Reduced gray matter volume in limbic and cortical areas is associated with anxiety and depression in alcohol use disorder patients

Alcohol use disorder (AUD) is a multifactorial disease closely related to neurodevelopment and environmental factors that influence behavior. This study explored the relationships between brain volume and behavior from an Exploratory Structural Equation Modeling (ESEM) based on the Research Domain Criteria. High-resolution magnetic resonance imaging scans were acquired from recent patients with AUD (n = 50) and healthy controls (HC=50). Group differences were assessed by means of voxel-based morphometry (VBM) and regions of interest (ROIs). Participants completed a battery of neurocognitive tasks and emotional tests. When controlling for age, education levels, and total intracranial volume, we found lower gray matter volume in cortical and limbic areas, as well as significant impairments in the AUD group on cognition and affective status. This study demonstrated the importance of multifactorial analysis and complex models in order to better understand substance use disorders. The brain losses may have been the result of neurodevelopmental impairments due to biological and environmental factors that predisposed to AUD or the result of drug abuse. The ESEM indicated that limbic areas indirectly affected the alcohol severity through emotional dysfunction. These results suggest a more relevant involvement of limbic regions for the severity of alcohol use, showing a more significant association between AUD and mood disorders.

Risk and Loss Aversion and Attitude to COVID and Vaccines in Anxious Individuals

Anxious individuals are known to show impaired decision-making in economic gambling task and in everyday life decisions. This impairment can be due to aversion to uncertainty about outcomes (risk aversion) and/or aversion to negative outcomes (loss aversion). We investigate how non-clinical individuals with high levels of Generalised Anxiety Disorder symptoms (GAD) (N = 54) behave compared to less anxious subjects (N = 61) in a gambling decision-making task delivered online and designed to separate the distinct influences of risk and loss aversion on decision-making. By modelling subjects' choices using computational models derived from Prospect Theory and fitted using Hierarchical Bayesian methods, we estimate individual levels of risk and loss aversion. We also link estimates of these parameters to individual propensity to risk averse behaviours during the COVID pandemic, like wearing safer types of face masks, or completing a COVID vaccination course. We report increased loss aversion in individuals with increased level of GAD compared to less anxious individuals and no differences in risk aversion. We also report no evidence for a link between risk and loss aversion and attitudes towards COVID and vaccines, under the experimental conditions and incentive scheme studied here. These results shed new light on the interplay of anxiety and risk and loss aversion and they can provide useful directions for clinical intervention.

A generalized reward processing deficit pathway to negative symptoms across diagnostic boundaries

BACKGROUND

Negative symptoms are a key feature of several psychiatric disorders. Difficulty identifying common neurobiological mechanisms that cut across diagnostic boundaries might result from equifinality (i.e., multiple mechanistic pathways to the same clinical profile), both within and across disorders. This study used a data-driven approach to identify unique subgroups of participants with distinct reward processing profiles to determine which profiles predicted negative symptoms.

METHODS

Participants were a transdiagnostic sample of youth from a multisite study of psychosis risk, including 110 individuals at clinical high-risk for psychosis (CHR; meeting psychosis-risk syndrome criteria), 88 help-seeking participants who failed to meet CHR criteria and/or who presented with other psychiatric diagnoses, and a reference group of 66 healthy controls. Participants completed clinical interviews and behavioral tasks assessing four reward processing constructs indexed by the RDoC Positive Valence Systems: hedonic reactivity, reinforcement learning, value representation, and effort-cost computation.

RESULTS

k-means cluster analysis of clinical participants identified three subgroups with distinct reward processing profiles, primarily characterized by: a value representation deficit (54%), a generalized reward processing deficit (17%), and a hedonic reactivity deficit (29%). Clusters did not differ in rates of clinical group membership or psychiatric diagnoses. Elevated negative symptoms were only present in the generalized deficit cluster, which also displayed greater functional impairment and higher psychosis conversion probability scores.

CONCLUSIONS

Contrary to the equifinality hypothesis, results suggested one global reward processing deficit pathway to negative symptoms independent of diagnostic classification. Assessment of reward processing profiles may have utility for individualized clinical prediction and treatment.

Anxiety involves altered planning

Clinicians have suggested but not shown how anxiety involves altered planning. Here, I synthesize and extend computational models of planning in a framework that can be used to explain planning biases in anxiety. To spur its development, I spotlight two of its promising areas: task construal and meta-control.

Math-anxious people suffer more in math-related events: The perspective of reward processing on motivated behavior

Individuals with high math anxiety (HMA) demonstrate a tendency to avoid math-related tasks, a behavior that perpetuates a detrimental cycle of limited practice, poor performance, increased anxiety, and further avoidance. This study delves into the cognitive and neural bases of math avoidance behavior in HMA through the lens of reward processing. In Experiment 1, participants reported their satisfaction level in response to the reward provided after solving an arithmetic problem. In Experiment 2, participants weighed the economic benefits against the cognitive costs of solving a calculation problem. This decision-making process was framed in terms of either retaining or losing some monetary reward, creating positive or negative contexts, respectively. Experiment 1 showed that HMA participants were more punishment-sensitive and less satisfied with incorrect answers. Experiment 2 revealed that HMA individuals were less willing to tackle math challenges when their satisfaction dipped after errors. HMAs exhibited increased math avoidance and a notably reduced P3 amplitude in negative contexts, a response unique to the HMA group. HMAs also displayed an elevated feedback-related negativity amplitude in both contexts. This study suggests a potential impairment in reward processing in negative contexts and under negative appraisal among those with high math anxiety.

The Association of Psychological Factors With Willingness to Share Health-Related Data From Technological Devices: Cross-Sectional Questionnaire Study

Background

Health-related data from technological devices are increasingly obtained through smartphone apps and wearable devices. These data could enable physicians and other care providers to monitor patients outside the clinic or assist individuals in improving lifestyle factors. However, the use of health technology data might be hampered by the reluctance of patients to share personal health technology data because of the privacy sensitivity of this information.

Objective

This study investigates to what extent psychological factors play a role in people's willingness to share personal health technology data.

Methods

Data for this cross-sectional study were obtained by quota sampling based on age and sex in a community-based sample (N=1013; mean age 48.6, SD 16.6 years; 522/1013, 51.5% women). Willingness to share personal health technology data and related privacy concerns were assessed using an 8-item questionnaire with good psychometric properties (Cronbach's α=0.82). Psychological variables were assessed using validated questionnaires for optimism (Life Orientation Test-Revised), psychological flexibility (Psychological Flexibility Questionnaire), negative affectivity (Type D Scale-14-Negative Affectivity), social inhibition (Type D Scale-14-Social Inhibition), generalized anxiety (Generalized Anxiety Disorder-7), and depressive symptoms (Patient Health Questionnaire-9). Data were analyzed using multiple linear regression analyses, and network analysis was used to visualize the associations between the item scores.

Results

Higher levels of optimism (β=.093; P=.004) and psychological flexibility (β=.127; P<.001) and lower levels of social inhibition (β=-.096; P=.002) were significantly associated with higher levels of willingness to share health technology data when adjusting for age, sex, and education level in separate regression models. Other associations with psychological variables were not statistically significant. Network analysis revealed that psychological flexibility clustered more with items that focused on the benefits of sharing data, while optimism was negatively associated with privacy concerns.

Conclusions

The current results suggest that people with higher levels of optimism and psychological flexibility and those with lower social inhibition levels are more likely to share health technology data. The magnitude of the effect sizes was low, and future studies with additional psychological measures are needed to establish which factors identify people who are reluctant to share their data such that optimal use of devices in health care can be facilitated.

