The selective serotonin reuptake inhibitor sertraline alters learning from aversive reinforcements in patients with depression: evidence from a randomized controlled trial.

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) are first-line pharmacological treatments for depression and anxiety. However, little is known about how pharmacological action is related to cognitive and affective processes. Here, we examine whether specific reinforcement learning processes mediate the treatment effects of SSRIs. METHODS: The PANDA trial was a multicentre, double-blind, randomized clinical trial in UK primary care comparing the SSRI sertraline with placebo for depression and anxiety. Participants (N = 655) performed an affective Go/NoGo task three times during the trial and computational models were used to infer reinforcement learning processes. RESULTS: There was poor task performance: only 54% of the task runs were informative, with more informative task runs in the placebo than in the active group. There was no evidence for the preregistered hypothesis that Pavlovian inhibition was affected by sertraline. Exploratory analyses revealed that in the sertraline group, early increases in Pavlovian inhibition were associated with improvements in depression after 12 weeks. Furthermore, sertraline increased how fast participants learned from losses and faster learning from losses was associated with more severe generalized anxiety symptoms. CONCLUSIONS: The study findings indicate a relationship between aversive reinforcement learning mechanisms and aspects of depression, anxiety, and SSRI treatment, but these relationships did not align with the initial hypotheses. Poor task performance limits the interpretability and likely generalizability of the findings, and highlights the critical importance of developing acceptable and reliable tasks for use in clinical studies. FUNDING: This article presents research supported by NIHR Program Grants for Applied Research (RP-PG-0610-10048), the NIHR BRC, and UCL, with additional support from IMPRS COMP2PSYCH (JM, QH) and a Wellcome Trust grant (QH).

Action selection in early stages of psychosis: an active inference approach.

BACKGROUND: To interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls. METHODS: Twenty-three individuals with an at-risk mental state, 26 patients with first-episode psychosis and 31 controls completed a probabilistic task in which action choice (go/no-go) was dissociated from outcome valence (gain or loss). We evaluated group differences in performance and active inference model parameters and performed receiver operating characteristic (ROC) analyses to assess group classification. RESULTS: We found reduced overall performance in patients with psychosis. Active inference modelling revealed that patients showed increased forgetting, reduced confidence in policy selection and less optimal general choice behaviour, with poorer action-state associations. Importantly, ROC analysis showed fair-to-good classification performance for all groups, when combining modelling parameters and performance measures. LIMITATIONS: The sample size is moderate. CONCLUSION: Active inference modelling of this task provides further explanation for dysfunctional mechanisms underlying decision-making in psychosis and may be relevant for future research on the development of biomarkers for early identification of psychosis.

The computational relationship between reinforcement learning, social inference, and paranoia.

Theoretical accounts suggest heightened uncertainty about the state of the world underpin aberrant belief updates, which in turn increase the risk of developing a persecutory delusion. However, this raises the question as to how an agent's uncertainty may relate to the precise phenomenology of paranoia, as opposed to other qualitatively different forms of belief. We tested whether the same population (n = 693) responded similarly to non-social and social contingency changes in a probabilistic reversal learning task and a modified repeated reversal Dictator game, and the impact of paranoia on both. We fitted computational models that included closely related parameters that quantified the rigidity across contingency reversals and the uncertainty about the environment/partner. Consistent with prior work we show that paranoia was associated with uncertainty around a partner's behavioural policy and rigidity in harmful intent attributions in the social task. In the non-social task we found that pre-existing paranoia was associated with larger decision temperatures and commitment to suboptimal cards. We show relationships between decision temperature in the non-social task and priors over harmful intent attributions and uncertainty over beliefs about partners in the social task. Our results converge across both classes of model, suggesting paranoia is associated with a general uncertainty over the state of the world (and agents within it) that takes longer to resolve, although we demonstrate that this uncertainty is expressed asymmetrically in social contexts. Our model and data allow the representation of sociocognitive mechanisms that explain persecutory delusions and provide testable, phenomenologically relevant predictions for causal experiments.

Compulsivity is linked to reduced adolescent development of goal-directed control and frontostriatal functional connectivity.

