Misattributing speech and jumping to conclusions: A longitudinal study in people at high risk of psychosis

Winton-Brown, Toby; Broome, Matthew R.; Allen, Paul; Valli, Isabel; Howes, Oliver; Johns, Louise; McGuire, Philip

doi:10.1016/j.eurpsy.2014.09.416

Cited by 15 publications

(13 citation statements)

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“…Our finding of a liberal response bias and a high rate of false alarms associated with PEs is consistent with neurocognitive models of psychosis involving bias in data gathering, including the Jumping-To-Conclusions (JTC) model of delusions[ 84 – 86 ]. This reasoning bias has also been revealed in individuals at risk for psychosis[ 85 , 87 ] and in delusion-prone individuals[ 88 , 89 ], suggesting that data-gathering may be impaired before the onset of full-blown psychosis. Moreover, an association between JTC and WM has been reported[ 35 – 37 , 85 ] although this has not been addressed in terms of SDT.…”

Section: Discussionmentioning

confidence: 89%

Psychotic Experiences and Working Memory: A Population-Based Study Using Signal-Detection Analysis

et al. 2016

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Psychotic Experiences (PEs) during adolescence index increased risk for psychotic disorders and schizophrenia in adult life. Working memory (WM) deficits are a core feature of these disorders. Our objective was to examine the relationship between PEs and WM in a general population sample of young people in a case control study. 4744 individuals of age 17–18 from Bristol and surrounding areas (UK) were analyzed in a cross-sectional study nested within the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort study. The dependent variable was PEs, assessed using the semi-structured Psychosis-Like Symptom Interview (PLIKSi). The independent variable was performance on a computerized numerical n-back working memory task. Signal-Detection Theory indices, including standardized hits rate, false alarms rate, discriminability index (d’) and response bias (c) from 2-Back and 3-Back tasks were calculated. 3576 and 3527 individuals had complete data for 2-Back and 3-Back respectively. Suspected/definite PEs prevalence was 7.9% (N = 374). Strongest evidence of association was seen between PEs and false alarms on the 2-Back, (odds ratio (OR) = 1.17 [95% confidence intervals (CI) 1.01, 1.35]) and 3-back (OR = 1.35 [1.18, 1.54]) and with c (OR = 1.59 [1.09, 2.34]), and lower d’ (OR = 0.76 [0.65, 0.89]), on the 3-Back. Adjustment for several potential confounders, including general IQ, drug exposure and different psycho-social factors, and subsequent multiple imputation of missing data did not materially alter the results. WM is impaired in young people with PEs in the general population. False alarms, rather than poor accuracy, are more closely related to PEs. Such impairment is consistent with different neuropsychological models of psychosis focusing on signal-to-noise discrimination, probabilistic reasoning and impaired reality monitoring as a basis of psychotic symptoms.

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Section: Discussionmentioning

confidence: 89%

Psychotic Experiences and Working Memory: A Population-Based Study Using Signal-Detection Analysis

et al. 2016

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“…Collectively, our results indicate that associative learning under volatility in the ARMS is characterised by higher estimates of environmental volatility (as expressed at the behavioural level) and overly high low-level precision-weighted PE activations (at the neural level). These effects may reflect an enhanced tendency towards belief updating and might explain the empirically observed "jumping to conclusions" bias in ARMS individuals (Broome et al, 2007;Winton-Brown et al, 2015). More generally, this cognitive style may represent a risk factor for delusion proneness.…”

Section: Discussionmentioning

confidence: 91%

Atypical processing of uncertainty in individuals at risk for psychosis

Cole

Diaconescu

Pfeiffer

et al. 2019

Preprint

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Background: 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 at-risk mental state (ARMS) individuals.Methods: Non-medicated ARMS 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. Results: Computational modelling of ARMS 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 ARMS 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 ARMS was negatively associated with clinical measures of global functioning. Conclusions: Our results suggest a multi-faceted learning abnormality in ARMS 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.

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“…Thirteen studies analysed the association of subcortical cerebral abnormalities with the severity of psychotic symptoms (Allen et al, 2016) or of cerebral dysfunction, bias and cognitive deficits with the risk of transition (Allen et al, 2012;Bramon et al, 2008;M. R. Broome et al, 2012;Goghari et al, 2014;Higuchi et al, 2013Higuchi et al, , 2014Kotlicka-Antczak et al, 2017;Klauser et al, 2015;Modinos et al, 2014;Uchida et al, 2014;Winton-Brown et al, 2015), whereas another examined the predictive role of stress biomarkers in the psychotic transition (Labad et al, 2015).…”

Section: Physiopathological Dimensionmentioning

confidence: 99%

“…Broome et al, 2005;Demjaha et al, 2012;Fusar-Poli et al, 2013Hui et al, 2013;Ising, Kraan, et al, 2016;Ising, Ruhrmann, et al, 2016;Klauser et al, 2015;T. C. Kraan et al, 2017;Landa et al, 2016;Lee et al, 2013;Lim et al, 2015;Morcillo et al, 2015;Morrison et al, 2011;Rietdijk et al, 2010Rietdijk et al, , 2013Rutigliano et al, 2016;Spada et al, 2016;Valmaggia et al, 2014;Velthorst et al, 2012;Winton-Brown et al, 2015) (see Table 1). Only Table 1).…”

Section: Ethnicityunclassified

“…As such, it was explored by Rietdijk et al (2010) using the Dutch version of the ICSEY.Ethnicity was self-reported inAllen et al (2012). It was considered equivalent to the concept of nationality(Spada et al, 2016) but also to skin colour(Bramon et al, 2008;Brandizzi et al, 2015;Fusar- Poli et al, 2017;Valmaggia et al, 2014;Winton-Brown et al, 2015),. Other studies classified their populations within heterogeneous categories by continent or subcontinent of origin alone or combined with skin colour (M Broome et al, 2005;Demjaha et al, 2012;Fusar-Poli et al, 2013;Hui et al, 2013;Klauser et al, 2015;Landa et al, 2016;Lee et al, 2013;Lim et al, 2015;Morcillo et al, 2015;Morrison et al, 2011…”

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confidence: 99%

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Early intervention for everyone? A review of cross‐cultural issues and their treatment in ultra‐high‐risk (UHR) cohorts

Deriu

Moro

Benoit

2018

Early Intervention Psych

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This systematic review demonstrates barriers to the access to participation in early intervention research for migrants and ethnic minorities. This selection bias may result in lower validity for the CAARMS among these populations and thus in inadequate intervention programmes. Along with targeted studies, minorities' access to participation in UHR cohorts should be improved through 3 tools: interpreters at recruitment and for administration of CAARMS, a guide to cultural formulation and transcultural data collection.

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Misattributing speech and jumping to conclusions: A longitudinal study in people at high risk of psychosis

Cited by 15 publications

References 38 publications

Psychotic Experiences and Working Memory: A Population-Based Study Using Signal-Detection Analysis

Psychotic Experiences and Working Memory: A Population-Based Study Using Signal-Detection Analysis

Atypical processing of uncertainty in individuals at risk for psychosis

Early intervention for everyone? A review of cross‐cultural issues and their treatment in ultra‐high‐risk (UHR) cohorts

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