Understanding the neural code of stress to control anhedonia

Anhedonia, the diminished drive to seek, value, and learn about rewards, is a core feature of major depressive disorder1-3. The neural underpinnings of anhedonia and how this emotional state drives behaviour remain unclear. Here we investigated the neural code of anhedonia by taking advantage of the fact that when mice are exposed to traumatic social stress, susceptible animals become socially withdrawn and anhedonic, whereas others remain resilient. By performing high-density electrophysiology to record neural activity patterns in the basolateral amygdala (BLA) and ventral CA1 (vCA1), we identified neural signatures of susceptibility and resilience. When mice actively sought rewards, BLA activity in resilient mice showed robust discrimination between reward choices. By contrast, susceptible mice exhibited a rumination-like signature, in which BLA neurons encoded the intention to switch or stay on a previously chosen reward. Manipulation of vCA1 inputs to the BLA in susceptible mice rescued dysfunctional neural dynamics, amplified dynamics associated with resilience, and reversed anhedonic behaviour. Finally, when animals were at rest, the spontaneous BLA activity of susceptible mice showed a greater number of distinct neural population states. This spontaneous activity allowed us to decode group identity and to infer whether a mouse had a history of stress better than behavioural outcomes alone. This work reveals population-level neural dynamics that explain individual differences in responses to traumatic stress, and suggests that modulating vCA1-BLA inputs can enhance resilience by regulating these dynamics.

Brooding, Reflection, and Anger Rumination Relate to Suicidal Ideation through the Role of Thought Control

Despite the far-reaching impact of suicide on our communities, suicide prevention has historically focused on distally related risk factors for suicidality, which gives us an incomplete picture of how someone comes to make a suicide attempt. Instead, our focus needs to extend to research that explains the maintenance and progression from an emotional state to a suicidal crisis. One such factor, rumination, may create or worsen suicidal thinking by amplifying the distress associated with negative thoughts. Ruminative thoughts are often described as difficult to control, and people may think about suicide as an escape from these uncontrollable thoughts. The current study examined the relationship between severity of lifetime suicidal thinking and certain forms of rumination (i.e., brooding, reflection, anger rumination, and suicidal rumination) in a sample of 145 undergraduate students with suicidal thoughts. For each form of rumination that was related to suicidal thinking, we then examined whether that relationship was accounted for by perceived uncontrollability of one's own thoughts. We found that all forms of rumination were related to severity of lifetime suicidal thinking, as well as heightened perceived inability to control one's own thoughts. This thought control inability helped account for the relationships between brooding, reflection, and anger rumination with severity of suicidal thinking, but did not play a role in the relationship between suicidal rumination and suicidal ideation severity. Clinicians should be aware of the impact ruminative thoughts may have on suicidal thinking. More research needs to be done to replicate and extend these effects.

Factors associated with financial exploitation in older adults: A systematic review

OBJECTIVES

This systematic review aimed to identify and analyze factors associated with financial exploitation in older adults.

METHODS

A comprehensive search strategy was implemented in December 2023, across three major databases (PubMed, Web of Science, and Scopus), along with Google Scholar as a search engine, without restrictions on publication year. Quality assessment was conducted using the Newcastle-Ottawa Scale (NOS) and CONSORT tool.

RESULTS

Among the initial 985 articles identified, 26 fulfilled the inclusion criteria. The majority of studies were conducted in the USA and had a cross-sectional design. Key factors identified included cognitive function, depression and emotional health, physical health, social support and interpersonal relationships, living arrangements, race, and personality traits.

CONCLUSION

This review highlights the complex factors linked to financial exploitation in older adults, with cognitive function, depression, and social support as key predictors. However, inconsistencies in age, marital status, and substance use call for further research. Targeted interventions are essential to reduce the risk of exploitation.

Intrinsic and extrinsic control impact motivation and outcome sensitivity: the role of anhedonia, stress, and anxiety

BACKGROUND

Motivated behaviors vary widely across individuals and are controlled by a range of environmental and intrinsic factors. However, due to a lack of objective measures, the role of intrinsic v. extrinsic control of motivation in psychiatric disorders remains poorly understood.

METHODS

We developed a novel multi-factorial behavioral task that separates the distinct contributions of intrinsic v. extrinsic control, and determines their influence on motivation and outcome sensitivity in a range of contextual environments. We deployed this task in two independent cohorts (final in-person N = 181 and final online N = 258), including individuals with and without depression and anxiety disorders.

RESULTS

There was a significant interaction between group (controls, depression, anxiety) and control-condition (extrinsic, intrinsic) on motivation where participants with depression showed lower extrinsic motivation and participants with anxiety showed higher extrinsic motivation compared to controls, while intrinsic motivation was broadly similar across the groups. There was also a significant group-by-valence (rewards, losses) interaction, where participants with major depressive disorder showed lower motivation to avoid losses, but participants with anxiety showed higher motivation to avoid losses. Finally, there was a double-dissociation with anhedonic symptoms whereby anticipatory anhedonia was associated with reduced extrinsic motivation, whereas consummatory anhedonia was associated with lower sensitivity to outcomes that modulated intrinsic behavior. These findings were robustly replicated in the second independent cohort.

CONCLUSIONS

Together this work demonstrates the effects of intrinsic and extrinsic control on altering motivation and outcome sensitivity, and shows how depression, anhedonia, and anxiety may influence these biases.

Neural and Computational Mechanisms of Motivation and Decision-making

Motivation is often thought to enhance adaptive decision-making by biasing actions toward rewards and away from punishment. Emerging evidence, however, points to a more nuanced view whereby motivation can both enhance and impair different aspects of decision-making. Model-based approaches have gained prominence over the past decade for developing more precise mechanistic explanations for how incentives impact goal-directed behavior. In this Special Focus, we highlight three studies that demonstrate how computational frameworks help decompose decision processes into constituent cognitive components, as well as formalize when and how motivational factors (e.g., monetary rewards) influence specific cognitive processes, decision-making strategies, and self-report measures. Finally, I conclude with a provocative suggestion based on recent advances in the field: that organisms do not merely seek to maximize the expected value of extrinsic incentives. Instead, they may be optimizing decision-making to achieve a desired internal state (e.g., homeostasis, effort, affect). Future investigation into such internal processes will be a fruitful endeavor for unlocking the cognitive, computational, and neural mechanisms of motivated decision-making.

"Regulating my anxiety worsens the safety of my driving": The synergistic influence of spatial anxiety and Self-regulation on driving behavior

Spatial Anxiety (SA) can be defined as the fear and apprehension experienced during tasks that require spatial thinking and may negatively impact the execution of daily actions. Although it has been explored in several research fields, limited research has explored the effects of SA on specific driving behaviours. In the current study, it was hypothesised that the severity of SA affects risky driving behaviours, and that this relationship is mediated by the driver's self-regulation abilities. Self-reported SA symptoms, driving self-regulation abilities, and risky driving behaviours (i.e., errors, violations, and lapses) were examined in 838 Italian drivers. Data were analysed through linear regressions and path analysis models, controlling for sociodemographic variables. The results showed the negative effects of SA on driving errors and lapses. As hypothesised, a driver's self-regulation abilities mediated the influence of SA on driving lapses, but not on errors nor violations. These findings suggest that the inclination to self-regulate the SA experienced while driving contribute to increase the occurrence of driving lapses. Showing specific pathways through which SA impacts risky driving, these results provide valuable insights for the development of 'driver-focused' road safety interventions.

