Cortical Grey Matter Mediates Increases in Model-Based Control and Learning from Positive Feedback from Adolescence to Adulthood.

Cognition and brain structure undergo significant maturation from adolescence into adulthood. Model-based (MB) control is known to increase across development, which is mediated by cognitive abilities. Here, we asked two questions unaddressed in previous developmental studies. First, what are the brain structural correlates of age-related increases in MB control? Second, how are age-related increases in MB control from adolescence to adulthood influenced by motivational context? A human developmental sample (n = 103; age, 12-50, male/female, 55:48) completed structural MRI and an established task to capture MB control. The task was modified with respect to outcome valence by including (1) reward and punishment blocks to manipulate the motivational context and (2) an additional choice test to assess learning from positive versus negative feedback. After replicating that an age-dependent increase in MB control is mediated by cognitive abilities, we demonstrate first-time evidence that gray matter density (GMD) in the parietal cortex mediates the increase of MB control with age. Although motivational context did not relate to age-related changes in MB control, learning from positive feedback improved with age. Meanwhile, negative feedback learning showed no age effects. We present a first report that an age-related increase in positive feedback learning was mediated by reduced GMD in the parietal, medial, and dorsolateral prefrontal cortex. Our findings indicate that brain maturation, putatively reflected in lower GMD, in distinct and partially overlapping brain regions could lead to a more efficient brain organization and might thus be a key developmental step toward age-related increases in planning and value-based choice.SIGNIFICANCE STATEMENT Changes in model-based decision-making are paralleled by extensive maturation in cognition and brain structure across development. Still, to date the neuroanatomical underpinnings of these changes remain unclear. Here, we demonstrate for the first time that parietal GMD mediates age-dependent increases in model-based control. Age-related increases in positive feedback learning were mediated by reduced GMD in the parietal, medial, and dorsolateral prefrontal cortex. A manipulation of motivational context did not have an impact on age-related changes in model-based control. These findings highlight that brain maturation in distinct and overlapping cortical regions constitutes a key developmental step toward improved value-based choices.

Proteomic mapping identifies serum marker signatures associated with MIS-C specific hyperinflammation and cardiovascular manifestation.

Multisystem inflammatory syndrome in children (MIS-C) shares several clinical and immunological features with Kawasaki Disease (KD) and pediatric hyperinflammation, but the immuno-phenotypic overlap among these clinical mimics is still incompletely understood. Here we analyzed serum samples from treatment-naïve patients with MIS-C (n = 31) and KD (n = 11), pediatric hyperinflammation (n = 13) and healthy controls (HC, n = 10) by proximity extension assay (PEA) to profile 184 blood biomarkers. Collectively, immunophenotypic overlap between MIS-C and hyperinflammation exceeds overlap with KD. Overexpression of IL-17A in MIS-C and KD could best separate these conditions from hyperinflammatory conditions, while those were hallmarked by overabundance of adenosin deaminase and IL-18. Depletion in serum TNF-related subfamily member 9 (TNFRSF9) and apoptosis inducing ligand (TRAIL) linked with cardiovascular manifestations and myocarditis in MIS-C. Altogether, our analysis highlights important differences in molecular marker signatures also across different MIS-C and KD cohorts and suggests several previously unidentified molecular associations in context of cardiovascular inflammation.

Fear conditioning and fear generalization in children and adolescents with anxiety disorders.

Overgeneralization of conditioned fear is associated with anxiety disorders (AD). Most results stem from studies done in adult patients, but studies with children are rare, although the median onset of anxiety disorders lies already in childhood. Thus, the goal of the present study was to examine fear learning and generalization in youth participants, aged 10-17 years, with AD (n = 39) compared to healthy controls (HC) (n = 40). A discriminative fear conditioning and generalization paradigm was used. Ratings of arousal, valence, and US expectancy (the probability of an aversive noise following each stimulus) were measured, hypothesizing that children with AD compared to HC would show heightened ratings of arousal and US expectancy, and decreased positive valence ratings, respectively, as well as overgeneralization of fear. The results indicated that children with AD rated all stimuli as more arousing and less pleasant, and demonstrated higher US expectancy ratings to all stimuli when compared to HC. Thus, rather than displaying qualitatively different generalization patterns (e.g., a linear vs. quadratic slope of the gradient), differences between groups were more quantitative (similar, but parallel shifted gradient). Therefore, overgeneralization of conditioned fear does not seem to be a general marker of anxiety disorders in children and adolescents.

