1]

                These authors contributed equally.

                Article
                S1053-8119(13)01158-0
                10.1016/j.neuroimage.2013.11.034
                3991847
                24291614
                208af980-606a-4886-a34a-379670e35828
                © 2013 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).

                History
                : 17 November 2013
                Categories
                Article

                Neurosciences
                schizophrenia,reversal learning,imaging,reward,ventral striatum,computational modeling
                Neurosciences
                schizophrenia, reversal learning, imaging, reward, ventral striatum, computational modeling

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