Computational phenotyping of aberrant belief updating in individuals with schizotypal traits and schizophrenia.
Biol Psychiatry
; 2024 Aug 30.
Article
in En
| MEDLINE
| ID: mdl-39218138
ABSTRACT
BACKGROUND:
Psychotic experiences are thought to emerge from various interrelated patterns of disrupted belief updating, such as overestimating the reliability of sensory information and misjudging task volatility. Yet, these substrates have never been jointly addressed under one computational framework and it is not clear to what degree they reflect trait-like computational patterns.METHODS:
We introduced a novel hierarchical Bayesian model that describes how individuals simultaneously update their beliefs about the task volatility and noise in observation. We applied this model to data from a modified Predictive inference task in a test-retest study with healthy volunteers (N=45, 4 sessions) and examined the relationship between model parameters and schizotypal traits in a larger online sample (N = 437) and in a cohort of patients with schizophrenia (N = 100).RESULTS:
The interclass correlations were moderate to high for model parameters and excellent for averaged belief trajectories and precision-weighted learning rates estimated through hierarchical Bayesian inference. We found that uncertainty about the task volatility was related to schizotypal traits and to positive symptoms in patients, when learning to gain rewards. In contrast, negative symptoms in patients were associated with more rigid beliefs about observational noise, when learning to avoid losses.CONCLUSION:
These findings suggest that individuals with schizotypal traits across the psychosis continuum are less likely to learn or utilize higher-order statistical regularities of the environment and showcase the potential of clinically relevant computational phenotypes for differentiating symptom groups in a transdiagnostic manner.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Biol Psychiatry
Year:
2024
Document type:
Article
Country of publication:
United States