Predicting change: Approximate inference under explicit representation of temporal structure in changing environments.

In our daily lives timing of our actions plays an essential role when we navigate the complex everyday environment. It is an open question though how the representations of the temporal structure of the world influence our behavior. Here we propose a probabilistic model with an explicit representation of state durations which may provide novel insights in how the brain predicts upcoming changes. We illustrate several properties of the behavioral model using a standard reversal learning design and compare its task performance to standard reinforcement learning models. Furthermore, using experimental data, we demonstrate how the model can be applied to identify participants' beliefs about the latent temporal task structure. We found that roughly one quarter of participants seem to have learned the latent temporal structure and used it to anticipate changes, whereas the remaining participants' behavior did not show signs of anticipatory responses, suggesting a lack of precise temporal expectations. We expect that the introduced behavioral model will allow, in future studies, for a systematic investigation of how participants learn the underlying temporal structure of task environments and how these representations shape behavior.

Opportunities for emotion and mental health research in the resource-rationality framework.

We discuss opportunities in applying the resource-rationality framework toward answering questions in emotion and mental health research. These opportunities rely on characterization of individual differences in cognitive strategies; an endeavor that may be at odds with the normative approach outlined in the target article. We consider ways individual differences might enter the framework and the translational opportunities offered by each.

Acute psychosocial stress alters thalamic network centrality.

Acute stress triggers a broad psychophysiological response that is adaptive if rapidly activated and terminated. While the brain controls the stress response, it is strongly affected by it. Previous research of stress effects on brain activation and connectivity has mainly focused on pre-defined brain regions or networks, potentially missing changes in the rest of the brain. We here investigated how both stress reactivity and stress recovery are reflected in whole-brain network topology and how changes in functional connectivity relate to other stress measures. Healthy young males (n = 67) completed the Trier Social Stress Test or a control task. From 60 min before until 105 min after stress onset, blocks of resting-state fMRI were acquired. Subjective, autonomic, and endocrine measures of the stress response were assessed throughout the experiment. Whole-brain network topology was quantified using Eigenvector centrality (EC) mapping, which detects central hubs of a network. Stress influenced subjective affect, autonomic activity, and endocrine measures. EC differences between groups as well as before and after stress exposure were found in the thalamus, due to widespread connectivity changes in the brain. Stress-driven EC increases in the thalamus were significantly correlated with subjective stress ratings and showed non-significant trends for a correlation with heart rate variability and saliva cortisol. Furthermore, increases in thalamic EC and in saliva cortisol persisted until 105 min after stress onset. We conclude that thalamic areas are central for information processing after stress exposure and may provide an interface for the stress response in the rest of the body and in the mind.

Behavioral and Neural Signatures of Reduced Updating of Alternative Options in Alcohol-Dependent Patients during Flexible Decision-Making.

Addicted individuals continue substance use despite the knowledge of harmful consequences and often report having no choice but to consume. Computational psychiatry accounts have linked this clinical observation to difficulties in making flexible and goal-directed decisions in dynamic environments via consideration of potential alternative choices. To probe this in alcohol-dependent patients (n = 43) versus healthy volunteers (n = 35), human participants performed an anticorrelated decision-making task during functional neuroimaging. Via computational modeling, we investigated behavioral and neural signatures of inference regarding the alternative option. While healthy control subjects exploited the anticorrelated structure of the task to guide decision-making, alcohol-dependent patients were relatively better explained by a model-free strategy due to reduced inference on the alternative option after punishment. Whereas model-free prediction error signals were preserved, alcohol-dependent patients exhibited blunted medial prefrontal signatures of inference on the alternative option. This reduction was associated with patients' behavioral deficit in updating the alternative choice option and their obsessive-compulsive drinking habits. All results remained significant when adjusting for potential confounders (e.g., neuropsychological measures and gray matter density). A disturbed integration of alternative choice options implemented by the medial prefrontal cortex appears to be one important explanation for the puzzling question of why addicted individuals continue drug consumption despite negative consequences. SIGNIFICANCE STATEMENT: In addiction, patients maintain substance use despite devastating consequences and often report having no choice but to consume. These clinical observations have been theoretically linked to disturbed mechanisms of inference, for example, to difficulties when learning statistical regularities of the environmental structure to guide decisions. Using computational modeling, we demonstrate disturbed inference on alternative choice options in alcohol addiction. Patients neglecting "what might have happened" was accompanied by blunted coding of inference regarding alternative choice options in the medial prefrontal cortex. An impaired integration of alternative choice options implemented by the medial prefrontal cortex might contribute to ongoing drug consumption in the face of evident negative consequences.