Computational Mechanisms of Learning and Forgetting Differentiate Affective and Substance Use Disorders

Depression and anxiety are common, highly co-morbid conditions associated with a range of learning and decision-making deficits. While the computational mechanisms underlying these deficits have received growing attention, the transdiagnostic vs. diagnosis-specific nature of these mechanisms remains insufficiently characterized. Individuals with affective disorders (iADs; i.e., depression with or without co-morbid anxiety; N=168 and 74, respectively) completed a widely-used decision-making task. To establish diagnostic specificity, we also incorporated data from a sample of individuals with substance use disorders (iSUDs; N=147) and healthy comparisons (HCs; N=54). Computational modeling afforded separate measures of learning and forgetting rates, among other parameters. Compared to HCs, forgetting rates (reflecting recency bias) were elevated in both iADs and iSUDs (p = 0.007, η 2 = 0.022). In contrast, iADs showed faster learning rates for negative outcomes than iSUDs (p = 0.027, η 2 = 0.017), but they did not differ from HCs. Other model parameters associated with learning and information-seeking also showed suggestive relationships with early adversity and impulsivity. Our findings demonstrate distinct differences in learning and forgetting rates between iSUDs, iADs, and HCs, suggesting that different cognitive processes are affected in these conditions. These differences in decision-making processes and their correlations with symptom dimensions suggest that one could specifically develop interventions that target changing forgetting rates and/or learning from negative outcomes. These results pave the way for replication studies to confirm these relationships and establish their clinical implications.

You are How You Eat: Foraging Behavior as a Potential Novel Marker of Rat Affective State

Effective and safe foraging requires animals to behave according to the expectations they have about the rewards, threats, and costs in their environment. Since these factors are thought to be reflected in the animals' affective states, we can use foraging behavior as a window into those states. In this study, rats completed a foraging task in which they had repeatedly to decide whether to continue to harvest a food source despite increasing time costs, or to forgo food to switch to a different food source. Rats completed this task across two experiments using manipulations designed to induce both positive and negative, and shorter- and longer- term changes in affective state: removal and return of enrichment (Experiment 1), implementation and reversal of an unpredictable housing treatment (Experiment 1), and delivery of rewards (tickling or sucrose) and punishers (air-puff or back-handling) immediately prior to testing (Experiment 2). In Experiment 1, rats completed fewer trials and were more prone to switching between troughs when housed in standard, compared to enriched, housing conditions. In Experiment 2, rats completed more trials following pre-test tickling compared to pre-test sucrose delivery. However, we also found that they were prone to disengaging from the task, suggesting they were really choosing between three options: 'harvest', 'switch', or 'not work'. This limits the straightforward interpretation of the results. At present, foraging behavior within the context of this task cannot reliably be used as an indicator of an affective state in animals.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42761-024-00242-4.

Adolescent Internet Gaming Disorder and sensitivity to money and social rewards

Internet Gaming Disorder (IGD) is a behavioural addiction characterised by excessive exposure to addictive stimuli, resulting in reduced sensitivity of the brain's reward system towards everyday rewards. Online game addiction is prevalent among adolescents; however, it remains unclear if there are variations in reward processing patterns among adolescents with online game addiction. We compared differences in sensitivity to two types of rewards between patients with IGD and patients with Recreational Game Use (RGU) using the Monetary Incentive Delay (MID) paradigm and the Social Incentive Delay (SID) paradigm (Experiment 1). Additionally, we used a mixed reward latency paradigm, including both monetary and social rewards, to further explore the processing characteristics of IGD towards a mixture of these two rewards (Experiment 2). There were significant differences in the sensitivity of IGD and RGU to monetary and social rewards. Adolescents with IGD had significantly shorter reaction times to the four mixed rewards compared to RGU, while no significant differences were found between groups regarding sensitivity to specific individual rewards. However, the simultaneous presence of two rewards affected the processing speed and preference of adolescents with IGD. The reward processing characteristics observed in adolescents with online gaming disorder show specificity concerning the type and presentation of rewards, providing a theoretical foundation for diagnosing and treating adolescent online gaming addiction.

Spontaneous instrumental approach-avoidance learning in social contexts in autism

BACKGROUND

Individuals with Autism Spectrum Condition (ASC) are characterized by atypicalities in social interactions, compared to Typically Developing individuals (TD). The social motivation theory posits that these difficulties stem from diminished anticipation, reception, and/or learning from social rewards. Although learning from socioemotional outcomes is core to the theory, studies to date have been sparse and inconsistent. This possibly arises from a combination of theoretical, methodological and sample-related issues. Here, we assessed participants' ability to develop a spontaneous preference for actions that lead to desirable socioemotional outcomes (approaching/avoiding of happy/angry individuals, respectively), in an ecologically valid social scenario. We expected that learning abilities would be impaired in ASC individuals, particularly in response to affiliative social feedback.

METHOD

We ran an online social reinforcement learning task, on two large online cohorts with (n = 274) and without (n = 290) ASC, matched for gender, age and education. Participants had to indicate where they would sit in a waiting room. Each seat was associated with different probabilities of approaching/avoiding emotional individuals. Importantly, the task was implicit, as participants were not instructed to learn, and emotional expressions were never mentioned. We applied both categorical analyses contrasting the ASC and TD groups and dimensional factor analysis on affective questionnaires.

RESULTS

Contrary to our hypothesis, participants showed spontaneous learning from socioemotional outcomes, regardless of their diagnostic group. Yet, when accounting for dimensional variations in autistic traits, as well as depression and anxiety, two main findings emerged among females who failed to develop explicit learning strategies: (1) autism severity in ASC correlated with reduced learning to approach happy individuals; (2) anxiety-depression severity across both ASC and TD participants correlated with reduced learning to approach/avoid happy/angry individuals, respectively.

CONCLUSIONS

Implicit spontaneous learning from socioemotional outcomes is not generally impaired in autism but may be specifically associated with autism severity in females with ASC, when they do not have an explicit strategy for adapting to their social environment. Clinical diagnosis and intervention ought to take into account individual differences in their full complexity, including the presence of co-morbid anxiety and depression, when dealing with social atypicalities in autism.

Jumping to attributions during social evaluation

Social learning is crucial for human relationships and well-being. Self- and other- evaluations are universal experiences, playing key roles in many psychiatric disorders, particularly anxiety and depression. We aimed to deepen our understanding of the computational mechanisms behind social learning, which have been implicated in internalizing conditions like anxiety and depression. We built on prior work based on the Social Evaluation Learning Task (SELT) and introduced a new computational model to better explain rapid initial inferences and progressive refinement during serial social evaluations. The Social Evaluation Learning Task-Revised (SELT-R) was improved by stakeholder input, making it more engaging and suitable for adolescents. A sample of 130 adults from the UK completed the SELT-R and questionnaires assessing symptoms of depression and anxiety. 'Classify-refine' computational models were compared with previously successful Bayesian models. The 'classify-refine' models performed better, providing insight into how people infer the attributes and motives of others. Parameters of the best fitting model from the SELT-R were correlated with Anxiety factor scores, with higher symptoms associated with greater decision noise and higher (less flexible) policy certainty. Our results replicate findings regarding the classify-refine process and set the stage for future investigations into the cognitive mechanisms of self and other evaluations in internalizing disorders.