A characteristic of adaptive behavior is its goal-directed nature. An ability to act in a goal-directed manner is progressively refined during development, but this refinement can be impacted by the emergence of psychiatric disorders. Disorders of compulsivity have been framed computationally as a deficit in model-based control, and have been linked also to abnormal frontostriatal connectivity. However, the developmental trajectory of model-based control, including an interplay between its maturation and an emergence of compulsivity, has not been characterized. Availing of a large sample of healthy adolescents (n = 569) aged 14 to 24 y, we show behaviorally that over the course of adolescence there is a within-person increase in model-based control, and this is more pronounced in younger participants. Using a bivariate latent change score model, we provide evidence that the presence of higher compulsivity traits is associated with an atypical profile of this developmental maturation in model-based control. Resting-state fMRI data from a subset of the behaviorally assessed subjects (n = 230) revealed that compulsivity is associated with a less pronounced change of within-subject developmental remodeling of functional connectivity, specifically between the striatum and a frontoparietal network. Thus, in an otherwise clinically healthy population sample, in early development, individual differences in compulsivity are linked to the developmental trajectory of model-based control and a remodeling of frontostriatal connectivity.

Credit assignment to state-independent task representations and its relationship with model-based decision making.

Model-free learning enables an agent to make better decisions based on prior experience while representing only minimal knowledge about an environment's structure. It is generally assumed that model-free state representations are based on outcome-relevant features of the environment. Here, we challenge this assumption by providing evidence that a putative model-free system assigns credit to task representations that are irrelevant to an outcome. We examined data from 769 individuals performing a well-described 2-step reward decision task where stimulus identity but not spatial-motor aspects of the task predicted reward. We show that participants assigned value to spatial-motor representations despite it being outcome irrelevant. Strikingly, spatial-motor value associations affected behavior across all outcome-relevant features and stages of the task, consistent with credit assignment to low-level state-independent task representations. Individual difference analyses suggested that the impact of spatial-motor value formation was attenuated for individuals who showed greater deployment of goal-directed (model-based) strategies. Our findings highlight a need for a reconsideration of how model-free representations are formed and regulated according to the structure of the environment.

Reduction in social learning and increased policy uncertainty about harmful intent is associated with pre-existing paranoid beliefs: Evidence from modelling a modified serial dictator game.

Current computational models suggest that paranoia may be explained by stronger higher-order beliefs about others and increased sensitivity to environments. However, it is unclear whether this applies to social contexts, and whether it is specific to harmful intent attributions, the live expression of paranoia. We sought to fill this gap by fitting a computational model to data (n = 1754) from a modified serial dictator game, to explore whether pre-existing paranoia could be accounted by specific alterations to cognitive parameters characterising harmful intent attributions. We constructed a 'Bayesian brain' model of others' intent, which we fitted to harmful intent and self-interest attributions made over 18 trials, across three different partners. We found that pre-existing paranoia was associated with greater uncertainty about other's actions. It moderated the relationship between learning rates and harmful intent attributions, making harmful intent attributions less reliant on prior interactions. Overall, the magnitude of harmful intent attributions was directly related to their uncertainty, and importantly, the opposite was true for self-interest attributions. Our results explain how pre-existing paranoia may be the result of an increased need to attend to immediate experiences in determining intentional threat, at the expense of what is already known, and more broadly, they suggest that environments that induce greater probabilities of harmful intent attributions may also induce states of uncertainty, potentially as an adaptive mechanism to better detect threatening others. Importantly, we suggest that if paranoia were able to be explained exclusively by core domain-general alterations we would not observe differential parameter estimates underlying harmful-intent and self-interest attributions.

Variability in Action Selection Relates to Striatal Dopamine 2/3 Receptor Availability in Humans: A PET Neuroimaging Study Using Reinforcement Learning and Active Inference Models.

