The traps of adaptation: Addiction as maladaptive referent-dependent evaluation.

Referent-dependent evaluation theories propose that the ongoing context influences how the brain attributes value to stimuli. What are the implications of these theories for understanding addiction? The paper asks this question by casting this disorder as a form of maladaptive referent-dependent evaluation. Specifically, addiction is proposed to arise from the establishment of an excessive reference point following repeated drug consumption. Several key aspects of the disorder emerge from this perspective, including withdrawal, tolerance, enhanced craving, negative mood, and diminished stimulus discriminability. As highlighted in the paper, this formulation has important analogies with classical accounts of addiction, such as set point theories and associative learning theories. Moreover, this picture fits with the pattern of striatal dopaminergic activity observed in addiction, a key neural signature of the disorder. Overall, the referent-dependent evaluation approach emerges as a useful add-on to the theoretical toolkit adopted to interpret addiction. This also supports the idea that referent-dependent evaluation might offer a general framework to understand various disorders characterised by disrupted motivation.

A Reference-Dependent Computational Model of Anorexia Nervosa.

Influential accounts interpret anorexia as arising from perfectionism, dichotomous thinking, and poor control expressed in a variety of life domains, resulting in low self-esteem. In this context, restraining eating would allow patients to re-establish some control and self-esteem. Although this view has offered important insight, one shortcoming is that constructs such as perfectionism, control, and dichotomous thinking, remain poorly specified. To clarify these constructs, we propose a computational model of anorexia. This relies on previous theories of evaluation, which highlight its reference-dependent nature: when attributing a value to an outcome, our brain automatically assesses the outcome relative to its context. Following these theories, the model proposes that a high reference point explains general characteristics such as perfectionism, dichotomous thinking, low self-esteem, and low sense of control. These characteristics would result specifically in anorexia when the sense of control regarding body shape, compared with other life domains, is relatively high. The model raises the possibility that reference effects also might explain why patients pursue extremely low weight; exposure to skinny body images-one product of obsessive dieting-might change the reference point for their own body, hence leading to extremely low body weight, staunch refusal to gain weight, and body misperceptions. The model contributes to clarify key concepts adopted in the literature and their relation. Such computational formulation might help to foster theoretical debate, formulating novel empirical predictions, and integrate psychological and neuroscientific perspectives on anorexia.

I want to believe: delusion, motivated reasoning, and Bayesian decision theory.

Introduction: Several arguments suggest that motivated reasoning (occurring when beliefs are not solely shaped by accuracy, but also by other motives such as promoting self-esteem or self-protection) is important in delusions. However, classical theories of delusion disregard the role of motivated reasoning. Thus, this role remains poorly understood.Methods: To explore the role of motivated reasoning in delusions, here we propose a computational model of delusion based on a Bayesian decision framework. This proposes that beliefs are not only evaluated based on their accuracy (as in classical theories), but also based on the cost (in terms of reward and punishment) of rejecting them.Results: The model proposes that, when the values at stake are high (as often it is the case in the context of delusion), a belief might be endorsed because rejecting it is evaluated as too costly, even if the belief is less accurate. This process might contribute to the genesis of delusions.Conclusions: Our account offers an interpretation of how motivated reasoning might shape delusions. This can inspire research on the affective and motivational processes supporting delusions in clinical conditions such as in psychosis, neurological disorders, and delusional disorder.

The Link Between COVID-19, Anxiety, and Religious Beliefs in the United States and the United Kingdom.

Research has shown that stress impacts on people's religious beliefs. However, several aspects of this effect remain poorly understood, for example regarding the role of prior religiosity and stress-induced anxiety. This paper explores these aspects in the context of the recent coronavirus pandemic (COVID-19). The latter has impacted dramatically on many people's well-being; hence it can be considered a highly stressful event. Through online questionnaires administered to UK (n = 140) and USA (n = 140) citizens professing either Christian faith or no religion, this paper examines the impact of the coronavirus crisis upon common people's religious beliefs. Anxiety about the coronavirus and prior religiosity showed an interaction effect upon change in religious beliefs (t(276) = 2.27, p = .024): for strong believers higher anxiety about coronavirus was associated with increased strengthening of religious beliefs (r = .249), while for non-believers higher anxiety about coronavirus was associated with increased scepticism towards religious beliefs (r = - .157). These observations are consistent with the notion that stress-induced anxiety enhances support for an individual's existing ideology already embraced before a stressful event occurs. This study sheds light on the psychological and cultural implications of the coronavirus crisis, which represents one of the most serious health emergencies in recent times.

