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      A Dynamical Systems Hypothesis of Schizophrenia

      research-article
      1 , 2 , * , 1 , 3
      PLoS Computational Biology
      Public Library of Science

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          Abstract

          We propose a top-down approach to the symptoms of schizophrenia based on a statistical dynamical framework. We show that a reduced depth in the basins of attraction of cortical attractor states destabilizes the activity at the network level due to the constant statistical fluctuations caused by the stochastic spiking of neurons. In integrate-and-fire network simulations, a decrease in the NMDA receptor conductances, which reduces the depth of the attractor basins, decreases the stability of short-term memory states and increases distractibility. The cognitive symptoms of schizophrenia such as distractibility, working memory deficits, or poor attention could be caused by this instability of attractor states in prefrontal cortical networks. Lower firing rates are also produced, and in the orbitofrontal and anterior cingulate cortex could account for the negative symptoms, including a reduction of emotions. Decreasing the GABA as well as the NMDA conductances produces not only switches between the attractor states, but also jumps from spontaneous activity into one of the attractors. We relate this to the positive symptoms of schizophrenia, including delusions, paranoia, and hallucinations, which may arise because the basins of attraction are shallow and there is instability in temporal lobe semantic memory networks, leading thoughts to move too freely round the attractor energy landscape.

          Author Summary

          One of the hallmarks of schizophrenia is the complexity and heterogeneity of the illness. We propose that part of the reason for the inconsistent symptoms may be a reduced signal-to-noise ratio and increased statistical fluctuations in different cortical brain networks. The novelty of the approach described here is that instead of basing our hypothesis purely on biological mechanisms, we develop a top-down approach based on the different types of symptoms and relate them to instabilities in attractor neural networks. Schizophrenia is characterized by cognitive, negative, and positive symptoms. We propose which characteristic effects in a dynamical system could cause these symptoms, and investigate our hypothesis in a computational model. We implement an integrate-and-fire network model and focus on the alterations of synaptic channels activated via NMDA and GABA receptors. We found that a decrease in the NMDA receptor conductance could contribute to both the cognitive and negative symptoms by reducing the neuronal firing rates and the stability of the attractor states. A reduction of both NMDA and GABA conductance causes an instability of the attractor states related to the positive symptoms. Overall, we provide a framework to discuss schizophrenia in a dynamical system framework.

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          Most cited references82

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          Neural networks and physical systems with emergent collective computational abilities.

          J Hopfield (1982)
          Computational properties of use of biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.
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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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              What are the functional consequences of neurocognitive deficits in schizophrenia?

              M. Green (1996)
              It has been well established that schizophrenic patients have neurocognitive deficits, but it is not known how these deficits influence the daily lives of patients. The goal of this review was to determine which, if any, neurocognitive deficits restrict the functioning of schizophrenic patients in the outside world. The author reviewed studies that have evaluated neurocognitive measures as predictors and correlates of functional outcome for schizophrenic patients. The review included 1) studies that have prospectively evaluated specific aspects of neurocognition and community (e.g., social and vocational) functioning (six studies), 2) all known studies of neurocognitive correlates of social problem solving (five studies), and 3) all known studies of neurocognitive correlates and predictors of psychosocial skill acquisition (six studies). Despite wide variation among studies in the selection of neurocognitive measures, some consistencies emerged. The most consistent finding was that verbal memory was associated with all types of functional outcome. Vigilance was related to social problem solving and skill acquisition. Card sorting predicted community functioning but not social problem solving. Negative symptoms were associated with social problem solving but not skill acquisition. Notably, psychotic symptoms were not significantly associated with outcome measures in any of the studies reviewed. Verbal memory and vigilance appear to be necessary for adequate functional outcome. Deficiencies in these areas may prevent patients from attaining optimal adaptation and hence act as "neurocognitive rate-limiting factors." On the basis of this review of the literature, a series of hypotheses are offered for follow-up studies.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                pcbi
                plcb
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                November 2007
                9 November 2007
                : 3
                : 11
                : e228
                Affiliations
                [1 ] Department of Technology, Universitas Pompeu Fabra, Barcelona, Spain
                [2 ] Department of Experimental Psychology, University of Oxford, Oxford, United Kindgom
                [3 ] Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
                University College London, United Kingdom
                Author notes
                * To whom correspondence should be addressed. E-mail: Edmund.Rolls@ 123456psy.ox.ac.uk
                Article
                07-PLCB-RA-0373R2 plcb-03-11-14
                10.1371/journal.pcbi.0030228
                2065887
                17997599
                0d077efa-01b1-4c77-8166-66c0a2a15259
                Copyright: © 2007 Loh et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 2 July 2007
                : 3 October 2007
                Page count
                Pages: 11
                Categories
                Research Article
                Neuroscience
                Homo (Human)
                Schizophrenia
                Attractor Networks
                Neuronal Networks
                Spiking Dynamics
                Custom metadata
                Loh M, Rolls ET, Deco G (2007) A dynamical systems hypothesis of schizophrenia. PLoS Comput Biol 3(11): e228. doi: 10.1371/journal.pcbi.0030228

                Quantitative & Systems biology
                Quantitative & Systems biology

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