Choosing actions that result in advantageous outcomes is a fundamental function of nervous systems. All computational decision-making models contain a mechanism that controls the variability of (or confidence in) action selection, but its neural implementation is unclear-especially in humans. We investigated this mechanism using two influential decision-making frameworks: active inference (AI) and reinforcement learning (RL). In AI, the precision (inverse variance) of beliefs about policies controls action selection variability-similar to decision 'noise' parameters in RL-and is thought to be encoded by striatal dopamine signaling. We tested this hypothesis by administering a 'go/no-go' task to 75 healthy participants, and measuring striatal dopamine 2/3 receptor (D2/3R) availability in a subset (n = 25) using [11C]-(+)-PHNO positron emission tomography. In behavioral model comparison, RL performed best across the whole group but AI performed best in participants performing above chance levels. Limbic striatal D2/3R availability had linear relationships with AI policy precision (P = 0.029) as well as with RL irreducible decision 'noise' (P = 0.020), and this relationship with D2/3R availability was confirmed with a 'decision stochasticity' factor that aggregated across both models (P = 0.0006). These findings are consistent with occupancy of inhibitory striatal D2/3Rs decreasing the variability of action selection in humans.

Distinct Roles of Dopamine and Noradrenaline in Incidental Memory.

Episodic memory is sensitive to the influence of neuromodulators, such as dopamine and noradrenaline. These influences are considered important in the expression of several known memory biases, though their specific role in memory remains unclear. Using pharmacological agents with relatively high selectivity for either dopamine (400 mg amisulpride) or noradrenaline (40 mg propranolol) we examined their specific contribution to incidental memory. In a double-blind placebo-controlled human study (30 females, 30 males in total), we show that a memory selectivity bias was insensitive to propranolol but sensitive to amisulpride, consistent with a dominant influence from dopamine. By contrast, a putative arousal-induced memory boosting effect was insensitive to amisulpride but was sensitive to propranolol, consistent with a dominant noradrenaline effect. Thus, our findings highlight specific functional roles for dopamine and noradrenaline neurotransmission in the expression of incidental memory.SIGNIFICANCE STATEMENT Why some information is preferentially encoded into memory while other information is not is a central question in cognitive neuroscience. The neurotransmitters dopamine and noradrenaline are often assumed critical in influencing this selectivity, but their specific contributions remain obscure. In this double-blind, placebo-controlled, between-subjects drug study, we investigate the contributions of noradrenaline and dopamine to episodic memory. Using an incidental memory task, we find that blocking dopamine (400 mg amisulpride) eliminates a neural-gain related memory selectivity bias. Blocking noradrenaline function (40 mg propranolol), in contrast, abolishes an arousal-related memory enhancement. In this assessment of dopamine and noradrenaline neuromodulatory effects we reveal their specific contributions to episodic memory.

White matter tract myelin maturation and its association with general psychopathology in adolescence and early adulthood.

Adolescence is a time period associated with marked brain maturation that coincides with an enhanced risk for onset of psychiatric disorder. White matter tract myelination, a process that continues to unfold throughout adolescence, is reported to be abnormal in several psychiatric disorders. Here, we ask whether psychiatric vulnerability is linked to aberrant developmental myelination trajectories. We assessed a marker of myelin maturation, using magnetisation transfer (MT) imaging, in 10 major white matter tracts. We then investigated its relationship to the expression of a general psychopathology "p-factor" in a longitudinal analysis of 293 healthy participants between the ages of 14 and 24. We observed significant longitudinal MT increase across the full age spectrum in anterior thalamic radiation, hippocampal cingulum, dorsal cingulum and superior longitudinal fasciculus. MT increase in the inferior fronto-occipital fasciculus, inferior longitudinal fasciculus and uncinate fasciculus was pronounced in younger participants but levelled off during the transition into young adulthood. Crucially, longitudinal MT increase in dorsal cingulum and uncinate fasciculus decelerated as a function of mean p-factor scores over the study period. This suggests that an increased expression of psychopathology is closely linked to lower rates of myelin maturation in selective brain tracts over time. Impaired myelin growth in limbic association fibres may serve as a neural marker for emerging mental illness during the course of adolescence and early adulthood.

Childhood socio-economic disadvantage predicts reduced myelin growth across adolescence and young adulthood.