Who is more willing to engage in social rejection? The roles of self-esteem, rejection sensitivity, and negative affect in social rejection decisions

How do self-schemas and their consequences guide would-be-rejectors? When making decisions about whether to reject, individuals consider the difficulty and emotional consequences of rejecting, and both considerations are likely to involve self-schemas. In three preregistered studies, we examine the roles of self-esteem, rejection sensitivity, and symptoms of depression and anxiety in rejection decisions. In an initial set of studies (N1a = 214, N1b = 264), participants forecast their willingness to reject and their emotional responses in friendship (Study 1a) and romantic (Study 1a-1b) vignettes. In Study 2 (N2 = 259), participants who recently rejected rated that experience on the same measures. Correlates of negative self-schema were associated with negative emotions. Self-esteem, rejection sensitivity, and general distress were associated with forecasted difficulty rejecting, but only anxiety and general distress were associated with retrospectively reported increased difficulty. Taken together, psychological distress may decrease willingness to reject in a way that participants cannot predict.

Exploring Factors Affecting Acceptance of Fecal Microbiota Transplantation for Patients with Recurrent Urinary Tract Infections: a Descriptive Qualitative Study

Purpose

Patients with recurrent urinary tract infections face complex management challenges. Fecal microbiota transplantation is a superior treatment for chronic infectious diseases, but limited patient knowledge affects treatment decisions. This study aims to identify factors associated with hesitancy towards fecal microbiota transplantation among patients with recurrent urinary tract infections, to help physicians and nurses in providing accurate and useful information to patients.

Patients and Methods

A descriptive qualitative approach was employed, utilizing semi-structured interviews conducted with patients experiencing recurrent urinary tract infections who expressed hesitancy towards fecal microbiota transplantation. The interviews took place between September 2021 and December 2022. Thematic analysis was conducted on the semi-structured interviews to identify perceived facilitators and barriers associated with fecal microbiota transplantation.

Results

The analysis included interviews with thirty adult female patients with recurrent urinary tract infections. Four facilitators influencing patients' decision-making regarding fecal microbiota transplantation were identified: (1) the motivating role of hope and expectations for active patient participation; (2) the influence of healthcare providers, as well as family members and friends on patients' decisions to pursue fecal microbiota transplantation; (3) the patients' perception of fecal microbiota transplantation as a low-risk treatment option; and (4) the dedication to the advancement of medical treatments. In contrast, two primary barriers to accepting fecal microbiota transplantation were identified: (1) that conventional treatment controls disease activity, while fecal microbiota transplantation effects remain uncertain; and (2) that safety concerns surrounding fecal microbiota transplantation.

Conclusion

Comprehensive information about fecal microbiota transplantation, including donor selection, sample processing, the procedure, and potential discomfort, is essential for patients and families to make informed treatment decisions.

Registration

CHiCTR2100048970.

Large environmental changes reduce valence-dependent belief updating

When updating beliefs, humans tend to integrate more desirable information than undesirable information. In stable environments (low uncertainty and high predictability), this asymmetry favors motivation towards action and perceived self-efficacy. However, in changing environments (high uncertainty and low predictability), this process can lead to risk underestimation and increase unwanted costs. Here, we examine how people (n = 388) integrate threatening information during an abrupt environmental change (mandatory quarantine during the COVID-19 pandemic). Given that anxiety levels are associated with the magnitude of the updating belief asymmetry; we explore its relationship during this particular context. We report a significant reduction in asymmetrical belief updating during a large environmental change as individuals integrated desirable and undesirable information to the same extent. Moreover, this result was supported by computational modeling of the belief update task. However, we found that the reduction in asymmetrical belief updating was not homogeneous among people with different levels of Trait-anxiety. Individuals with higher levels of Trait-anxiety maintained a valence-dependent updating, as it occurs in stable environments. On the other hand, updating behavior was not associated with acute anxiety (State-Anxiety), health concerns (Health-Anxiety), or having positive expectations (Trait-Optimism). These results suggest that highly uncertain environments can generate adaptive changes in information integration. At the same time, it reveals the vulnerabilities of individuals with higher levels of anxiety to adapt the way they learn.

Health factors that influence sustainable behaviour in a single-player resource management game

Encouraging sustainable use of limited natural, social, and economic resources requires understanding the variety of ways in which people think about how resources work and how they adjust their behaviour (or not) as available resources fluctuate. Previous investigations which have focused on understanding how individuals navigate erodible resources, have tended to use group-based, common pool games. However, such social games make it difficult to disentangle whether resource erosion is linked to difficulty navigating the dynamics of the resource or caused by social factors. Here, in two experiments, we recruited 781 participants to play a single-player resource management game in which individuals were invited to harvest monetary rewards from a fully depletable but stochastically replenishing resource over time. We find that the ability to sustain a resource over successive harvesting opportunities (in order to maximize the total harvested rewards) is reliably worse in individuals reporting elevated psychological distress, the often cooccurring hazardous alcohol use, and elevated rates of delay discounting. The associations between resource outcomes, harmful alcohol use, and psychological distress remained substantial even once we had controlled for elevated discounting rates (as a form of impulsivity and a strong risk factor for these health challenges). By contrast, individuals who reported higher levels of financial literacy and general well-being achieved better resource outcomes. Our observations demonstrate that the capacity to respond effectively to the dynamics of a resource are compromised in individuals at risk of psychological and alcohol-related disorders.

A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals

Objective measures of animal emotion-like and mood-like states are essential for preclinical studies of affective disorders and for assessing the welfare of laboratory and other animals. However, the development and validation of measures of these affective states poses a challenge partly because the relationships between affect and its behavioural, physiological and cognitive signatures are complex. Here, we suggest that the crisp characterisations offered by computational modelling of the underlying, but unobservable, processes that mediate these signatures should provide better insights. Although this computational psychiatry approach has been widely used in human research in both health and disease, translational computational psychiatry studies remain few and far between. We explain how building computational models with data from animal studies could play a pivotal role in furthering our understanding of the aetiology of affective disorders, associated affective states and the likely underlying cognitive processes involved. We end by outlining the basic steps involved in a simple computational analysis.

The Approach of Physiotherapists in the Management of Patients with Persistent Pain and Comorbid Anxiety/Depression: Are There Any Differences between Male and Female Professionals?

Background and Objectives: Chronic pain is a prevalent condition that is frequently complicated by mood and anxiety disorders. The purpose of the present article is to identify differences in the management of patients with chronic pain and anxiety/mood disorders depending on the physiotherapists' gender. Materials and Methods: An ad hoc questionnaire was developed and sent to 327 physiotherapists by e-mail. The two groups identified by gender were compared by unpaired-sample t tests for continuous variables and χ2 tests for qualitative ones. A binary logistic regression was then performed with factors resulting as statistically significant in univariate analyses as independent variables and gender as a dependent one. Results: Female physiotherapists exhibited a higher level of confidence than male physiotherapists in administering continued physiotherapy for patients affected by Generalized Anxiety Disorder (GAD) (p = 0.01), as well as for individuals who had previously engaged with a mental health professional (p = 0.01). Furthermore, female physiotherapists believed that pharmacotherapy was less associated with motor side effects (p < 0.01) and more frequently recognized the importance of training to identify affective disorders (p = 0.01) and the need for more education in mental health (p = 0.01). The binary logistic regression model confirmed that female professionals were less likely to work = freelance (p = 0.015) and were more confident in the receival of physiotherapy by patients with GAD (p = 0.05). Conclusions: Female physiotherapists compared to male ones seem to be more comfortable with patients affected by mental conditions and to be more aware of the need for training on mental health. Further studies are needed to confirm the results of the present study.

'Eating is like experiencing a gamble': A qualitative study exploring the dietary decision-making process in adults with inflammatory bowel disease

BACKGROUND

For adults with inflammatory bowel disease (IBD), they experience many challenges in dietary decision-making. Thus, this study examined the perspective and experiences of adults with IBD in dietary decision-making.

OBJECTIVE

This study aimed to explore the perception and consideration of people with IBD in their daily dietary decisions through monitoring, interpretation and action during the decision-making process.

