Atypical processing of uncertainty in individuals at risk for psychosis

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

Self-Reported Psychotic-Like Experiences Are a Poor Estimate of Clinician-Rated Attenuated and Frank Delusions and Hallucinations

Background: One reason for the decision to delay the introduction of an Attenuated Psychosis Syndrome in the main text of the fifth edition of the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders was the concern that attenuated psychotic symptoms (APS) might in fact be common features in adolescents and young adults from the general population of no psychopathological significance in themselves. This concern was based on reports of high prevalence rates of psychotic-like experiences (PLEs) in the general population and the assumption that PLEs are a good estimate of APS. Although the criterion validity of self-reported PLEs had already been studied with respect to clinician-rated psychotic symptoms and found insufficient, it had been argued that PLEs might in fact be more comparable with mild, subclinical expressions of psychotic symptoms and, therefore, with APS. The present paper is the first to specifically study this assumption. Sampling and Methods: The sample consisted of 123 persons seeking help at a service for the early detection of psychosis, of whom 54 had an at-risk mental state or psychosis, 55 had a nonpsychotic mental disorder and 14 had no full-blown mental disorder. PLEs were assessed with the Peters Delusion Inventory and the revised Launay-Slade Hallucination Scale, and psychotic symptoms and APS were assessed with the Structured Interview for Prodromal Syndromes. Results: At a level of agreement between the presence of any PLE (in 98.4% of patients) and any APS (in 40.7%) just exceeding chance (κ = 0.022), the criterion validity of PLEs for APS was insufficient. Even if additional qualifiers (high agreement or distress, preoccupation and conviction) were considered, PLEs (in 52.8%) still tended to significantly overestimate APS, and agreement was only fair (κ = 0.340). Furthermore, the group effect on PLE prevalence was, at most, moderate (Cramer's V ≤ 0.382). Conclusions: The prevalence of APS cannot be deduced from studies of PLEs. Thus, the high population prevalence rate of PLEs does not allow the conclusion that APS are common features of no pathological significance and would lack clinical validity as an Attenuated Psychosis Syndrome in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition. Rather, the population prevalence rate of APS has to be assumed to be largely unknown at present but is likely lower than indicated by epidemiological studies of PLEs. Therefore, dedicated studies are warranted, in which APS are assessed in a way that equates to their clinical evaluation

Chances and risks of predicting psychosis

Prevention is currently regarded a promising strategy for fighting the unfavorable consequences of psychosis. Yet, for the error probability inherent in any predictive approach, benefits and costs must be carefully weighed against each other. False attribution of risk may unnecessarily provoke stress and anxiety, and lead to unwarranted intervention exposure. However, clinical risk samples already exhibit psychopathological symptoms, cognitive and functional impairments, and help-seeking for mental problems. Thus, the risk of futile interventions is low as long as preventive measures also provide treatment for current complaints. Differentiation between still normal and clinically relevant mental states is another challenge as psychotic-like phenomena occur frequently in the general population, especially in younger adolescents. Reported prevalence rates vary with age, and if severe in terms of frequency and persistence, these phenomena considerably increase risk of psychosis in clinical as well as general population samples. Stigmatization is another concern, though insufficiently studied. Yet, at least more severe states of risk, which are accompanied by changes in thinking, feeling, and behavior, might lead to unfavorable, (self-) stigmatizing effects already by themselves, independent of any diagnostic label, and to stress and confusion for the lack of understanding of what is going on. To further improve validity of risk criteria, advanced risk algorithms combining multi-step detection and risk stratification procedures should be developed. However, all prediction models possess a certain error probability. Thus, whether a risk model justifies preventive measures can only be decided by weighing the costs of unnecessary intervention and the benefits of avoiding a potentially devastating outcome

Efficient Implementation of Application-Aware Spinlock Control in MPSoCs

Recent years have seen considerable progress in epidemiological and molecular genetic research into environmental and genetic factors in schizophrenia, but methodological uncertainties remain with regard to validating environmental exposures, and the population risk conferred by individual molecular genetic variants is small. There are now also a limited number of studies that have investigated molecular genetic candidate gene-environment interactions (G × E), however, so far, thorough replication of findings is rare and G × E research still faces several conceptual and methodological challenges. In this article, we aim to review these recent developments and illustrate how integrated, large-scale investigations may overcome contemporary challenges in G × E research, drawing on the example of a large, international, multi-center study into the identification and translational application of G × E in schizophrenia. While such investigations are now well underway, new challenges emerge for G × E research from late-breaking evidence that genetic variation and environmental exposures are, to a significant degree, shared across a range of psychiatric disorders, with potential overlap in phenotyp