Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training

BACKGROUND AND HYPOTHESIS: In a complex world, gathering information and adjusting our beliefs about the world is of paramount importance. The literature suggests that patients with psychotic disorders display a tendency to draw early conclusions based on limited evidence, referred to as the jumping-to-conclusions bias, but few studies have examined the computational mechanisms underlying this and related belief-updating biases. Here, we employ a computational approach to understand the relationship between jumping-to-conclusions, psychotic disorders, and delusions. STUDY DESIGN: We modeled probabilistic reasoning of 261 patients with psychotic disorders and 56 healthy controls during an information sampling task-the fish task-with the Hierarchical Gaussian Filter. Subsequently, we examined the clinical utility of this computational approach by testing whether computational parameters, obtained from fitting the model to each individual's behavior, could predict treatment response to Metacognitive Training using machine learning. STUDY RESULTS: We observed differences in probabilistic reasoning between patients with psychotic disorders and healthy controls, participants with and without jumping-to-conclusions bias, but not between patients with low and high current delusions. The computational analysis suggested that belief instability was increased in patients with psychotic disorders. Jumping-to-conclusions was associated with both increased belief instability and greater prior uncertainty. Lastly, belief instability predicted treatment response to Metacognitive Training at the individual level. CONCLUSIONS: Our results point towards increased belief instability as a key computational mechanism underlying probabilistic reasoning in psychotic disorders. We provide a proof-of-concept that this computational approach may be useful to help identify suitable treatments for individual patients with psychotic disorders

Active inference, evidence accumulation, and the urn task

Deciding how much evidence to accumulate before making a decision is a problem we and other animals often face, but one that is not completely understood. This issue is particularly important because a tendency to sample less information (often known as reflection impulsivity) is a feature in several psychopathologies, such as psychosis. A formal understanding of information sampling may therefore clarify the computational anatomy of psychopathology. In this theoretical letter, we consider evidence accumulation in terms of active (Bayesian) inference using a generic model of Markov decision processes. Here, agents are equipped with beliefs about their own behavior--in this case, that they will make informed decisions. Normative decision making is then modeled using variational Bayes to minimize surprise about choice outcomes. Under this scheme, different facets of belief updating map naturally onto the functional anatomy of the brain (at least at a heuristic level). Of particular interest is the key role played by the expected precision of beliefs about control, which we have previously suggested may be encoded by dopaminergic neurons in the midbrain. We show that manipulating expected precision strongly affects how much information an agent characteristically samples, and thus provides a possible link between impulsivity and dopaminergic dysfunction. Our study therefore represents a step toward understanding evidence accumulation in terms of neurobiologically plausible Bayesian inference and may cast light on why this process is disordered in psychopathology

Understanding mechanisms related to psychosis in Motor Neurone Disease

Psychosis is a challenging feature of the syndromes of motor neurone disease (MND), frontotemporal dementia (FTD) and their overlap (FTD-MND). Clinically evident psychosis is not common, except in those with C9orf72+ expansions. However, subthreshold psychosis or pre-psychosis processes are common and provide the opportunity to study the mechanisms of psychosis in MND and FTD-MND. My aim was to identify the prevalence and the cognitive and neural correlates of psychosis, and related processes, in MND. I used a tiered cohort study approach. Tier 1 introduced screening as standard in a regional MND clinic (N=111) using the Edinburgh Cognitive and Behavioural ALS Screen and Cambridge Behavioural Inventory-Revised (CBI-R). In Tier 2, 60 patients and 30 controls underwent neuropsychological assessment, including (i) evidence-based decision-making, to quantify jumping to conclusions (JTC), (ii) attentional control and associative learning, (iii) perceptual inference, and (iv) psychiatric screening with Neuropsychiatric Inventory (NPI), Brief Psychiatric Rating Scale (BRPS), and the Comprehensive Assessment of At-Risk Mental States (CAARMS). Tier 3 included magnetic resonance imaging of 30 patients and 20 controls. Carer reports in Tier 1 indicated that 10% of patients exhibited features suggestive of psychosis and 40% exhibited behavioural change. In Tier 2, many patients manifested abnormal behaviours (CBI-R 41%; NPI showed 19%; BPRS 24%), with 12-16% showing psychosis-specific symptoms (CBI-R and NPI psychosis index scores). In the jumping to conclusions task, patients made decisions based on less evidence than controls and were insensitive to negative feedback. Carer ratings of patient behaviour correlated with performance on the jumping to conclusions task when decisions were rewarded or costs fixed. Attentional shifting and perceptual inference were normal in MND. A principal component analysis (PCA) of questionnaires revealed two component scores, reflecting distinct patients’ and carers’ perspectives. The imaging analyses focused on the correlates of jumping to conclusions and insensitivity to negative feedback, as a potential risk profile for psychosis, with exploratory analyses of the correlates of the CBI-R psychosis index, and carers’ ratings of behaviour from the PCA. Using a Freesurfer regions-of-interest approach, grey matter volume correlated inversely with CBI-R psychosis index in the caudate, amygdala, cingulate and hippocampus. Using tract-based spatial statistics, increased mean diffusivity (MD) of diffusion weighted imaging correlated with the CBI-R psychosis responses in inferior longitudinal and uncinate fasciculi. Cost sensitivity in the JTC task correlated with cingulate and cerebellar grey matter volumes. White matter correlates of cost sensitivity included reduced FA with increasing cost sensitivity in white matter connecting the inferior frontal lobe in controls and patients. Although overt psychosis is uncommon in MND, many patients displayed abnormal behaviour or cognitive symptoms, including suboptimal reasoning biases and inferential impulsivity. Degeneration of cerebellar, cingulate and striatal grey matter, and adjacent major white matter tracts, may underlie these cognitive impairments and together represent a vulnerability to develop psychosis. Compromised reasoning and inference have implications for clinical management, including decisions around treatment options and management of well-being in MND.This research was funded by Alzheimer’s Research UK Studentship (PhD2017-26); Medical Research Council (SUAG 051/ G101400); and the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care

Problematisation and regulation: bodies, risk, and recovery within the context of Neonatal Abstinence Syndrome

Background Neonatal Abstinence Syndrome (NAS) is an anticipated effect of maternal drug use during pregnancy. Yet it remains a contested area of policy and practice. In this paper, we contribute to ongoing debates about the way NAS is understood and responded to, through different treatment regimes, or logics of care. Our analysis examines the role of risk and recovery discourses, and the way in which the bodies of women and babies are conceptualised within these. Methods Qualitative interviews with 16 parents (9 mothers, 7 fathers) and four focus groups with 27 health and social care professionals based in Scotland. All the mothers were prescribed opioid replacement therapy and parents were interviewed after their baby was born. Data collection explored understandings about the causes and consequences of NAS and experiences of preparing for, and caring for, a baby with NAS. Data were analysed using a narrative and discursive approach. Results Parent and professional accounts simultaneously upheld and subverted logics of care which govern maternal drug use and the assessment and care of mother and baby. Despite acknowledging the unpredictability of NAS symptoms and the inability of the women who are opioid-dependent to prevent NAS, logics of care centred on ‘proving’ risk and recovery. Strategies appealed to the need for caution, intervening and control, and obscured alternative logics of care that focus on improving support for mother-infant dyads and the family as a whole. Conclusion Differing notions of risk and recovery that govern maternal drug use, child welfare and family life both compel and trouble all logics of care. The contentious nature of NAS reflects wider socio-political and moral agendas that ultimately have little to do with meeting the needs of mothers and babies. Fundamental changes in the principles, quality and delivery of care could improve outcomes for families affected by NAS