DESIGN

A qualitative study of individuals affected by IBD was conducted through semistructured interviews.

RESULTS

Twenty patients were recruited from four tertiary hospitals in Nanjing, China, and each participant completed a semistructured interview. The majority of participants reported on the process and experience of dietary decision-making. Key themes were categorised into three stages: (1) assessing needs, preferences and food cues (monitor); (2) moving from experience to expertise (interpret) and (3) balancing expectations amidst limitations (act). The majority of participants reported that their decisions were shaped by assessing current disease status and food cues. Those interviewed with IBD were willing to make tradeoffs for bowel stability, but their decisions were also influenced by past dietary experiences and traditional Chinese beliefs. The lack of awareness of dietary guidelines was a significant barrier to healthy eating decisions. Positive or negative feelings accompanied dietary decisions.

CONCLUSION

Although most people with IBD change their diet after diagnosis, the changes made are often inconsistent with existing dietary recommendations. Several factors can influence the dietary decision-making process. This study will help assess the experiences of people with IBD in dietary decision-making to encourage the formation of targeted dietary health and well-being interventions. Knowledge of nutrition and diet should be provided in education and training programmes for IBD management.

PATIENT OR PUBLIC CONTRIBUTION

The first three authors of this paper were the lead researchers in this study's design. These authors were mentored by patient researchers who also contributed to the manuscript, and the research process was co-lead and directed by other patient participants and consultants. The results of this paper were directly obtained from patient participants.

Material Hardship Predicts Response Bias in Loss-Averse Decisions: The Roles of Anxiety and Cognitive Control

Income poverty is associated with an enhanced tendency to avoid losses in economic decisions, which can be driven by a response bias (risk avoidance) and a valuation bias (loss aversion). However, the impact of non-income dimensions of poverty on these biases remains unclear. The current study tested the impact of material hardship on these biases, and the mediating effects of anxiety, depression, and cognitive control in these associations. Healthy adults (N = 188) completed questionnaire and behavioral measures of the variables. Results of regression-based analyses showed that participants who reported higher material hardship exhibited greater response bias, but not valuation bias. This effect was mediated by anxiety. Although material hardship predicted lower cognitive control, cognitive control did not mediate the association between material hardship and either type of bias. These findings suggest that material hardship may lead to economic decision-making biases because it impacts emotional states rather than cognitive control.

Interval Timing as a Computational Pathway From Early Life Adversity to Affective Disorders

Adverse early life experiences can have remarkably enduring negative consequences on mental health, with numerous, varied psychiatric conditions sharing this developmental origin. Yet, the mechanisms linking adverse experiences to these conditions remain poorly understood. Here, we draw on a principled model of interval timing to propose that statistically optimal adaptation of temporal representations to an unpredictable early life environment can produce key characteristics of anhedonia, a transdiagnostic symptom associated with affective disorders like depression and anxiety. The core observation is that early temporal unpredictability produces broader, more imprecise temporal expectations. As a result, reward anticipation is diminished, and associative learning is slowed. When agents with such representations are later introduced to more stable environments, they demonstrate a negativity bias, responding more to the omission of reward than its receipt. Increased encoding of negative events has been proposed to contribute to disorders with anhedonia as a symptom. We then examined how unpredictability interacts with another form of adversity, low reward availability. We found that unpredictability's effect was most strongly felt in richer environments, potentially leading to categorically different phenotypic expressions. In sum, our formalization suggests a single mechanism can help to link early life adversity to a range of behaviors associated with anhedonia, and offers novel insights into the interactive impacts of multiple adversities.

Factual and counterfactual learning in major adolescent depressive disorder, evidence from an instrumental learning study

BACKGROUND

The incidence of adolescent depressive disorder is globally skyrocketing in recent decades, albeit the causes and the decision deficits depression incurs has yet to be well-examined. With an instrumental learning task, the aim of the current study is to investigate the extent to which learning behavior deviates from that observed in healthy adolescent controls and track the underlying mechanistic channel for such a deviation.

METHODS

We recruited a group of adolescents with major depression and age-matched healthy control subjects to carry out the learning task with either gain or loss outcome and applied a reinforcement learning model that dissociates valence (positive v. negative) of reward prediction error and selection (chosen v. unchosen).

RESULTS

The results demonstrated that adolescent depressive patients performed significantly less well than the control group. Learning rates suggested that the optimistic bias that overall characterizes healthy adolescent subjects was absent for the depressive adolescent patients. Moreover, depressed adolescents exhibited an increased pessimistic bias for the counterfactual outcome. Lastly, individual difference analysis suggested that these observed biases, which significantly deviated from that observed in normal controls, were linked with the severity of depressive symoptoms as measured by HAMD scores.

CONCLUSIONS

By leveraging an incentivized instrumental learning task with computational modeling within a reinforcement learning framework, the current study reveals a mechanistic decision-making deficit in adolescent depressive disorder. These findings, which have implications for the identification of behavioral markers in depression, could support the clinical evaluation, including both diagnosis and prognosis of this disorder.

Anxiety and Depression in Metastatic Cancer: A Critical Review of Negative Impacts on Advance Care Planning and End-of-Life Decision Making With Practical Recommendations

PURPOSE

Providers treating adults with advanced cancer increasingly seek to engage patients and surrogates in advance care planning (ACP) and end-of-life (EOL) decision making; however, anxiety and depression may interfere with engagement. The intersection of these two key phenomena is examined among patients with metastatic cancer and their surrogates: the need to prepare for and engage in ACP and EOL decision making and the high prevalence of anxiety and depression.

METHODS

Using a critical review framework, we examine the specific ways that anxiety and depression are likely to affect both ACP and EOL decision making.

RESULTS

The review indicates that depression is associated with reduced compliance with treatment recommendations, and high anxiety may result in avoidance of difficult discussions involved in ACP and EOL decision making. Depression and anxiety are associated with increased decisional regret in the context of cancer treatment decision making, as well as a preference for passive (not active) decision making in an intensive care unit setting. Anxiety about death in patients with advanced cancer is associated with lower rates of completion of an advance directive or discussion of EOL wishes with the oncologist. Patients with advanced cancer and elevated anxiety report higher discordance between wanted versus received life-sustaining treatments, less trust in their physicians, and less comprehension of the information communicated by their physicians.

CONCLUSION

Anxiety and depression are commonly elevated among adults with advanced cancer and health care surrogates, and can result in less engagement and satisfaction with ACP, cancer treatment, and EOL decisions. We offer practical strategies and sample scripts for oncology care providers to use to reduce the effects of anxiety and depression in these contexts.

Approach-avoidance reinforcement learning as a translational and computational model of anxiety-related avoidance

Although avoidance is a prevalent feature of anxiety-related psychopathology, differences in the measurement of avoidance between humans and non-human animals hinder our progress in its theoretical understanding and treatment. To address this, we developed a novel translational measure of anxiety-related avoidance in the form of an approach-avoidance reinforcement learning task, by adapting a paradigm from the non-human animal literature to study the same cognitive processes in human participants. We used computational modelling to probe the putative cognitive mechanisms underlying approach-avoidance behaviour in this task and investigated how they relate to subjective task-induced anxiety. In a large online study (n = 372), participants who experienced greater task-induced anxiety avoided choices associated with punishment, even when this resulted in lower overall reward. Computational modelling revealed that this effect was explained by greater individual sensitivities to punishment relative to rewards. We replicated these findings in an independent sample (n = 627) and we also found fair-to-excellent reliability of measures of task performance in a sub-sample retested 1 week later (n = 57). Our findings demonstrate the potential of approach-avoidance reinforcement learning tasks as translational and computational models of anxiety-related avoidance. Future studies should assess the predictive validity of this approach in clinical samples and experimental manipulations of anxiety.

