Early life adversities are associated with lower expected value signaling in the adult brain.

BACKGROUND: Early adverse experiences are assumed to affect fundamental processes of reward learning and decision-making. However, computational neuroimaging studies investigating these circuits in the context of adversity are sparse and limited to studies conducted in adolescent samples, leaving the long-term effects unexplored. METHODS: Using data from a longitudinal birth cohort study (n=156, 87 females), we investigated associations between adversities and computational markers of reward learning (i.e., expected value (EV), prediction errors). At the age of 33 years, all participants completed an fMRI-based passive avoidance task. Psychopathology measures were collected at the time of fMRI investigation and during the COVID-19 pandemic. We applied a principal component analysis to capture common variation across seven adversity measures. The resulting adversity factors (factor-1: postnatal psychosocial adversities and prenatal maternal smoking, factor-2: prenatal maternal stress and obstetric adversity, and factor-3: lower maternal stimulation) were linked with psychopathology and neural responses in the core reward network using multiple regression analysis. RESULTS: We found that the adversity dimension primarily informed by lower maternal stimulation was linked to lower EV representation in the right putamen, right nucleus accumbens (NAcc), and anterior cingulate cortex. EV encoding in the right NAcc further mediated the relationship between this adversity dimension and psychopathology and predicted higher withdrawn symptoms during the COVID-19 pandemic. CONCLUSIONS: Our results suggested that early adverse experiences in caregiver context might have a long-term disruptive effect on reward learning in reward-related brain regions, which can be associated with suboptimal decision-making and thereby may increase the vulnerability of developing psychopathology.

Different components of cognitive-behavioral therapy affect specific cognitive mechanisms.

Psychological therapies are among the most effective treatments for common mental health problems-however, we still know relatively little about how exactly they improve symptoms. Here, we demonstrate the power of combining theory with computational methods to parse effects of different components of cognitive-behavioral therapies onto underlying mechanisms. Specifically, we present data from a series of randomized-controlled experiments testing the effects of brief components of behavioral and cognitive therapies on different cognitive processes, using well-validated behavioral measures and associated computational models. A goal setting intervention, based on behavioral activation therapy activities, reliably and selectively reduced sensitivity to effort when deciding how to act to gain reward. By contrast, a cognitive restructuring intervention, based on cognitive therapy materials, reliably and selectively reduced the tendency to attribute negative everyday events to self-related causes. The effects of each intervention were specific to these respective measures. Our approach provides a basis for beginning to understand how different elements of common psychotherapy programs may work.

Closing the accessibility gap to mental health treatment with a personalized self-referral chatbot.

Inequality in treatment access is a pressing issue in most healthcare systems across many medical disciplines. In mental healthcare, reduced treatment access for minorities is ubiquitous but remedies are sparse. Here we demonstrate that digital tools can reduce the accessibility gap by addressing several key barriers. In a multisite observational study of 129,400 patients within England's NHS services, we evaluated the impact of a personalized artificial intelligence-enabled self-referral chatbot on patient referral volume and diversity in ethnicity, gender and sexual orientation. We found that services that used this digital solution identified substantially increased referrals (15% increase versus 6% increase in control services). Critically, this increase was particularly pronounced in minorities, such as nonbinary (179% increase) and ethnic minority individuals (29% increase). Using natural language processing to analyze qualitative feedback from 42,332 individuals, we found that the chatbot's human-free nature and the patients' self-realization of their need for treatment were potential drivers for the observed improvement in the diversity of access. This provides strong evidence that digital tools may help overcome the pervasive inequality in mental healthcare.

Self-reported childhood family adversity is linked to an attenuated gain of trust during adolescence.

A longstanding proposal in developmental research is that childhood family experiences provide a template that shapes a capacity for trust-based social relationships. We leveraged longitudinal data from a cohort of healthy adolescents (n = 570, aged 14-25), which included decision-making and psychometric data, to characterise normative developmental trajectories of trust behaviour and inter-individual differences therein. Extending on previous cross-sectional findings from the same cohort, we show that a task-based measure of trust increases longitudinally from adolescence into young adulthood. Computational modelling suggests this is due to a decrease in social risk aversion. Self-reported family adversity attenuates this developmental gain in trust behaviour, and within our computational model, this relates to a higher 'irritability' parameter in those reporting greater adversity. Unconditional trust at measurement time point T1 predicts the longitudinal trajectory of self-reported peer relation quality, particularly so for those with higher family adversity, consistent with trust acting as a resilience factor.

Probing apathy in children and adolescents with the Apathy Motivation Index-Child version.