The Feedback-related Negativity Codes Components of Abstract Inference during Reward-based Decision-making.

Behavioral control is influenced not only by learning from the choices made and the rewards obtained but also by "what might have happened," that is, inference about unchosen options and their fictive outcomes. Substantial progress has been made in understanding the neural signatures of direct learning from choices that are actually made and their associated rewards via reward prediction errors (RPEs). However, electrophysiological correlates of abstract inference in decision-making are less clear. One seminal theory suggests that the so-called feedback-related negativity (FRN), an ERP peaking 200-300 msec after a feedback stimulus at frontocentral sites of the scalp, codes RPEs. Hitherto, the FRN has been predominantly related to a so-called "model-free" RPE: The difference between the observed outcome and what had been expected. Here, by means of computational modeling of choice behavior, we show that individuals employ abstract, "double-update" inference on the task structure by concurrently tracking values of chosen stimuli (associated with observed outcomes) and unchosen stimuli (linked to fictive outcomes). In a parametric analysis, model-free RPEs as well as their modification because of abstract inference were regressed against single-trial FRN amplitudes. We demonstrate that components related to abstract inference uniquely explain variance in the FRN beyond model-free RPEs. These findings advance our understanding of the FRN and its role in behavioral adaptation. This might further the investigation of disturbed abstract inference, as proposed, for example, for psychiatric disorders, and its underlying neural correlates.

A cognitive-computational account of mood swings in adolescence.

Teenagers have a reputation for being fickle, in both their choices and their moods. This variability may help adolescents as they begin to independently navigate novel environments. Recently, however, adolescent moodiness has also been linked to psychopathology. Here, we consider adolescents' mood swings from a novel computational perspective, grounded in reinforcement learning (RL). This model proposes that mood is determined by surprises about outcomes in the environment, and how much we learn from these surprises. It additionally suggests that mood biases learning and choice in a bidirectional manner. Integrating independent lines of research, we sketch a cognitive-computational account of how adolescents' mood, learning, and choice dynamics influence each other, with implications for normative and psychopathological development.

Neurocomputational mechanisms underlying differential reinforcement learning from wins and losses in obesity with and without binge eating.

BACKGROUND: Binge Eating Disorder (BED) is thought of as a disorder of cognitive control but evidence regarding its neurocognitive mechanisms is inconclusive. Key limitations in prior research are a lack of consistent separation between effects of BED and obesity, and a disregard for self-report evidence suggesting that neurocognitive alterations may emerge primarily in loss- or harm-avoidance contexts. METHODS: Addressing these gaps, this longitudinal study investigated behavioral flexibility and its underlying neuro-computational processes in reward-seeking and loss-avoidance contexts. Obese participants with BED (BED), without BED (OB), and healthy normal-weight participants (NW) (Ntotal=96) performed a probabilistic reversal learning task during functional imaging, with different blocks focused on obtaining wins or avoiding losses. They were reinvited for a 6-months follow-up. RESULTS: Analyses informed by computational models of reinforcement learning showed that unlike BED, OB performed worse in the win than the loss condition. Computationally, this was explained by differential learning sensitivities in the win vs loss conditions between groups. In the brain, this was echoed in differential neural learning signals in the ventromedial prefrontal cortex (vmPFC) per condition. The differences were subtle, but scaled with BED symptoms, such that more severe BED symptoms were associated with increasing bias towards improved learning from wins vs losses. Across conditions, OB switched more between choice options than NW. This was reflected in diminished representation of choice certainty in the vmPFC. CONCLUSIONS: Our study highlights the importance of distinguishing between obesity with and without BED to identify unique neuro-computational alterations underlying different styles of maladaptive eating behavior.

Diminished reinforcement sensitivity in adolescence is associated with enhanced response switching and reduced coding of choice probability in the medial frontal pole.

