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

Roy Salomon, Oliver Alan Kannape, Henrique Galvan Debarba, Mariia Kaliuzhna, Maude Schneider, Nathan Faivre, Stephan Eliez, Olaf Blanke

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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.

Original languageEnglish
Pages (from-to)495-504
Number of pages10
JournalSchizophrenia Bulletin
Volume48
Issue number2
Early online dateDec 2021
DOIs
StatePublished - 1 Mar 2022

Bibliographical note

Publisher Copyright:
© 2021 The Author(s). Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Keywords

  • Locomotion
  • Psychosis
  • Sense of agency
  • Sensorimotor prediction
  • Velocardiofacial syndrome
  • Virtual reality

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