Anxiety associated with perceived uncontrollable stress enhances expectations of environmental volatility and impairs reward learning

Unavoidable stress can lead to perceived lack of control and learned helplessness, a risk factor for depression. Avoiding punishment and gaining rewards involve updating the values of actions based on experience. Such updating is however useful only if action values are sufficiently stable, something that a lack of control may impair. We examined whether self-reported stress uncontrollability during the first wave of the COVID-19 pandemic predicted impaired reward-learning. In a preregistered study during the first-wave of the COVID-19 pandemic, we used self-reported measures of depression, anxiety, uncontrollable stress, and COVID-19 risk from 427 online participants to predict performance in a three-armed-bandit probabilistic reward learning task. As hypothesised, uncontrollable stress predicted impaired learning, and a greater proportion of probabilistic errors following negative feedback for correct choices, an effect mediated by state anxiety. A parameter from the best-fitting hidden Markov model that estimates expected beliefs that the identity of the optimal choice will shift across images, mediated effects of state anxiety on probabilistic errors and learning deficits. Our findings show that following uncontrollable stress, anxiety promotes an overly volatile representation of the reward-structure of uncertain environments, impairing reward attainment, which is a potential path to anhedonia in depression.

Neural signatures of stress susceptibility and resilience in the amygdala-hippocampal network

The neural dynamics that underlie divergent anhedonic responses to stress remain unclear. Here, we identified neuronal dynamics in an amygdala-hippocampal circuit that distinguish stress resilience and susceptibility. In a reward-choice task, basolateral amygdala (BLA) activity in resilient mice showed enhanced discrimination of upcoming reward choices. In contrast, a rumination-like signature emerged in the BLA of susceptible mice; a linear decoder could classify the intention to switch or stay on a previously chosen reward. Spontaneous activity in the BLA of susceptible mice was higher dimensional than controls, reflecting the exploration of a larger number of distinct neural states. Manipulation of vCA1-BLA inputs rescued dysfunctional neural dynamics and anhedonia in susceptible mice, suggesting that targeting this pathway can enhance BLA circuit function and ameliorate of depression-related behaviors.

Uncertainty as a driver of the youth mental health crisis

Mental health problems in young people have been on the rise for over a decade, with that trend accelerating during the pandemic. This review proposes that the catalyst effect of the pandemic offers insights into a key driver of increases in youth depression and anxiety: greater uncertainty. Uncertainty about many aspects of everyday life, including social connections, education, job security and health, increased during the pandemic, and this coincided with increasing rates of depression and anxiety. Lab-based developmental cognitive and clinical neuroscience research on tolerance of uncertainty and adolescent mental health shows that when adolescents fail to show age-typical tolerance of uncertainty, they are at greater risk of mental health problems. Avenues for future research to understand and promote tolerance of uncertainty in adolescents are proposed.

Toward a computational understanding of how reminiscing about positive autobiographical memories influences decision-making under risk

Recent computational psychiatric research has dissected decision-making under risk into different underlying cognitive computational constructs and identified disease-specific changes in these constructs. Studies are underway to investigate what kind of behavioral or psychological interventions can restore these cognitive, computational constructs. In our previous study, we showed that reminiscing about positive autobiographical memories reduced risk aversion and affected probability weighting in the opposite direction from that observed in psychiatric disorders. However, in that study, we compared positive versus neutral memory retrieval by using a within-subjects crossover posttest design. Therefore, the change of decision-making from baseline is unclear. Furthermore, we used a hypothetical decision-making task and did not include monetary incentives. We attempt to address these limitations and investigated how reminiscing about positive autobiographical memories influences decision-making under risk using a between-subjects pretest posttest comparison design with performance-contingent monetary incentives. In thirty-eight healthy, young adults, we found that reminiscing about positive memories reinforced the commonly observed inverted S-shaped nonlinear probability weighting (f = 0.345, medium to large in effect size). In contrast, reminiscing about positive memories did not affect risk aversion in general. Given that the change in probability weighting after reminiscing about positive memories is in the opposite direction from that observed in psychiatric disorders, our results indicate that positive autobiographical memory retrieval might be a useful behavioral intervention strategy for amending the altered decision-making under risk in psychiatric diseases.

Understanding anxiety symptoms as aberrant defensive responding along the threat imminence continuum

Threat-anticipatory defensive responses have evolved to promote survival in a dynamic world. While inherently adaptive, aberrant expression of defensive responses to potential threat could manifest as pathological anxiety, which is prevalent, impairing, and associated with adverse outcomes. Extensive translational neuroscience research indicates that normative defensive responses are organized by threat imminence, such that distinct response patterns are observed in each phase of threat encounter and orchestrated by partially conserved neural circuitry. Anxiety symptoms, such as excessive and pervasive worry, physiological arousal, and avoidance behavior, may reflect aberrant expression of otherwise normative defensive responses, and therefore follow the same imminence-based organization. Here, empirical evidence linking aberrant expression of specific, imminence-dependent defensive responding to distinct anxiety symptoms is reviewed, and plausible contributing neural circuitry is highlighted. Drawing from translational and clinical research, the proposed framework informs our understanding of pathological anxiety by grounding anxiety symptoms in conserved psychobiological mechanisms. Potential implications for research and treatment are discussed.

Adaptive Design Optimization as a Promising Tool for Reliable and Efficient Computational Fingerprinting

A key challenge in understanding mental (dys)functions is their etiological and functional heterogeneity, and several multidimensional assessments have been proposed for their comprehensive characterization. However, such assessments require lengthy testing, which may hinder reliable and efficient characterization of individual differences due to increased fatigue and distraction, especially in clinical populations. Computational modeling may address this challenge as it often provides more reliable measures of latent neurocognitive processes underlying observed behaviors and captures individual differences better than traditional assessments. However, even with a state-of-the-art hierarchical modeling approach, reliable estimation of model parameters still requires a large number of trials. Recent work suggests that Bayesian adaptive design optimization (ADO) is a promising way to address these challenges. With ADO, experimental design is optimized adaptively from trial to trial to extract the maximum amount of information about an individual's characteristics. In this review, we first describe the ADO methodology and then summarize recent work demonstrating that ADO increases the reliability and efficiency of latent neurocognitive measures. We conclude by discussing the challenges and future directions of ADO and proposing development of ADO-based computational fingerprints to reliably and efficiently characterize the heterogeneous profiles of psychiatric disorders.

The nature and neurobiology of fear and anxiety: State of the science and opportunities for accelerating discovery

Fear and anxiety play a central role in mammalian life, and there is considerable interest in clarifying their nature, identifying their biological underpinnings, and determining their consequences for health and disease. Here we provide a roundtable discussion on the nature and biological bases of fear- and anxiety-related states, traits, and disorders. The discussants include scientists familiar with a wide variety of populations and a broad spectrum of techniques. The goal of the roundtable was to take stock of the state of the science and provide a roadmap to the next generation of fear and anxiety research. Much of the discussion centered on the key challenges facing the field, the most fruitful avenues for future research, and emerging opportunities for accelerating discovery, with implications for scientists, funders, and other stakeholders. Understanding fear and anxiety is a matter of practical importance. Anxiety disorders are a leading burden on public health and existing treatments are far from curative, underscoring the urgency of developing a deeper understanding of the factors governing threat-related emotions.

