Using Computational Phenotyping to Identify Divergent Strategies for Effort Allocation Across the Psychosis Spectrum.

Alexis E Whitton, Jessica A Cooper, Jaisal T Merchant, Michael T Treadway, Kathryn E Lewandowski
Author Information
  1. Alexis E Whitton: Black Dog Institute, University of New South Wales, Sydney, NSW, Australia.
  2. Jessica A Cooper: Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
  3. Jaisal T Merchant: Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA.
  4. Michael T Treadway: Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
  5. Kathryn E Lewandowski: Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA.

Abstract

BACKGROUND AND HYPOTHESIS: Disturbances in effort-cost decision-making have been highlighted as a potential transdiagnostic process underpinning negative symptoms in individuals with schizophrenia. However, recent studies using computational phenotyping show that individuals employ a range of strategies to allocate effort, and use of different strategies is associated with unique clinical and cognitive characteristics. Building on prior work in schizophrenia, this study evaluated whether effort allocation strategies differed in individuals with distinct psychotic disorders.
STUDY DESIGN: We applied computational modeling to effort-cost decision-making data obtained from individuals with psychotic disorders (n���=���190) who performed the Effort Expenditure for Rewards Task. The sample included 91 individuals with schizophrenia/schizoaffective disorder, 90 individuals with psychotic bipolar disorder, and 52 controls.
STUDY RESULTS: Different effort allocation strategies were observed both across and within different disorders. Relative to individuals with psychotic bipolar disorder, a greater proportion of individuals with schizophrenia/schizoaffective disorder did not use reward value or probability information to guide effort allocation. Furthermore, across disorders, different effort allocation strategies were associated with specific clinical and cognitive features. Those who did not use reward value or probability information to guide effort allocation had more severe positive and negative symptoms, and poorer cognitive and community functioning. In contrast, those who only used reward value information showed a trend toward more severe positive symptoms.
CONCLUSIONS: These findings indicate that similar deficits in effort-cost decision-making may arise from different computational mechanisms across the psychosis spectrum.

Keywords

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Grants

  1. F31 MH132276/NIMH NIH HHS
  2. K01 MH126308/NIMH NIH HHS
  3. R21MH110699/NIMH NIH HHS
  4. GNT1110773/National Health and Medical Research Council of Australia

MeSH Term

Humans
Psychotic Disorders
Schizophrenia
Bipolar Disorder
Adult
Male
Female
Decision Making
Phenotype
Middle Aged
Reward

Word Cloud

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