Socio-economic disadvantage increases exposure to life stressors. Animal research suggests early life stressors impact later neurodevelopment, including myelin developmental growth. To determine how early life disadvantage may affect myelin growth in adolescence and young adulthood, we analysed data from an accelerated longitudinal neuroimaging study measuring magnetisation transfer (MT), a myelin-sensitive marker, in 288 participants (149 female) between 14 and 25 years of age at baseline. We found that early life economic disadvantage before age 12, measured by a neighbourhood poverty index, was associated with slower myelin growth. This association was observed for magnetization transfer in cortical, subcortical and core white matter regions, and also in key subcortical nuclei. Participant IQ at baseline, alcohol use, body mass index, parental occupation and self-reported parenting quality did not account for these effects, but parental education did so partially. Specifically, positive parenting moderated the effect of socio-economic disadvantage in a protective manner. Thus, early socioeconomic disadvantage appears to alter myelin growth across adolescence. This finding has potential translational implications, including clarifying whether reducing socio-economic disadvantage during childhood, and increasing parental education and positive parenting, promote normal trajectories of brain development in economically disadvantaged contexts.

Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion modeling.

A well-established notion in cognitive neuroscience proposes that multiple brain systems contribute to choice behaviour. These include: (1) a model-free system that uses values cached from the outcome history of alternative actions, and (2) a model-based system that considers action outcomes and the transition structure of the environment. The widespread use of this distinction, across a range of applications, renders it important to index their distinct influences with high reliability. Here we consider the two-stage task, widely considered as a gold standard measure for the contribution of model-based and model-free systems to human choice. We tested the internal/temporal stability of measures from this task, including those estimated via an established computational model, as well as an extended model using drift-diffusion. Drift-diffusion modeling suggested that both choice in the first stage, and RTs in the second stage, are directly affected by a model-based/free trade-off parameter. Both parameter recovery and the stability of model-based estimates were poor but improved substantially when both choice and RT were used (compared to choice only), and when more trials (than conventionally used in research practice) were included in our analysis. The findings have implications for interpretation of past and future studies based on the use of the two-stage task, as well as for characterising the contribution of model-based processes to choice behaviour.

Beta-Blocker Propranolol Modulates Decision Urgency During Sequential Information Gathering.

Arbitrating between timely choice and extended information gathering is critical for effective decision making. Aberrant information gathering behavior is thought to be a feature of psychiatric disorders such as schizophrenia and obsessive-compulsive disorder, but we know little about the underlying neurocognitive control mechanisms. In a double-blind, placebo-controlled drug study involving 60 healthy human subjects (30 female), we examined the effects of noradrenaline and dopamine antagonism on information gathering during performance of an information sampling task. We show that modulating noradrenaline function with 40 mg of the ß-blocker propranolol leads to decreased information gathering behavior. Modulating dopamine function via a single dose of 400 mg of amisulpride revealed some effects that were intermediate between those of propranolol and placebo. Using a Bayesian computational model, we show that sampling behavior is best explained by inclusion of a nonlinear urgency signal that promotes commitment to an early decision. Noradrenaline blockade promotes the expression of this decision-related urgency signal during information gathering. We discuss the findings with respect to psychopathological conditions that are linked to aberrant information gathering.SIGNIFICANCE STATEMENT Knowing when to stop gathering information and commit to a choice option is nontrivial. This is an important element in arbitrating between information gain and energy conservation. In this double-blind, placebo-controlled drug study, we investigated the role of catecholamines noradrenaline and dopamine on sequential information gathering. We found that blockade of noradrenaline led to a decrease in information gathering. Dopamine blockade showed an intermediate, but nonsignificant, effect. Using a Bayesian computational model, we show that this noradrenaline effect is driven by increased decision urgency, a signal that reflects an escalating subjective cost of sampling. The observation that noradrenaline modulates decision urgency suggests new avenues for treating patients that show information gathering deficits.

Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood.

