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Comprehensive review: Computational modelling of schizophrenia. Neurosci Biobehav Rev 2017; 83:631-646. [PMID: 28867653 DOI: 10.1016/j.neubiorev.2017.08.022] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Revised: 07/08/2017] [Accepted: 08/30/2017] [Indexed: 12/21/2022]
Abstract
Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behavior (e.g. Bayesian models - top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist and neural networks - bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i.e. understanding behavioral vs. neurobiological anomalies) about the nature of the disorder. As such, these computational studies have mostly supported diverging hypotheses of schizophrenia's pathophysiology, resulting in a literature that is not always expanding coherently. Some of these hypotheses are however ripe for revision using novel empirical evidence. Here we present a review that first synthesizes the literature of computational modelling for schizophrenia and psychotic symptoms into categories supporting the dopamine, glutamate, GABA, dysconnection and Bayesian inference hypotheses respectively. Secondly, we compare model predictions against the accumulated empirical evidence and finally we identify specific hypotheses that have been left relatively under-investigated.
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Talamini LM, Meeter M. Dominance of objects over context in a mediotemporal lobe model of schizophrenia. PLoS One 2009; 4:e6505. [PMID: 19652706 PMCID: PMC2714963 DOI: 10.1371/journal.pone.0006505] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2009] [Accepted: 06/04/2009] [Indexed: 11/19/2022] Open
Abstract
Background A large body of evidence suggests impaired context processing in schizophrenia. Here we propose that this impairment arises from defective integration of mediotemporal ‘what’ and ‘where’ routes, carrying object and spatial information to the hippocampus. Methodology and Findings We have previously shown, in a mediotemporal lobe (MTL) model, that the abnormal connectivity between MTL regions observed in schizophrenia can explain the episodic memory deficits associated with the disorder. Here we show that the same neuropathology leads to several context processing deficits observed in patients with schizophrenia: 1) failure to choose subordinate stimuli over dominant ones when the former fit the context, 2) decreased contextual constraints in memory retrieval, as reflected in increased false alarm rates and 3) impaired retrieval of contextual information in source monitoring. Model analyses show that these deficits occur because the ‘schizophrenic MTL’ forms fragmented episodic representations, in which objects are overrepresented at the expense of spatial contextual information. Conclusions and Significance These findings highlight the importance of MTL neuropathology in schizophrenia, demonstrating that it may underlie a broad spectrum of deficits, including context processing and memory impairments. It is argued that these processing deficits may contribute to central schizophrenia symptoms such as contextually inappropriate behavior, associative abnormalities, conversational drift, concreteness and delusions.
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Affiliation(s)
- Lucia M Talamini
- Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
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Coscia DM, Narr KL, Robinson DG, Hamilton LS, Sevy S, Burdick KE, Gunduz‐Bruce H, McCormack J, Bilder RM, Szeszko PR. Volumetric and shape analysis of the thalamus in first-episode schizophrenia. Hum Brain Mapp 2009; 30:1236-45. [PMID: 18570200 PMCID: PMC6870587 DOI: 10.1002/hbm.20595] [Citation(s) in RCA: 44] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2007] [Revised: 03/11/2008] [Accepted: 03/20/2008] [Indexed: 01/17/2023] Open
Abstract
Thalamic abnormalities have been implicated in the pathogenesis of schizophrenia, although the majority of studies used chronic samples treated extensively with antipsychotics. Moreover, the clinical and neuropsychological correlates of these abnormalities remain largely unknown. Using high-resolution MR imaging and novel methods for shape analysis, we investigated thalamic subregions in 35 (25 M/10 F) first-episode schizophrenia patients compared with 33 (23 M/10 F) healthy volunteers. The right and left thalami were traced bilaterally on coronal brain slices and volumes were compared between groups. In addition, regional abnormalities were identified by comparing distances, measured from homologous thalamic surface points to the central core of each individual's surface model, between groups in 3D space. Patients had significantly less total thalamic volume compared with healthy volunteers. Statistical mapping demonstrated most pronounced shape abnormalities in the pulvinar; however, estimated false discovery rates in these regions were sizable. Smaller thalamus volume was significantly correlated with worse overall neuropsychological functioning and specific deficits were observed in the language, motor, and executive domains. There were no significant associations between thalamus volume and positive or negative symptoms. Our findings suggest that thalamic abnormalities are evident at the onset of a first episode of schizophrenia prior to extensive pharmacologic intervention and that these abnormalities have neuropsychological correlates.
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Affiliation(s)
- Denise M. Coscia
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore ‐ Long Island Jewish Health System, Glen Oaks, New York
| | - Katherine L. Narr
- Departments of Neurology, Psychiatry and Biobehavioral Sciences, UCLA Geffen School of Medicine, Los Angeles, California
| | - Delbert G. Robinson
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore ‐ Long Island Jewish Health System, Glen Oaks, New York
- Department of Psychiatry, Albert Einstein College of Medicine, Bronx, New York
- Feinstein Institute for Medical Research, North Shore – Long Island Jewish Health System, Manhasset, New York
| | - Liberty S. Hamilton
- Departments of Neurology, Psychiatry and Biobehavioral Sciences, UCLA Geffen School of Medicine, Los Angeles, California
| | - Serge Sevy
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore ‐ Long Island Jewish Health System, Glen Oaks, New York
- Department of Psychiatry, Albert Einstein College of Medicine, Bronx, New York
| | - Katherine E. Burdick
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore ‐ Long Island Jewish Health System, Glen Oaks, New York
- Department of Psychiatry, Albert Einstein College of Medicine, Bronx, New York
- Feinstein Institute for Medical Research, North Shore – Long Island Jewish Health System, Manhasset, New York
| | - Handan Gunduz‐Bruce
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Joanne McCormack
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore ‐ Long Island Jewish Health System, Glen Oaks, New York
| | - Robert M. Bilder
- Departments of Neurology, Psychiatry and Biobehavioral Sciences, UCLA Geffen School of Medicine, Los Angeles, California
| | - Philip R. Szeszko
- Division of Psychiatry Research, The Zucker Hillside Hospital, North Shore ‐ Long Island Jewish Health System, Glen Oaks, New York
- Department of Psychiatry, Albert Einstein College of Medicine, Bronx, New York
- Feinstein Institute for Medical Research, North Shore – Long Island Jewish Health System, Manhasset, New York
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