49
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Agency Deficits in a Human Genetic Model of Schizophrenia: Insights From 22q11DS Patients

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Schizophrenia is a chronic and disabling mental illness characterized by a disordered sense of self. Current theories suggest that deficiencies in the sense of control over one’s actions (Sense of Agency, SoA) may underlie some of the symptoms of schizophrenia. However, it is not clear if agency deficits are a precursor or a result of psychosis. Here, we investigated full body agency using virtual reality in a cohort of 22q11 deletion syndrome participants with a genetic propensity for schizophrenia. In two experiments employing virtual reality, full body motion tracking, and online feedback, we investigated SoA in two separate domains. Our results show that participants with 22q11DS had a considerable deficit in monitoring their actions, compared to age-matched controls in both the temporal and spatial domain. This was coupled with a bias toward erroneous attribution of actions to the self. These results indicate that nonpsychotic 22q11DS participants have a domain general deficit in the conscious sensorimotor mechanisms underlying the bodily self. Our data reveal an abnormality in the SoA in a cohort with a genetic predisposition for schizophrenia, but without psychosis, providing evidence that deficits in delineation of the self may be a precursor rather than a result of the psychotic state.

          Related collections

          Most cited references89

          • Record: found
          • Abstract: not found
          • Article: not found

          lmerTest Package: Tests in Linear Mixed Effects Models

            Bookmark
            • Record: found
            • Abstract: not found
            • Book: not found

            ggplot2

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found
              Is Open Access

              Fitting Linear Mixed-Effects Models Using lme4

              Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
                Bookmark

                Author and article information

                Journal
                Schizophr Bull
                Schizophr Bull
                schbul
                Schizophrenia Bulletin
                Oxford University Press (US )
                0586-7614
                1745-1701
                March 2022
                22 December 2021
                22 December 2021
                : 48
                : 2
                : 495-504
                Affiliations
                [1 ] Gonda Multidisciplinary Brain Research Center, Bar Ilan University (BIU) , Ramat-Gan, Israel
                [2 ] Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL) , Lausanne, Switzerland
                [3 ] Department of Digital Design, IT University of Copenhagen , Copenhagen, Denmark
                [4 ] Immersive Interaction Group, Ecole Polytechnique Fédérale de Lausanne (EPFL) , Lausanne, Switzerland
                [5 ] Clinical and Experimental Psychopathology Group, Department of Psychiatry, University of Geneva , Geneva, Switzerland
                [6 ] Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, University of Geneva , Geneva, Switzerland
                [7 ] Clinical Psychology Unit for Intellectual and Developmental Disabilities, Faculty of Psychology and Educational Sciences, University of Geneva , Geneva, Switzerland
                [8 ] Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC , Grenoble, France
                [9 ] Department of Clinical Neurosciences, Faculty of Medicine, University Hospital , Geneva, Switzerland
                Author notes

                Contributed equally.

                To whom correspondence should be addressed; Laboratory of Cognitive Neuroscience, Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, CH-1202 Geneva, Switzerland; tel: +41 21 693 96 21, e-mail: olaf.blanke@ 123456epfl.ch
                Author information
                https://orcid.org/0000-0002-6688-617X
                https://orcid.org/0000-0002-2930-4118
                https://orcid.org/0000-0001-6011-4921
                Article
                sbab143
                10.1093/schbul/sbab143
                8886583
                34935960
                62b998ca-92f3-419c-bb2b-93a75ec41d52
                © The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Page count
                Pages: 10
                Funding
                Funded by: Swiss National Science Foundation Project Funding;
                Award ID: 144260
                Award ID: 159968
                Funded by: SNSF National Center of Competence in Research;
                Award ID: 185897
                Funded by: Bertarelli Foundation, DOI 10.13039/100009152;
                Categories
                Regular Articles
                AcademicSubjects/MED00810

                Neurology
                sense of agency,velocardiofacial syndrome,sensorimotor prediction,virtual reality,psychosis,locomotion

                Comments

                Comment on this article