Precisely charting the maturation of core neurocognitive functions such as reinforcement learning (RL) and flexible adaptation to changing action-outcome contingencies is key for developmental neuroscience and adjacent fields like developmental psychiatry. However, research in this area is both sparse and conflicted, especially regarding potentially asymmetric development of learning for different motives (obtain wins vs avoid losses) and learning from valenced feedback (positive vs negative). In the current study, we investigated the development of RL from adolescence to adulthood, using a probabilistic reversal learning task modified to experimentally separate motivational context and feedback valence, in a sample of 95 healthy participants between 12 and 45. We show that adolescence is characterized by enhanced novelty seeking and response shifting especially after negative feedback, which leads to poorer returns when reward contingencies are stable. Computationally, this is accounted for by reduced impact of positive feedback on behavior. We also show, using fMRI, that activity of the medial frontopolar cortex reflecting choice probability is attenuated in adolescence. We argue that this can be interpreted as reflecting diminished confidence in upcoming choices. Interestingly, we find no age-related differences between learning in win and loss contexts.

Universal prevention for non-suicidal self-injury in adolescents is scarce - A systematic review.

Non-suicidal self-injury (NSSI) during adolescence is a high-risk marker for the development and persistence of mental health problems and has been recognized as a significant public health problem. Whereas targeted prevention has indeed shown to be effective in reducing NSSI and improve mental health problems, access to such programs is limited. By face validity, universal prevention of NSSI seems an ideal starting point for a stepped-care model to circumvent a lack of resources in the medical care system. However, it is yet unclear how effective such approaches are. Here, we provide a summary of existing work on universal prevention of NSSI in adolescents younger than 21 years based on a systematic literature search. We found that only seven studies are available. None of the programs evaluated was found to be effective in reducing the incidence or frequency of NSSI. After providing a comprehensive summary of the existing work, we evaluate the fact that existing work primarily focusses on selected/targeted prevention and on psychoeducational methods. We derive implications for future directions in the field of universal prevention of NSSI.

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.

Revealing human sensitivity to a latent temporal structure of changes.

Precisely timed behavior and accurate time perception plays a critical role in our everyday lives, as our wellbeing and even survival can depend on well-timed decisions. Although the temporal structure of the world around us is essential for human decision making, we know surprisingly little about how representation of temporal structure of our everyday environment impacts decision making. How does the representation of temporal structure affect our ability to generate well-timed decisions? Here we address this question by using a well-established dynamic probabilistic learning task. Using computational modeling, we found that human subjects' beliefs about temporal structure are reflected in their choices to either exploit their current knowledge or to explore novel options. The model-based analysis illustrates a large within-group and within-subject heterogeneity. To explain these results, we propose a normative model for how temporal structure is used in decision making, based on the semi-Markov formalism in the active inference framework. We discuss potential key applications of the presented approach to the fields of cognitive phenotyping and computational psychiatry.

Investigating adult age differences in real-life empathy, prosociality, and well-being using experience sampling.

While the importance of social affect and cognition is indisputable throughout the adult lifespan, findings of how empathy and prosociality develop and interact across adulthood are mixed and real-life data are scarce. Research using ecological momentary assessment recently demonstrated that adults commonly experience empathy in daily life. Furthermore, experiencing empathy was linked to higher prosocial behavior and subjective well-being. However, to date, it is not clear whether there are adult age differences in daily empathy and daily prosociality and whether age moderates the relationship between empathy and prosociality across adulthood. Here we analyzed experience-sampling data collected from participants across the adult lifespan to study age effects on empathy, prosocial behavior, and well-being under real-life circumstances. Linear and quadratic age effects were found for the experience of empathy, with increased empathy across the three younger age groups (18 to 45 years) and a slight decrease in the oldest group (55 years and older). Neither prosocial behavior nor well-being showed significant age-related differences. We discuss these findings with respect to (partially discrepant) results derived from lab-based and traditional survey studies. We conclude that studies linking in-lab experiments with real-life experience-sampling may be a promising venue for future lifespan studies.

Anger regulation choice-The role of age and habitual reappraisal.