Apathy is linked to mental health and altered neurocognitive functions such as learning and decision-making in healthy adults. Mental health problems typically begin to emerge during adolescence, yet little is known about how apathy develops due to an absence of quantitative measurements specific to young people. Here, we present and evaluate the Apathy Motivation Index-Child Version (AMI-CV) for children and adolescents. We show across two samples of young people (aged 8 to 17 years, total N = 191) tested in schools in the UK and on a smartphone app, that the AMI-CV is a short, psychometrically sound measure to assess levels of apathy and motivation in young people. Similar to adult versions, the AMI-CV captures three distinct apathy domains: Behavioural Activation, Social Motivation and Emotional Sensitivity. The AMI-CV showed excellent construct validity with an alternative measure of apathy and external validity replicating specific links with related mental health traits shown in adults. Our results provide a short measure of self-reported apathy in young people that enables research into apathy development. The AMI-CV can be used in conjunction with the adult version to investigate the impact of levels of apathy across the lifespan.

Boosting Serotonin Increases Information Gathering by Reducing Subjective Cognitive Costs.

Serotonin is implicated in the valuation of aversive costs, such as delay or physical effort. However, its role in governing sensitivity to cognitive effort, for example, deliberation costs during information gathering, is unclear. We show that treatment with a serotonergic antidepressant in healthy human individuals of either sex enhances a willingness to gather information when trying to maximize reward. Using computational modeling, we show this arises from a diminished sensitivity to subjective deliberation costs during the sampling process. This result is consistent with the notion that serotonin alleviates sensitivity to aversive costs in a domain-general fashion, with implications for its potential contribution to a positive impact on motivational deficits in psychiatric disorders.SIGNIFICANCE STATEMENT Gathering information about the world is essential for successfully navigating it. However, sampling information is costly, and we need to balance between gathering too little and too much information. The neurocomputational mechanisms underlying this arbitration between a putative gain, such as reward, and the associated costs, such as allocation of cognitive resources, remain unclear. In this study, we show that week-long daily treatment with a serotonergic antidepressant enhances a willingness to gather information when trying to maximize reward. Computational modeling indicates this arises from a reduced perception of aversive costs, rendering information gathering less cognitively effortful. This finding points to a candidate mechanism by which serotonergic treatment might help alleviate motivational deficits in a range of mental illnesses.

Computational and behavioral markers of model-based decision making in childhood.

Human decision-making is underpinned by distinct systems that differ in flexibility and associated cognitive cost. A widely accepted dichotomy distinguishes between a cheap but rigid model-free system and a flexible but costly model-based system. Typically, humans use a hybrid of both types of decision-making depending on environmental demands. However, children's use of a model-based system during decision-making has not yet been shown. While prior developmental work has identified simple building blocks of model-based reasoning in young children (1-4 years old), there has been little evidence of this complex cognitive system influencing behavior before adolescence. Here, by using a modified task to make engagement in cognitively costly strategies more rewarding, we show that children aged 5-11-years (N = 85), including the youngest children, displayed multiple indicators of model-based decision making, and that the degree of its use increased throughout childhood. Unlike adults (N = 24), however, children did not display adaptive arbitration between model-free and model-based decision-making. Our results demonstrate that throughout childhood, children can engage in highly sophisticated and costly decision-making strategies. However, the flexible arbitration between decision-making strategies might be a critically late-developing component in human development.

From promise to practice: towards the realisation of AI-informed mental health care.

In this Series paper, we explore the promises and challenges of artificial intelligence (AI)-based precision medicine tools in mental health care from clinical, ethical, and regulatory perspectives. The real-world implementation of these tools is increasingly considered the prime solution for key issues in mental health, such as delayed, inaccurate, and inefficient care delivery. Similarly, machine-learning-based empirical strategies are becoming commonplace in psychiatric research because of their potential to adequately deconstruct the biopsychosocial complexity of mental health disorders, and hence to improve nosology of prognostic and preventive paradigms. However, the implementation steps needed to translate these promises into practice are currently hampered by multiple interacting challenges. These obstructions range from the current technology-distant state of clinical practice, over the lack of valid real-world databases required to feed data-intensive AI algorithms, to model development and validation considerations being disconnected from the core principles of clinical utility and ethical acceptability. In this Series paper, we provide recommendations on how these challenges could be addressed from an interdisciplinary perspective to pave the way towards a framework for mental health care, leveraging the combined strengths of human intelligence and AI.

The promise of a model-based psychiatry: building computational models of mental ill health.

Computational models have great potential to revolutionise psychiatry research and clinical practice. These models are now used across multiple subfields, including computational psychiatry and precision psychiatry. Their goals vary from understanding mechanisms underlying disorders to deriving reliable classification and personalised predictions. Rapid growth of new tools and data sources (eg, digital data, gamification, and social media) requires an understanding of the constraints and advantages of different modelling approaches in psychiatry. In this Series paper, we take a critical look at the range of computational models that are used in psychiatry and evaluate their advantages and disadvantages for different purposes and data sources. We describe mechanism-driven and mechanism-agnostic computational models and discuss how interpretability of models is crucial for clinical translation. Based on these evaluations, we provide recommendations on how to build computational models that are clinically useful.

