Atypical processing of uncertainty in individuals at risk for psychosis

•Humans at psychosis clinical high risk (CHR) over-estimate environmental volatility.•Low-level prediction error (PE) signals evoke increased frontal activity in CHR.•Volatility-related PEs are associated with reduced frontal activity in CHR.•Frontal cortical activation to low-level PEs reflects imp...

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Veröffentlicht in:NeuroImage clinical 2020-01, Vol.26, p.102239, Article 102239
Hauptverfasser: Cole, David M., Diaconescu, Andreea O., Pfeiffer, Ulrich J., Brodersen, Kay H., Mathys, Christoph D., Julkowski, Dominika, Ruhrmann, Stephan, Schilbach, Leonhard, Tittgemeyer, Marc, Vogeley, Kai, Stephan, Klaas E.
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Sprache:eng
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Zusammenfassung:•Humans at psychosis clinical high risk (CHR) over-estimate environmental volatility.•Low-level prediction error (PE) signals evoke increased frontal activity in CHR.•Volatility-related PEs are associated with reduced frontal activity in CHR.•Frontal cortical activation to low-level PEs reflects impaired clinical functioning.•Atypical PE learning signal representations may promote delusion formation in CHR. Current theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in clinical high risk (CHR) individuals. Non-medicated CHR individuals (n = 13) and control participants (n = 13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour – with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental ‘volatility’ – and used these computational quantities for analyses of fMRI data. Computational modelling of CHR individuals’ behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of CHR individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in CHR was negatively associated with clinical measures of global functioning. Our results suggest a multi-faceted learning abnormality in CHR individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation.
ISSN:2213-1582
2213-1582
DOI:10.1016/j.nicl.2020.102239