Pavlovian influences are important in guiding decision-making across health and psychopathology. There is an increasing interest in using concise computational tasks to parametrise such influences in large populations, and especially to track their evolution during development and changes in mental health. However, the developmental course of Pavlovian influences is uncertain, a problem compounded by the unclear psychometric properties of the relevant measurements. We assessed Pavlovian influences in a longitudinal sample using a well characterised and widely used Go-NoGo task. We hypothesized that the strength of Pavlovian influences and other 'psychomarkers' guiding decision-making would behave like traits. As reliance on Pavlovian influence is not as profitable as precise instrumental decision-making in this Go-NoGo task, we expected this influence to decrease with higher IQ and age. Additionally, we hypothesized it would correlate with expressions of psychopathology. We found that Pavlovian effects had weak temporal stability, while model-fit was more stable. In terms of external validity, Pavlovian effects decreased with increasing IQ and experience within the task, in line with normative expectations. However, Pavlovian effects were poorly correlated with age or psychopathology. Thus, although this computational construct did correlate with important aspects of development, it does not meet conventional requirements for tracking individual development. We suggest measures that might improve psychometric properties of task-derived Pavlovian measures for future studies.

Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome.

How does human brain structure mature during adolescence? We used MRI to measure cortical thickness and intracortical myelination in 297 population volunteers aged 14-24 y old. We found and replicated that association cortical areas were thicker and less myelinated than primary cortical areas at 14 y. However, association cortex had faster rates of shrinkage and myelination over the course of adolescence. Age-related increases in cortical myelination were maximized approximately at the internal layer of projection neurons. Adolescent cortical myelination and shrinkage were coupled and specifically associated with a dorsoventrally patterned gene expression profile enriched for synaptic, oligodendroglial- and schizophrenia-related genes. Topologically efficient and biologically expensive hubs of the brain anatomical network had greater rates of shrinkage/myelination and were associated with overexpression of the same transcriptional profile as cortical consolidation. We conclude that normative human brain maturation involves a genetically patterned process of consolidating anatomical network hubs. We argue that developmental variation of this consolidation process may be relevant both to normal cognitive and behavioral changes and the high incidence of schizophrenia during human brain adolescence.

Increased decision thresholds enhance information gathering performance in juvenile Obsessive-Compulsive Disorder (OCD).

Patients with obsessive-compulsive disorder (OCD) can be described as cautious and hesitant, manifesting an excessive indecisiveness that hinders efficient decision making. However, excess caution in decision making may also lead to better performance in specific situations where the cost of extended deliberation is small. We compared 16 juvenile OCD patients with 16 matched healthy controls whilst they performed a sequential information gathering task under different external cost conditions. We found that patients with OCD outperformed healthy controls, winning significantly more points. The groups also differed in the number of draws required prior to committing to a decision, but not in decision accuracy. A novel Bayesian computational model revealed that subjective sampling costs arose as a non-linear function of sampling, closely resembling an escalating urgency signal. Group difference in performance was best explained by a later emergence of these subjective costs in the OCD group, also evident in an increased decision threshold. Our findings present a novel computational model and suggest that enhanced information gathering in OCD can be accounted for by a higher decision threshold arising out of an altered perception of costs that, in some specific contexts, may be advantageous.

Personality dimensions emerging during adolescence and young adulthood are underpinned by a single latent trait indexing impairment in social functioning.

BACKGROUND: Personality with stable behavioural traits emerges in the adolescent and young adult years. Models of putatively distinct, but correlated, personality traits have been developed to describe behavioural styles including schizotypal, narcissistic, callous-unemotional, negative emotionality, antisocial and impulsivity traits. These traits have influenced the classification of their related personality disorders. We tested if a bifactor model fits the data better than correlated-factor and orthogonal-factor models and subsequently validated the obtained factors with mental health measures and treatment history. METHOD: A set of self-report questionnaires measuring the above traits together with measures of mental health and service use were collected from a volunteer community sample of adolescents and young adults aged 14 to 25 years (N = 2443). RESULTS: The bifactor model with one general and four specific factors emerged in exploratory analysis, which fit data better than models with correlated or orthogonal factors. The general factor showed high reliability and validity. CONCLUSIONS: The findings suggest that a selected range of putatively distinct personality traits is underpinned by a general latent personality trait that may be interpreted as a severity factor, with higher scores indexing more impairment in social functioning. The results are in line with ICD-11, which suggest an explicit link between personality disorders and compromised interpersonal or social function. The obtained general factor was akin to the overarching dimension of personality functioning (describing one's relation to the self and others) proposed by DSM-5 Section III.