FENS-Kavli Network of Excellence: Science needs strong European cohesion.

Decades of scientific collaboration have brought innovation, prosperity and wide societal benefit to Europe. However, recent political events have impacted pan-European research and collaborations, and solutions are yet to materialise. Here, we argue that a vibrant, united European Research community led by its members and independent from political bodies is needed for Europe to remain a successful, interconnected scientific hub and keep delivering globally competitive science. The Federation of European Neuroscience Societies (FENS) is in an ideal position to play a paramount role in this endeavour.

Value-free random exploration is linked to impulsivity.

Deciding whether to forgo a good choice in favour of exploring a potentially more rewarding alternative is one of the most challenging arbitrations both in human reasoning and in artificial intelligence. Humans show substantial variability in their exploration, and theoretical (but only limited empirical) work has suggested that excessive exploration is a critical mechanism underlying the psychiatric dimension of impulsivity. In this registered report, we put these theories to test using large online samples, dimensional analyses, and computational modelling. Capitalising on recent advances in disentangling distinct human exploration strategies, we not only demonstrate that impulsivity is associated with a specific form of exploration-value-free random exploration-but also explore links between exploration and other psychiatric dimensions.

Exploration heuristics decrease during youth.

Deciding between exploring new avenues and exploiting known choices is central to learning, and this exploration-exploitation trade-off changes during development. Exploration is not a unitary concept, and humans deploy multiple distinct mechanisms, but little is known about their specific emergence during development. Using a previously validated task in adults, changes in exploration mechanisms were investigated between childhood (8-9 y/o, N = 26; 16 females), early (12-13 y/o, N = 38; 21 females), and late adolescence (16-17 y/o, N = 33; 19 females) in ethnically and socially diverse schools from disadvantaged areas. We find an increased usage of a computationally light exploration heuristic in younger groups, effectively accommodating their limited neurocognitive resources. Moreover, this heuristic was associated with self-reported, attention-deficit/hyperactivity disorder symptoms in this population-based sample. This study enriches our mechanistic understanding about how exploration strategies mature during development.

A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement.

Low-intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation, applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional MRI (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability. Despite the growing number of published reports, there are no consensus-based checklists for disclosing methodological details of concurrent tES-fMRI studies. The objective of this work was to develop a consensus-based checklist of reporting standards for concurrent tES-fMRI studies to support methodological rigor, transparency and reproducibility (ContES checklist). A two-phase Delphi consensus process was conducted by a steering committee (SC) of 13 members and 49 expert panelists through the International Network of the tES-fMRI Consortium. The process began with a circulation of a preliminary checklist of essential items and additional recommendations, developed by the SC on the basis of a systematic review of 57 concurrent tES-fMRI studies. Contributors were then invited to suggest revisions or additions to the initial checklist. After the revision phase, contributors rated the importance of the 17 essential items and 42 additional recommendations in the final checklist. The state of methodological transparency within the 57 reviewed concurrent tES-fMRI studies was then assessed by using the checklist. Experts refined the checklist through the revision and rating phases, leading to a checklist with three categories of essential items and additional recommendations: (i) technological factors, (ii) safety and noise tests and (iii) methodological factors. The level of reporting of checklist items varied among the 57 concurrent tES-fMRI papers, ranging from 24% to 76%. On average, 53% of checklist items were reported in a given article. In conclusion, use of the ContES checklist is expected to enhance the methodological reporting quality of future concurrent tES-fMRI studies and increase methodological transparency and reproducibility.

Reliability of web-based affective auditory stimulus presentation.

Web-based experimental testing has seen exponential growth in psychology and cognitive neuroscience. However, paradigms involving affective auditory stimuli have yet to adapt to the online approach due to concerns about the lack of experimental control and other technical challenges. In this study, we assessed whether sounds commonly used to evoke affective responses in-lab can be used online. Using recent developments to increase sound presentation quality, we selected 15 commonly used sound stimuli and assessed their impact on valence and arousal states in a web-based experiment. Our results reveal good inter-rater and test-retest reliabilities, with results comparable to in-lab studies. Additionally, we compared a variety of previously used unpleasant stimuli, allowing us to identify the most aversive among these sounds. Our findings demonstrate that affective sounds can be reliably delivered through web-based platforms, which help facilitate the development of new auditory paradigms for affective online experiments.

Children are full of optimism, but those rose-tinted glasses are fading-Reduced learning from negative outcomes drives hyperoptimism in children.