Internet addiction and its relationship with attention deficit hyperactivity disorder (ADHD) symptoms, anxiety and stress among university students in Malaysia

BACKGROUND AND AIMS

There is growing evidence on the contribution of psychological factors to internet addiction; yet it remains inconsistent and deserves further exploration. The aim of this study was to determine the relationship between the psychological symptoms (Attention Deficit Hyperactivity Disorder (ADHD) symptoms, stress, depression, anxiety and loneliness) and internet addiction (IA) among the university students in Malaysia.

MATERIALS AND METHODS

A total of 480 students from different faculties in a Malaysian public university participated in this study. They were selected by simple random sampling method. They completed self-administered questionnaires including the Malay Version of Internet Addiction Test (MVIAT)) to measure internet addiction and Adult Self-Report Scale (ASRS) Symptom Checklist, Depression Anxiety Stress Scales (DASS) and UCLA Loneliness Scale (Version 3) to assess for ADHD symptoms, depression, anxiety, stress, and loneliness respectively.

RESULTS

The prevalence of IA among university students was 33.33% (n = 160). The respondents' mean age was 21.01 ± 1.29 years old and they were predominantly females (73.1%) and Malays (59.4%). Binary logistic regression showed that gender (p = 0.002; OR = 0.463, CI = 0.284-0.754), ADHD inattention (p = 0.003; OR = 2.063, CI = 1.273-3.345), ADHD hyperactivity (p<0.0001; OR = 2.427, CI = 1.495-3.939), stress (p = 0.048; OR = 1.795, CI = 1.004-3.210) and loneliness (p = 0.022; OR = 1.741, CI = 1.084-2.794) were significantly associated with IA.

CONCLUSION

A third of university students had IA. In addition, we found that those who were at risk of IA were males, with ADHD symptoms of inattention and hyperactivity, who reported stress and loneliness. Preventive strategy to curb internet addiction and its negative sequelae may consider these factors in its development and implementation.

Decision making and executive functions in problematic pornography use

Introduction

Previous research on cognitive functions in Compulsive Sexual Behavior Disorder (CSBD) and problematic pornography use (PPU) reported inconsistent findings and mostly included sexual pictures in the used tasks. The role of general executive functions and cognitive competences (without the presence of appetitive stimuli) in the context of PPU is largely unexplored.

Methods

This study investigated differences between individuals with high versus low problem severity of PPU regarding decision making and executive functions. The sample of the laboratory study consisted of N = 102 male adults. Besides measures of trait impulsivity, we used standard neuropsychological tests (Trail Making Test and three-back working memory task) and an intertemporal risky choice paradigm, the Cards & Lottery Task (CLT).

Results

The results show heightened impulsivity (urgency and deficits in perseverance) in individuals with high PPU, but no differences regarding performance in the CLT and executive function tasks.

Discussion

The findings indicate that PPU might be associated with impulsive behavior when experiencing strong emotions (urgency) and deficient cognitive performance especially in the presence of sexual stimuli but not in general.

Explaining reversal learning deficits in anxiety with electrophysiological evidence

Reversal learning is a crucial aspect of behavioral flexibility that plays a significant role in environmental adaptation and development. While previous studies have established a link between anxiety and impaired reversal learning ability, the underlying mechanisms behind this association remain unclear. This study employed a probabilistic reversal learning task with electroencephalographic recording to investigate these mechanisms. Participants were divided into two groups based on their scores on Spielberger's State-Trait Anxiety Inventory: high trait-anxiety (HTA) and low trait-anxiety (LTA), consisting of 50 individuals in each group. The results showed that the HTA group had poorer reversal learning performance than the LTA group, including a lower tendency to shift to the new optimal option after rule reversals (reversal-shift). The study also examined event-related potentials elicited by reversals and found that although the N1 (related to attention allocation), feedback-related negativity (FRN: related to belief updating), and P3 (related to response inhibition) were all sensitive to the grouping factor, only the FRN elicited by reversal-shift mediated the relationship between anxiety and the number/reaction time of reversal-shift. From these findings, we suggest that abnormalities in belief updating may contribute to the impaired reversal learning performance observed in anxious individuals. In our opinion, this study sheds light on potential targets for interventions aimed at improving behavioral flexibility in anxious individuals.

Acute caffeine differently affects risk-taking and the expression of BDNF and of adenosine and opioid receptors in rats with high or low anxiety-like behavior

Anxiety disorders are common psychiatric conditions with a partially elucidated neurobiology. Caffeine, an unspecific adenosine receptor antagonist, is a common psychostimulant with anxiogenic effects in sensitive individuals. High doses of caffeine produce anxiety-like behavior in rats but it is not known if this is specific for rats with high baseline anxiety-like behavior. Thus, the aim of this study was to investigate general behavior, risk-taking, and anxiety-like behavior, as well as mRNA expression (adenosine A2A and A1, dopamine D2, and, μ, κ, δ opioid, receptors, BDNF, c-fos, IGF-1) in amygdala, caudate putamen, frontal cortex, hippocampus, hypothalamus, after an acute dose of caffeine. Untreated rats were screened using the elevated plus maze (EPM), giving each rat a score on anxiety-like behavior based on their time spent in the open arms, and categorized into a high or low anxiety-like behavior group accordingly. Three weeks after categorization, the rats were treated with 50 mg/kg caffeine and their behavior profile was studied in the multivariate concentric square field (MCSF) test, and one week later in the EPM. qPCR was performed on selected genes and corticosterone plasma levels were measured using ELISA. The results demonstrated that the high anxiety-like behavior rats treated with caffeine spent less time in risk areas of the MCSF and resituated towards the sheltered areas, a behavior accompanied by lower mRNA expression of adenosine A2A receptors in caudate putamen and increased BDNF expression in hippocampus. These results support the hypothesis that caffeine affects individuals differently depending on their baseline anxiety-like behavior, possibly involving adenosine receptors. This highlights the importance of adenosine receptors as a possible drug target for anxiety disorders, although further research is needed to fully elucidate the neurobiological mechanisms of caffeine on anxiety disorders.

Anxiety and depression related abnormalities in socio-affective learning

Affective distress (as observed in anxiety and depression) has been observed to be related to insufficient sensitivity to changing reinforcement during operant learning. Whether such findings are specific to anxiety or depression is unclear given a wider literature relating negative affect to abnormal learning and the possibility that relationships are not consistent across incentive types (i.e., punishment and reward) and outcomes (i.e., positive or negative). In two separate samples (n = 100; n = 88), participants completed an operant learning task with positive or negative, and neutral socio-affective feedback, designed to assess adaptive responses to changing environmental volatility. Individual parameter estimates were generated with hierarchical Bayesian modelling. Effects of manipulations were modelled by decomposing parameters into a linear combination of effects on the logit scale. While effects tended to support prior work, neither general affective distress nor anxiety or depression were consistently related to a decrease in the adaptive adjustment of learning-rates in response to changing environmental volatility (Sample 1: β_{α:volatility} = -0.01, 95 % HDI = -0.14, 0.13; Sample 2: β_{α:volatility} = -0.15, 95 % HDI = -0.37, 0.05). Interaction effects in Sample 1 suggested that while distress was associated with decrements in adaptive learning under punishment-maximisation, it was associated with improvements under reward-maximisation. While our results are broadly consistent with prior work, they suggest that the role of anxiety or depression in volatility learning, if present, is subtle and difficult to detect. Inconsistencies between our samples, along with issues of parameter identifiability complicated interpretation.