Correction: A unifying Bayesian account of contextual effects in value-based choice.

[This corrects the article DOI: 10.1371/journal.pcbi.1005769.].

The role of expecting feedback during decision-making under risk.

Sometimes choice is followed by outcome feedback and other times it is not. It remains unknown whether humans prefer gambling when they expect feedback to be revealed. Regarding this question, decision-making theories make alternative predictions. Some theories have proposed that choice is influenced by whether one expects to be disappointed in the future. Given that feedback is sometimes disappointing, these theories predict increased aversion towards gambling when feedback is expected compared to when feedback is not expected. The opposite effect is predicted by theories of curiosity, which postulate reduction of uncertainty as an important behavioural drive. Given that feedback reduces uncertainty, these theories predict that gambling will be favoured when feedback is expected. To examine whether expecting feedback influences gambling behaviour, we recorded functional neuroimaging data while participants performed a novel decision-making task requiring to chose between a sure option and a gamble. Crucially, participants expected to receive feedback in some trials but not in other trials. Consistent with theories of curiosity, we found that expecting feedback increased gambling propensity. At the neural level, at option presentation the increased value of gambling during feedback was reflected in activity in the ventral striatum. This suggests that, together with its established role in signalling reward, the ventral striatum also processes a form of epistemic value. Our study demonstrates that gambling becomes more attractive when feedback is expected and suggests that striatal activity could signal the value of feedback information.

Learning Contextual Reward Expectations for Value Adaptation.

Substantial evidence indicates that subjective value is adapted to the statistics of reward expected within a given temporal context. However, how these contextual expectations are learned is poorly understood. To examine such learning, we exploited a recent observation that participants performing a gambling task adjust their preferences as a function of context. We show that, in the absence of contextual cues providing reward information, an average reward expectation was learned from recent past experience. Learning dependent on contextual cues emerged when two contexts alternated at a fast rate, whereas both cue-independent and cue-dependent forms of learning were apparent when two contexts alternated at a slower rate. Motivated by these behavioral findings, we reanalyzed a previous fMRI data set to probe the neural substrates of learning contextual reward expectations. We observed a form of reward prediction error related to average reward such that, at option presentation, activity in ventral tegmental area/substantia nigra and ventral striatum correlated positively and negatively, respectively, with the actual and predicted value of options. Moreover, an inverse correlation between activity in ventral tegmental area/substantia nigra (but not striatum) and predicted option value was greater in participants showing enhanced choice adaptation to context. The findings help understanding the mechanisms underlying learning of contextual reward expectation.

Value encoding in the globus pallidus: fMRI reveals an interaction effect between reward and dopamine drive.

The external part of the globus pallidus (GPe) is a core nucleus of the basal ganglia (BG) whose activity is disrupted under conditions of low dopamine release, as in Parkinson's disease. Current models assume decreased dopamine release in the dorsal striatum results in deactivation of dorsal GPe, which in turn affects motor expression via a regulatory effect on other nuclei of the BG. However, recent studies in healthy and pathological animal models have reported neural dynamics that do not match with this view of the GPe as a relay in the BG circuit. Thus, the computational role of the GPe in the BG is still to be determined. We previously proposed a neural model that revisits the functions of the nuclei of the BG, and this model predicts that GPe encodes values which are amplified under a condition of low striatal dopaminergic drive. To test this prediction, we used an fMRI paradigm involving a within-subject placebo-controlled design, using the dopamine antagonist risperidone, wherein healthy volunteers performed a motor selection and maintenance task under low and high reward conditions. ROI-based fMRI analysis revealed an interaction between reward and dopamine drive manipulations, with increased BOLD activity in GPe in a high compared to low reward condition, and under risperidone compared to placebo. These results confirm the core prediction of our computational model, and provide a new perspective on neural dynamics in the BG and their effects on motor selection and cognitive disorders.