Believing that good things will happen in life is essential to maintain motivation and achieve highly ambitious goals. This optimism bias, the overestimation of positive outcomes, may be particularly important during childhood when motivation must be maintained in the face of negative outcomes. In a learning task, we have thus studied the mechanisms underlying the development of optimism bias. Investigating children (8 to 9 year-olds), early (12 to 13 year-olds), and late adolescents (16 to 17 year-olds), we find a consistent optimism bias across age groups. However, children were particularly hyperoptimistic, with the optimism bias decreasing with age. Using computational modeling, we show that this was driven by a reduced learning from worse-than-expected outcomes, and this reduced learning explains why children are hyperoptimistic. Our findings thus show that insensitivity to bad outcomes in childhood helps to prevent taking on an overly realistic perspective and maintain motivation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Assigning the right credit to the wrong action: compulsivity in the general population is associated with augmented outcome-irrelevant value-based learning.

Compulsive behavior is enacted under a belief that a specific act controls the likelihood of an undesired future event. Compulsive behaviors are widespread in the general population despite having no causal relationship with events they aspire to influence. In the current study, we tested whether there is an increased tendency to assign value to aspects of a task that do not predict an outcome (i.e., outcome-irrelevant learning) among individuals with compulsive tendencies. We studied 514 healthy individuals who completed self-report compulsivity, anxiety, depression, and schizotypal measurements, and a well-established reinforcement-learning task (i.e., the two-step task). As expected, we found a positive relationship between compulsivity and outcome-irrelevant learning. Specifically, individuals who reported having stronger compulsive tendencies (e.g., washing, checking, grooming) also tended to assign value to response keys and stimuli locations that did not predict an outcome. Controlling for overall goal-directed abilities and the co-occurrence of anxious, depressive, or schizotypal tendencies did not impact these associations. These findings indicate that outcome-irrelevant learning processes may contribute to the expression of compulsivity in a general population setting. We highlight the need for future research on the formation of non-veridical action-outcome associations as a factor related to the occurrence and maintenance of compulsive behavior.

Obsessive-compulsive symptoms and information seeking during the Covid-19 pandemic.

Increased mental-health symptoms as a reaction to stressful life events, such as the Covid-19 pandemic, are common. Critically, successful adaptation helps to reduce such symptoms to baseline, preventing long-term psychiatric disorders. It is thus important to understand whether and which psychiatric symptoms show transient elevations, and which persist long-term and become chronically heightened. At particular risk for the latter trajectory are symptom dimensions directly affected by the pandemic, such as obsessive-compulsive (OC) symptoms. In this longitudinal large-scale study (N = 406), we assessed how OC, anxiety and depression symptoms changed throughout the first pandemic wave in a sample of the general UK public. We further examined how these symptoms affected pandemic-related information seeking and adherence to governmental guidelines. We show that scores in all psychiatric domains were initially elevated, but showed distinct longitudinal change patterns. Depression scores decreased, and anxiety plateaued during the first pandemic wave, while OC symptoms further increased, even after the ease of Covid-19 restrictions. These OC symptoms were directly linked to Covid-related information seeking, which gave rise to higher adherence to government guidelines. This increase of OC symptoms in this non-clinical sample shows that the domain is disproportionately affected by the pandemic. We discuss the long-term impact of the Covid-19 pandemic on public mental health, which calls for continued close observation of symptom development.

I know better! Emerging metacognition allows adolescents to ignore false advice.

Adolescents aspire for independence. Successful independence means knowing when to rely on one's own knowledge and when to listen to others. A critical prerequisite thus is a well-developed metacognitive ability to accurately assess the quality of one's own knowledge. Little is known about whether the strive to become an independent decision maker in adolescence is underpinned by the necessary metacognitive skills. Here, we demonstrate that metacognition matures from childhood to adolescence (N = 107) and that this process coincides with greater independent decision-making. We show that adolescents, in contrast to children, take on others' advice less often, but only when the advice is misleading. Finally, we demonstrate that adolescents' reduced reliance on others' advice is explained by their increased metacognitive skills, suggesting that a developing ability to introspect may support independent decision-making in adolescence.

Human complex exploration strategies are enriched by noradrenaline-modulated heuristics.

An exploration-exploitation trade-off, the arbitration between sampling a lesser-known against a known rich option, is thought to be solved using computationally demanding exploration algorithms. Given known limitations in human cognitive resources, we hypothesised the presence of additional cheaper strategies. We examined for such heuristics in choice behaviour where we show this involves a value-free random exploration, that ignores all prior knowledge, and a novelty exploration that targets novel options alone. In a double-blind, placebo-controlled drug study, assessing contributions of dopamine (400 mg amisulpride) and noradrenaline (40 mg propranolol), we show that value-free random exploration is attenuated under the influence of propranolol, but not under amisulpride. Our findings demonstrate that humans deploy distinct computationally cheap exploration strategies and that value-free random exploration is under noradrenergic control.