The ability to choose emotion regulation strategies in accordance to contextual demands, known as emotion regulation flexibility, is key to healthy adaptation. While recent investigations on spontaneous emotion regulation choice tested the effects of emotional intensity and age using standardized negative pictures with no particular emotional quality, we elicited the discrete emotion of anger with personally relevant autobiographical memories in a sample of 52 younger and 41 older adults. In addition, we included habitual reappraisal as a predictor of emotion regulation choice. Our main hypothesis was that, compared with younger adults, older adults prefer less resource-demanding emotion regulation strategies (i.e., distraction) over more resource-demanding strategies (i.e., reappraisal), particularly if older adults' habitual reappraisal is low and the to-be-regulated anger is of high intensity. Surprisingly, our findings suggest that only older adults' emotion regulation choices depend on the emotional intensity of the autobiographical memory and habitual reappraisal. Only older adults with high habitual reappraisal preferred to reappraise their anger in situations of low anger intensity but switched to the less demanding strategy of distraction in high anger memories, indicating emotion regulation flexibility. This study extends previous research by testing emotion regulation choices in natural contexts and considering regulation habits. Although we replicate previous findings of emotion regulation flexibility according to emotional intensity in anger memories for older adults with high habitual reappraisal only, our findings illustrate the relevance of reappraisal habits to emotion regulation choice in age-comparative research. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The ageing of the social mind: replicating the preservation of socio-affective and the decline of socio-cognitive processes in old age.

Anticipating population ageing to reach a historically unprecedented level in this century and considering the public goal of promoting well-being until old age, research in many fields has started to focus on processes and factors that contribute to healthy ageing. Since human interactions have a tremendous impact on our mental and physical well-being, scientists are increasingly investigating the basic processes that enable successful social interactions such as social affect (empathy, compassion) and social cognition (Theory of Mind). However, regarding the replication crisis in psychological science it is crucial to probe the reproducibility of findings revealed by each specific method. To this end, we aimed to replicate the effect of age on empathy, compassion and Theory of Mind observed in Reiter and colleagues' study (Reiter et al. 2017 Sci. Rep. 7, 11046 (doi:10.1038/s41598-017-10669-4)) by using the same ecologically valid paradigm in an independent sample with similar age ranges. We were able to replicate the previously observed results of a preservation or even enhancement in socio-affective processes, but a decline in socio-cognitive processes for older adults. Our findings add to the understanding of how social affect and cognition change across the adult lifespan and may suggest targets for intervention studies aiming to foster successful social interactions and well-being until advanced old age.

Human aging alters social inference about others' changing intentions.

Decoding others' intentions accurately in order to adapt one's own behavior is pivotal throughout life. In this study, we asked how younger and older adults deal with uncertainty in dynamic social environments. We used an advice-taking paradigm together with Bayesian modeling to characterize effects of aging on learning about others' time-varying intentions. We observed age differences when comparing learning on two levels of social uncertainty: the fidelity of the adviser and the volatility of intentions. Older adults expected the adviser to change his/her intentions more frequently (i.e., a higher volatility of the adviser). They also showed higher confidence (i.e., precision) in their volatility beliefs and were less willing to change their beliefs about volatility over the course of the experiment. This led them to update their predictions about the fidelity of the adviser more quickly. Potentially indicative of stereotype effects, we observed that older advisers were perceived as more volatile, but also more faithful than younger advisers. This offers new insights into adult age differences in response to social uncertainty.

Seizing the opportunity: Lifespan differences in the effects of the opportunity cost of time on cognitive control.

Previous work suggests that lifespan developmental differences in cognitive control reflect maturational and aging-related changes in prefrontal cortex functioning. However, complementary explanations exist: It could be that children and older adults differ from younger adults in how they balance the effort of engaging in control against its potential benefits. Here we test whether the degree of cognitive effort expenditure depends on the opportunity cost of time (average reward rate per unit time): if the average reward rate is high, participants should withhold cognitive effort whereas if it is low, they should invest more. In Experiment 1, we examine this hypothesis in children, adolescents, younger, and older adults, by applying a reward rate manipulation in two cognitive control tasks: a modified Erikson Flanker and a task-switching paradigm. We found that young adults and adolescents reflexively withheld effort when the opportunity cost of time was high, whereas older adults and, to a lesser degree children, invested more resources to accumulate reward as quickly as possible. We tentatively interpret these results in terms of age- and task-specific differences in the processing of the opportunity cost of time. We qualify our findings in a second experiment in younger adults in which we address an alternative explanation of our results and show that the observed age differences in effort expenditure may not result from differences in task difficulty. To conclude, we think that our results present an interesting first step at relating opportunity costs to motivational processes across the lifespan. We frame the implications of further work in this area within a recent developmental model of resource-rationality, which points to developmental sweet spots in cognitive control.