Risk preference and choice stochasticity during decisions for other people.

In several contexts, such as finance and politics, people make choices that are relevant for others but irrelevant for oneself. Focusing on decision-making under risk, we compared monetary choices made for one's own interest with choices made on behalf of an anonymous individual. Consistent with the previous literature, other-interest choices were characterized by an increased gambling propensity. We also investigated choice stochasticity, which captures how much decisions vary in similar conditions. An aspect related to choice stochasticity is how much decisions are tuned to the option values, and we found that this was higher during self-interest than during other-interest choices. This effect was observed only in individuals who reported a motivation to distribute rewards unequally, suggesting that it may (at least partially) depend on a motivation to make accurate decisions for others. Our results indicate that, during decision-making under risk, choices for other people are characterized by a decreased tuning to the values of the options, in addition to enhanced risk seeking.

Better than expected: the influence of option expectations during decision-making.

Our choices often arise from a consideration of options presented in a sequence (e.g. the products in a supermarket row). However, whether the precise sequential order of option presentation affects decision-making remains poorly understood. A recent model of choice proposes that, in a set of options presented sequentially, those that are better than expected will be perceived as more valuable, even when options are objectively equivalent within the set. Inspired by this proposal, we devised a novel decision-making task where we manipulated the order of option presentation together with expectations about option value. Even when we compared trials that were exactly equivalent except for option order, we observed a striking preference for options that were better than expected. Our findings show that expectations about options affect which option will be favoured within a sequence, an influence which is manifested as a preference for better-than-expected options. The findings have potential practical implications, as for example they may help policymakers in devising nudge strategies that rely on ad hoc option orders.

A unifying Bayesian account of contextual effects in value-based choice.

Empirical evidence suggests the incentive value of an option is affected by other options available during choice and by options presented in the past. These contextual effects are hard to reconcile with classical theories and have inspired accounts where contextual influences play a crucial role. However, each account only addresses one or the other of the empirical findings and a unifying perspective has been elusive. Here, we offer a unifying theory of context effects on incentive value attribution and choice based on normative Bayesian principles. This formulation assumes that incentive value corresponds to a precision-weighted prediction error, where predictions are based upon expectations about reward. We show that this scheme explains a wide range of contextual effects, such as those elicited by other options available during choice (or within-choice context effects). These include both conditions in which choice requires an integration of multiple attributes and conditions where a multi-attribute integration is not necessary. Moreover, the same scheme explains context effects elicited by options presented in the past or between-choice context effects. Our formulation encompasses a wide range of contextual influences (comprising both within- and between-choice effects) by calling on Bayesian principles, without invoking ad-hoc assumptions. This helps clarify the contextual nature of incentive value and choice behaviour and may offer insights into psychopathologies characterized by dysfunctional decision-making, such as addiction and pathological gambling.

Active Inference: A Process Theory.

This article describes a process theory based on active inference and belief propagation. Starting from the premise that all neuronal processing (and action selection) can be explained by maximizing Bayesian model evidence-or minimizing variational free energy-we ask whether neuronal responses can be described as a gradient descent on variational free energy. Using a standard (Markov decision process) generative model, we derive the neuronal dynamics implicit in this description and reproduce a remarkable range of well-characterized neuronal phenomena. These include repetition suppression, mismatch negativity, violation responses, place-cell activity, phase precession, theta sequences, theta-gamma coupling, evidence accumulation, race-to-bound dynamics, and transfer of dopamine responses. Furthermore, the (approximately Bayes' optimal) behavior prescribed by these dynamics has a degree of face validity, providing a formal explanation for reward seeking, context learning, and epistemic foraging. Technically, the fact that a gradient descent appears to be a valid description of neuronal activity means that variational free energy is a Lyapunov function for neuronal dynamics, which therefore conform to Hamilton's principle of least action.