Neurocomputational mechanisms underlying fear-biased adaptation learning in changing environments

Humans are able to adapt to the fast-changing world by estimating statistical regularities of the environment. Although fear can profoundly impact adaptive behaviors, the computational and neural mechanisms underlying this phenomenon remain elusive. Here, we conducted a behavioral experiment (n = 21) and a functional magnetic resonance imaging experiment (n = 37) with a novel cue-biased adaptation learning task, during which we simultaneously manipulated emotional valence (fearful/neutral expressions of the cue) and environmental volatility (frequent/infrequent reversals of reward probabilities). Across 2 experiments, computational modeling consistently revealed a higher learning rate for the environment with frequent versus infrequent reversals following neutral cues. In contrast, this flexible adjustment was absent in the environment with fearful cues, suggesting a suppressive role of fear in adaptation to environmental volatility. This suppressive effect was underpinned by activity of the ventral striatum, hippocampus, and dorsal anterior cingulate cortex (dACC) as well as increased functional connectivity between the dACC and temporal-parietal junction (TPJ) for fear with environmental volatility. Dynamic causal modeling identified that the driving effect was located in the TPJ and was associated with dACC activation, suggesting that the suppression of fear on adaptive behaviors occurs at the early stage of bottom-up processing. These findings provide a neuro-computational account of how fear interferes with adaptation to volatility during dynamic environments.

Transdiagnostic computations of uncertainty: towards a new lens on intolerance of uncertainty

People radically differ in how they cope with uncertainty. Clinical researchers describe a dispositional characteristic known as "intolerance of uncertainty", a tendency to find uncertainty aversive, reported to be elevated across psychiatric and neurodevelopmental conditions. Concurrently, recent research in computational psychiatry has leveraged theoretical work to characterise individual differences in uncertainty processing. Under this framework, differences in how people estimate different forms of uncertainty can contribute to mental health difficulties. In this review, we briefly outline the concept of intolerance of uncertainty within its clinical context, and we argue that the mechanisms underlying this construct may be further elucidated through modelling how individuals make inferences about uncertainty. We will review the evidence linking psychopathology to different computationally specified forms of uncertainty and consider how these findings might suggest distinct mechanistic routes towards intolerance of uncertainty. We also discuss the implications of this computational approach for behavioural and pharmacological interventions, as well as the importance of different cognitive domains and subjective experiences in studying uncertainty processing.

Spatiotemporal Precision of Neuroimaging in Psychiatry

Aberrant patterns of cognition, perception, and behavior seen in psychiatric disorders are thought to be driven by a complex interplay of neural processes that evolve at a rapid temporal scale. Understanding these dynamic processes in vivo in humans has been hampered by a trade-off between spatial and temporal resolutions inherent to current neuroimaging technology. A recent trend in psychiatric research has been the use of high temporal resolution imaging, particularly magnetoencephalography, often in conjunction with sophisticated machine learning decoding techniques. Developments here promise novel insights into the spatiotemporal dynamics of cognitive phenomena, including domains relevant to psychiatric illnesses such as reward and avoidance learning, memory, and planning. This review considers recent advances afforded by exploiting this increased spatiotemporal precision, with specific reference to applications that seek to drive a mechanistic understanding of psychopathology and the realization of preclinical translation.

Computational Mechanisms of Addiction and Anxiety: A Developmental Perspective

A central goal of computational psychiatry is to identify systematic relationships between transdiagnostic dimensions of psychiatric symptomatology and the latent learning and decision-making computations that inform individuals' thoughts, feelings, and choices. Most psychiatric disorders emerge prior to adulthood, yet little work has extended these computational approaches to study the development of psychopathology. Here, we lay out a roadmap for future studies implementing this approach by developing empirically and theoretically informed hypotheses about how developmental changes in model-based control of action and Pavlovian learning processes may modulate vulnerability to anxiety and addiction. We highlight how insights from studies leveraging computational approaches to characterize the normative developmental trajectories of clinically relevant learning and decision-making processes may suggest promising avenues for future developmental computational psychiatry research.

Invasive Computational Psychiatry

Computational psychiatry, a relatively new yet prolific field that aims to understand psychiatric disorders with formal theories about the brain, has seen tremendous growth in the past decade. Despite initial excitement, actual progress made by computational psychiatry seems stagnant. Meanwhile, understanding of the human brain has benefited tremendously from recent progress in intracranial neuroscience. Specifically, invasive techniques such as stereotactic electroencephalography, electrocorticography, and deep brain stimulation have provided a unique opportunity to precisely measure and causally modulate neurophysiological activity in the living human brain. In this review, we summarize progress and drawbacks in both computational psychiatry and invasive electrophysiology and propose that their combination presents a highly promising new direction-invasive computational psychiatry. The value of this approach is at least twofold. First, it advances our mechanistic understanding of the neural computations of mental states by providing a spatiotemporally precise depiction of neural activity that is traditionally unattainable using noninvasive techniques with human subjects. Second, it offers a direct and immediate way to modulate brain states through stimulation of algorithmically defined neural regions and circuits (i.e., algorithmic targeting), thus providing both causal and therapeutic insights. We then present depression as a use case where the combination of computational and invasive approaches has already shown initial success. We conclude by outlining future directions as a road map for this exciting new field as well as presenting cautions about issues such as ethical concerns and generalizability of findings.

Life skills training: Can it increases self esteem and reduces student anxiety?

Students are always required to have good self-esteem. Still, psychological problems, such as excessive anxiety, will cause discomfort and distress, avoid social situations, and interfere with daily life, made them feel worthless. The purpose of the study was to determine the effect of self-esteem on anxiety through life skills training. The research subjects were 14 students divided into two groups, namely the experimental group and the control group. The measurement uses a self-esteem scale and an anxiety scale. Data analysis used non-parametric analysis, namely Mann Whitney, Wilcoxon, and Spearman's Rank Correlation Test. The results of this study indicate a significant decrease in anxiety with increased self-esteem using life skills training for students.

Altered social decision making in patients with chronic pain

BACKGROUND

Chronic pain affects up to 20% of the population, impairs quality of life and reduces social participation. Previous research reported that pain-related perceived injustice covaries with these negative consequences. The current study probed whether chronic pain patients responded more strongly to disadvantageous social inequity than healthy individuals.

METHODS

We administered the Ultimatum Game, a neuroeconomic social exchange game, where a sum of money is split between two players to a large sample of patients with chronic pain disorder with somatic and psychological factors (n = 102) and healthy controls (n = 101). Anonymised, and in truth experimentally controlled, co-players proposed a split, and our participants either accepted or rejected these offers.

RESULTS

Chronic pain patients were hypersensitive to disadvantageous inequity and punished their co-players for proposed unequal splits more often than healthy controls. Furthermore, this systematic shift in social decision making was independent of patients' performance on tests of executive functions and risk-sensitive (non-social) decision making .

CONCLUSIONS

Our findings indicate that chronic pain is associated with anomalies in social decision making (compared to healthy controls) and hypersensitivity to social inequity that is likely to negatively impact social partaking and thereby the quality of life.

Anterior cingulate and medial prefrontal cortex oscillations underlie learning alterations in trait anxiety in humans

Anxiety has been linked to altered belief formation and uncertainty estimation, impacting learning. Identifying the neural processes underlying these changes is important for understanding brain pathology. Here, we show that oscillatory activity in the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC) explains anxiety-related learning alterations. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a probabilistic reward-based learning task. HTA undermined learning through an overestimation of volatility, leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. On a neural level, we observed increased gamma activity in the ACC, dmPFC, and OFC during encoding of precision-weighted prediction errors in HTA, accompanied by suppressed ACC alpha/beta activity. Our findings support the association between altered learning and belief updating in anxiety and changes in gamma and alpha/beta activity in the ACC, dmPFC, and OFC.