How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences.

The weight with which a specific outcome feature contributes to preference quantifies a person's 'taste' for that feature. However, far from being fixed personality characteristics, tastes are plastic. They tend to align, for example, with those of others even if such conformity is not rewarded. We hypothesised that people can be uncertain about their tastes. Personal tastes are therefore uncertain beliefs. People can thus learn about them by considering evidence, such as the preferences of relevant others, and then performing Bayesian updating. If a person's choice variability reflects uncertainty, as in random-preference models, then a signature of Bayesian updating is that the degree of taste change should correlate with that person's choice variability. Temporal discounting coefficients are an important example of taste-for patience. These coefficients quantify impulsivity, have good psychometric properties and can change upon observing others' choices. We examined discounting preferences in a novel, large community study of 14-24 year olds. We assessed discounting behaviour, including decision variability, before and after participants observed another person's choices. We found good evidence for taste uncertainty and for Bayesian taste updating. First, participants displayed decision variability which was better accounted for by a random-taste than by a response-noise model. Second, apparent taste shifts were well described by a Bayesian model taking into account taste uncertainty and the relevance of social information. Our findings have important neuroscientific, clinical and developmental significance.

Reflection impulsivity in binge drinking: behavioural and volumetric correlates.

The degree to which an individual accumulates evidence prior to making a decision, also known as reflection impulsivity, can be affected in psychiatric disorders. Here, we study decisional impulsivity in binge drinkers, a group at elevated risk for developing alcohol use disorders, comparing two tasks assessing reflection impulsivity and a delay discounting task, hypothesizing impairments in both subtypes of impulsivity. We also assess volumetric correlates of reflection impulsivity focusing on regions previously implicated in functional magnetic resonance imaging studies. Sixty binge drinkers and healthy volunteers were tested using two different information-gathering paradigms: the beads task and the Information Sampling Task (IST). The beads task was analysed using a behavioural approach and a Bayesian model of decision making. Delay discounting was assessed using the Monetary Choice Questionnaire. Regression analyses of primary outcomes were conducted with voxel-based morphometry analyses. Binge drinkers sought less evidence prior to decision in the beads task compared with healthy volunteers in both the behavioural and computational modelling analysis. There were no group differences in the IST or delay discounting task. Greater impulsivity as indexed by lower evidence accumulation in the beads task was associated with smaller dorsolateral prefrontal cortex and inferior parietal volumes. In contrast, greater impulsivity as indexed by lower evidence accumulation in the IST was associated with greater dorsal cingulate and precuneus volumes. Binge drinking is characterized by impaired reflection impulsivity suggesting a deficit in deciding on the basis of future outcomes that are more difficult to represent. These findings emphasize the role of possible therapeutic interventions targeting decision-making deficits.

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.

An empirical study of defensive avoidance in paranoia.

BACKGROUND: There is controversy as to whether psychological defensive avoidance is associated with paranoia. AIMS: To elucidate whether "Poor-me" paranoid patients, who believe that the persecution they perceive is undeserved, show more prominent avoidance of negative thoughts about themselves than healthy and clinical controls. METHOD: The act of avoidance of aversive mental contents was assessed in 27 healthy controls and 48 patients with poor-me, bad-me (perceived to be deserved) or no paranoia. Defensive avoidance was assessed via established questionnaires, a novel task based on self-discrepancy theory and research-clinician ratings. RESULTS: Participants in all groups showed substantial levels of verbal defensive avoidance. Paranoia was associated with reduced self-reported tolerance of negative mental contents (high Experiential Avoidance, EA). Contrary to our hypotheses, poor-me and bad-me patients showed similar EA. All participant groups showed similar levels of verbal defensive avoidance. CONCLUSION: The findings do not support an association of psychological avoidance with paranoia.