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Pathways from performance monitoring to negative symptoms and functional outcomes in psychotic disorders

Published online by Cambridge University Press:  22 April 2020

Dan Foti*
Affiliation:
Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
Greg Perlman
Affiliation:
Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
Evelyn J. Bromet
Affiliation:
Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
Philip D. Harvey
Affiliation:
University of Miami Miller School of Medicine, Miami, FL, USA
Greg Hajcak
Affiliation:
Department of Psychology and Biomedical Science, Florida State University, Tallahassee, FL, USA
Daniel H. Mathalon
Affiliation:
Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
Roman Kotov
Affiliation:
Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
*
Author for correspondence: Dan Foti, E-mail: foti@purdue.edu
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Abstract

Background

Performance monitoring entails rapid error detection to maintain task performance. Impaired performance monitoring is a candidate pathophysiological process in psychotic disorders, which may explain the broader deficit in executive function and its known associations with negative symptoms and poor functioning. The current study models cross-sectional pathways bridging neurophysiological measures of performance monitoring with executive function, symptoms, and functioning.

Methods

Data were from the 20-year assessment of the Suffolk County Mental Health Project. Individuals with psychotic disorders (N = 181) were originally recruited from inpatient psychiatric facilities. Data were also collected from a geographically and demographically matched group with no psychosis history (N = 242). Neural measures were the error-related negativity (ERN) and error positivity (Pe). Structural equation modeling tested mediation pathways.

Results

Blunted ERN and Pe in the clinical cohort related to impaired executive function (r = 0.26–0.35), negative symptom severity (r = 0.17–0.25), and poor real-world functioning (r = 0.17–0.19). Associations with executive function were consistent across groups. Multiple potential pathways were identified in the clinical cohort: reduced ERN to inexpressivity was mediated by executive function (β = 0.10); reduced Pe to global functioning was mediated by executive function and avolition (β = 0.10).

Conclusions

This supports a transdiagnostic model of psychotic disorders by which poor performance monitoring contributes to impaired executive function, which contributes to negative symptoms and poor real-world functioning. If supported by future longitudinal research, these pathways could inform the development of targeted interventions to address cognitive and functional deficits that are central to psychotic disorders.

Information

Type
Original Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press
Figure 0

Table 1. Sample characteristics

Figure 1

Fig. 1. ERP data. (a) Averaged waveforms for the ERN, presented separately for NP adults (top) and individuals with psychotic disorders (bottom). Scalp topographies are the error minus correct difference from 0 to 100 ms. (b) Averaged waveforms for the Pe. Scalp topographies are the difference from 300 to 500 ms. (c) Group means and standard errors of neural measures of performance monitoring across the psychosis spectrum.

Figure 2

Table 2. Cross-sectional associations of performance monitoring with clinical and neuropsychological measures among individuals with psychotic disorders

Figure 3

Fig. 2. Relationships between neural measures of performance monitoring and independent measures of executive function across the psychosis spectrum. Outcome is composite executive function score, combining the Stroop, Letter-Number Sequencing, and Trail Making (B) tests.

Figure 4

Fig. 3. Structural equation model of performance monitoring, cognitive impairment, negative symptoms, and everyday functioning among individuals with psychotic disorders (N = 181). All variables are observed (not latent constructs). Executive function is the composite of Trail Making (B), Letter-Number, and Stroop; Inexpressivity and Avolition are SANS subscales. Global functioning is the highest in the past year. Coefficients are completely standardized. All paths with solid lines are statistically significant (p's < 0.05).

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