Active Inference, epistemic value, and vicarious trial and error.

Balancing habitual and deliberate forms of choice entails a comparison of their respective merits-the former being faster but inflexible, and the latter slower but more versatile. Here, we show that arbitration between these two forms of control can be derived from first principles within an Active Inference scheme. We illustrate our arguments with simulations that reproduce rodent spatial decisions in T-mazes. In this context, deliberation has been associated with vicarious trial and error (VTE) behavior (i.e., the fact that rodents sometimes stop at decision points as if deliberating between choice alternatives), whose neurophysiological correlates are "forward sweeps" of hippocampal place cells in the arms of the maze under consideration. Crucially, forward sweeps arise early in learning and disappear shortly after, marking a transition from deliberative to habitual choice. Our simulations show that this transition emerges as the optimal solution to the trade-off between policies that maximize reward or extrinsic value (habitual policies) and those that also consider the epistemic value of exploratory behavior (deliberative or epistemic policies)-the latter requiring VTE and the retrieval of episodic information via forward sweeps. We thus offer a novel perspective on the optimality principles that engender forward sweeps and VTE, and on their role on deliberate choice.

The Dopaminergic Midbrain Mediates an Effect of Average Reward on Pavlovian Vigor.

Dopamine plays a key role in motivation. Phasic dopamine response reflects a reinforcement prediction error (RPE), whereas tonic dopamine activity is postulated to represent an average reward that mediates motivational vigor. However, it has been hard to find evidence concerning the neural encoding of average reward that is uncorrupted by influences of RPEs. We circumvented this difficulty in a novel visual search task where we measured participants' button pressing vigor in a context where information (underlying an RPE) about future average reward was provided well before the average reward itself. Despite no instrumental consequence, participants' pressing force increased for greater current average reward, consistent with a form of Pavlovian effect on motivational vigor. We recorded participants' brain activity during task performance with fMRI. Greater average reward was associated with enhanced activity in dopaminergic midbrain to a degree that correlated with the relationship between average reward and pressing vigor. Interestingly, an opposite pattern was observed in subgenual cingulate cortex, a region implicated in negative mood and motivational inhibition. These findings highlight a crucial role for dopaminergic midbrain in representing aspects of average reward and motivational vigor.

Multiple value signals in dopaminergic midbrain and their role in avoidance contexts.

The role of dopaminergic brain regions in avoidance behaviour is unclear. Active avoidance requires motivation, and the latter is linked to increased activity in dopaminergic regions. However, avoidance is also often tethered to the prospect of punishment, a state typically characterized by below baseline levels of dopaminergic function. Avoidance has been considered from the perspective of two-factor theories where the prospect of safety is considered to act as a surrogate for reward, leading to dopamine release and enhanced motivational drive. Using fMRI we investigated predictions from two-factor theory by separating the neural representation of a conventional net expected value, which is negative in the case of avoidance, from an adjusted expected value which factors in a possibility of punishment and is larger for both big rewards and big (predictably avoidable) punishments. We show that neural responses in ventral striatum and ventral tegmental area/substantial nigra (VTA/SN) covaried with net expected value. Activity in VTA/SN also covaried with an adjusted expected value, as did activity in anterior insula. Consistent with two-factor theory models, the findings indicate that VTA/SN and insula process an adjusted expected value during avoidance behaviour.

The influence of contextual reward statistics on risk preference.

Decision theories mandate that organisms should adjust their behaviour in the light of the contextual reward statistics. We tested this notion using a gambling choice task involving distinct contexts with different reward distributions. The best fitting model of subjects' behaviour indicated that the subjective values of options depended on several factors, including a baseline gambling propensity, a gambling preference dependent on reward amount, and a contextual reward adaptation factor. Combining this behavioural model with simultaneous functional magnetic resonance imaging we probed neural responses in three key regions linked to reward and value, namely ventral tegmental area/substantia nigra (VTA/SN), ventromedial prefrontal cortex (vmPFC) and ventral striatum (VST). We show that activity in the VTA/SN reflected contextual reward statistics to the extent that context affected behaviour, activity in the vmPFC represented a value difference between chosen and unchosen options while VST responses reflected a non-linear mapping between the actual objective rewards and their subjective value. The findings highlight a multifaceted basis for choice behaviour with distinct mappings between components of this behaviour and value sensitive brain regions.

