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      Dysconnection in Schizophrenia: From Abnormal Synaptic Plasticity to Failures of Self-monitoring

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          Abstract

          Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl- D-aspartate receptor (NMDAR)–mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia.

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          The MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and validity.

          The lack of an accepted standard for measuring cognitive change in schizophrenia has been a major obstacle to regulatory approval of cognition-enhancing treatments. A primary mandate of the National Institute of Mental Health's Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative was to develop a consensus cognitive battery for clinical trials of cognition-enhancing treatments for schizophrenia through a broadly based scientific evaluation of measures. The MATRICS Neurocognition Committee evaluated more than 90 tests in seven cognitive domains to identify the 36 most promising measures. A separate expert panel evaluated the degree to which each test met specific selection criteria. Twenty tests were selected as a beta battery. The beta battery was administered to 176 individuals with schizophrenia and readministered to 167 of them 4 weeks later so that the 20 tests could be compared directly. The expert panel ratings are presented for the initially selected 36 tests. For the beta battery tests, data on test-retest reliability, practice effects, relationships to functional status, practicality, and tolerability are presented. Based on these data, 10 tests were selected to represent seven cognitive domains in the MATRICS Consensus Cognitive Battery. The structured consensus method was a feasible and fair mechanism for choosing candidate tests, and direct comparison of beta battery tests in a common sample allowed selection of a final consensus battery. The MATRICS Consensus Cognitive Battery is expected to be the standard tool for assessing cognitive change in clinical trials of cognition-enhancing drugs for schizophrenia. It may also aid evaluation of cognitive remediation strategies.
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            Dynamic causal modelling.

            In this paper we present an approach to the identification of nonlinear input-state-output systems. By using a bilinear approximation to the dynamics of interactions among states, the parameters of the implicit causal model reduce to three sets. These comprise (1) parameters that mediate the influence of extrinsic inputs on the states, (2) parameters that mediate intrinsic coupling among the states, and (3) [bilinear] parameters that allow the inputs to modulate that coupling. Identification proceeds in a Bayesian framework given known, deterministic inputs and the observed responses of the system. We developed this approach for the analysis of effective connectivity using experimentally designed inputs and fMRI responses. In this context, the coupling parameters correspond to effective connectivity and the bilinear parameters reflect the changes in connectivity induced by inputs. The ensuing framework allows one to characterise fMRI experiments, conceptually, as an experimental manipulation of integration among brain regions (by contextual or trial-free inputs, like time or attentional set) that is revealed using evoked responses (to perturbations or trial-bound inputs, like stimuli). As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling (cf., psychophysiologic interactions). However, unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
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              Cortical inhibitory neurons and schizophrenia.

              Impairments in certain cognitive functions, such as working memory, are core features of schizophrenia. Convergent findings indicate that a deficiency in signalling through the TrkB neurotrophin receptor leads to reduced GABA (gamma-aminobutyric acid) synthesis in the parvalbumin-containing subpopulation of inhibitory GABA neurons in the dorsolateral prefrontal cortex of individuals with schizophrenia. Despite both pre- and postsynaptic compensatory responses, the resulting alteration in perisomatic inhibition of pyramidal neurons contributes to a diminished capacity for the gamma-frequency synchronized neuronal activity that is required for working memory function. These findings reveal specific targets for therapeutic interventions to improve cognitive function in individuals with schizophrenia.
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                Author and article information

                Journal
                Schizophr Bull
                schbul
                schbul
                Schizophrenia Bulletin
                Oxford University Press
                0586-7614
                1745-1701
                May 2009
                20 January 2009
                20 January 2009
                : 35
                : 3
                : 509-527
                Affiliations
                [2 ]Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK
                [3 ]Laboratory for Social and Neural Systems Research, Institute for Empirical Research in Economics, University of Zurich, Zurich, Switzerland
                [4 ]Centre of Functionally Integrative Neuroscience (CFIN), Aarhus University Hospital, 8000-Aarhus, Denmark
                Author notes
                [1 ]To whom correspondence should be addressed; tel: +44-207-8337472, fax: +44-207-8131420, e-mail: k.stephan@ 123456fil.ion.ucl.ac.uk .
                Article
                10.1093/schbul/sbn176
                2669579
                19155345
                6f6d68fc-5a13-481a-ae1c-44cfceb1b8fe
                Published by Oxford University Press 2009.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Categories
                Theme: Theories of Schizophrenia: Explanatory Power and Inferential Strength Guest Editors: Angus MacDonald and S. Charles Schulz

                Neurology
                hallucinations,acetylcholine,serotonin,nmda,psychosis,dynamic causal modeling,predictive coding,corollary discharge,dysconnectivity,effective connectivity,delusions,dopamine,dcm

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