The Status Importance Scale: Development and validation of a self-report questionnaire for measuring how much people care about status.

Although substantial research indicates that considerations about status can lead to anxiety and other negative outcomes, a valid measure of the importance individuals attribute to status is lacking. This paper introduces the Status Importance Scale (SIS), a mono-factorial 10-item self-report questionnaire that quantifies how important a person deems status to be. Five studies validate the scale showing that it has excellent internal reliability and acceptable test-retest reliability, it correlates with several related measures (supporting convergent validity), it shows little correlation with theoretically unrelated constructs (supporting discriminant validity), it is the best predictor of conspicuous consumption compared with other potential candidates (supporting concurrent validity), and it can help predicting which activities one gives importance to (further supporting concurrent validity). Finally, as hypothesized by previous literature, the last study reveals that the SIS can predict status anxiety. The SIS can contribute to research regarding important phenomena such as the detrimental psychological effects of income inequality.

The Computations of a Traumatized Mind: A Latent Cause Model of Posttraumatic Stress Disorder.

ABSTRACT: In cognitive psychology, a recent perspective based on the notion of latent cause (LC) has offered new insight on how learning and memory work. Here I explore the implications of this novel perspective to understand posttraumatic stress disorder (PTSD). The proposal is that, because of a propensity to interpret events as manifestations of multiple LCs (a propensity facilitated by experiencing traumas in childhood), PTSD patients form an LC associated with the trauma and that this LC is responsible for typical symptoms of the illness (specifically, intrusive symptoms and associated fear). Later, after the trauma, some patients develop a second LC, now associated with the presence of trauma-related cues combined with absence of danger. Development of the latter LC would interfere with extinction and explain why, for some patients, exposure to trauma-related cues (even when supported by interventions such as exposure protocols) fails to provide much improvement. This proposal has potential clinical implications, raising the possibility that some patients might benefit from exposure to mildly painful aspects of the trauma in conjunction with trauma-related cues.

Prisoner of the present: Borderline personality and a tendency to overweight cues during Bayesian inference.

Recent work has examined the computational mechanisms underlying borderline personality (BP). However, this research has been confined to specific tasks. A computational analysis of BP's mental processes as they broadly unfold in everyday life is lacking. Here, a computational model of BP is proposed, which describes patients' everyday-life mental experience at large. Grounded on Bayesian inference, the proposal is that BP sufferers attribute excessive weight to cues considered to infer life contexts (e.g., to infer whether a cooperation or competition context is ongoing). Remarkably, model simulations demonstrate that this idea accounts for several characteristics of BP, from extreme oscillations in identity, affect, and behavior, to dysfunctional interpersonal cycles. Altogether, the article offers a framework to interpret the broad, everyday life computational mechanisms underlying BP. This can inspire theoretical and empirical research and can help understanding how clinical interventions for BP work, thus contributing to refine such interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Deconstructing the Conspiratorial Mind: the Computational Logic Behind Conspiracy Theories.

In the social sciences, research on conspiracy theories is accumulating fast. To contribute to this research, here I introduce a computational model about the psychological processes underlying support for conspiracy theories. The proposal is that endorsement of these theories depends on three factors: prior beliefs, novel evidence, and expected consequences. Thanks to the latter, a conspiracy hypothesis might be selected because it is the costliest to reject even if it is not the best supported by evidence and by prior beliefs (i.e., even if it is not the most accurate). In this way, the model implies a key role for motivated reasoning. By examining the social conditions that favour the success of conspiracy theories, the paper embeds the model, whose focus is primarily psychological, within the broader social context, and applies this analysis to probe the role of conspiracy theories within contemporary Western societies. Altogether, the paper argues that a computational outlook can contribute to elucidate the socio-psychological dynamics underlying the attractiveness of conspiracy theories.