Strategic social decision making undergoes significant changes in typically developing and autistic early adolescents.

Information sampling about others' trustworthiness prior to cooperation allows humans to minimize the risk of exploitation. Here, we examined whether early adolescence or preadolescence, a stage defined as in between childhood and adolescence, is a significant developmental period for strategic social decisions. We also sought to characterize differences between autistic children and their typically developing (TD) peers. TD (N = 48) and autistic (N = 56) 8- to 12-year-olds played an online information sampling trust game. While both groups adapted their information sampling and cooperation to the various trustworthiness levels of the trustees, groups differed in how age and social skills modulated task behavior. In the TD group social skills were a stronger overall predictor of task behavior. In the autistic group, age was a stronger predictor and interacted with social skills. Computational modeling revealed that both groups used the same heuristic information sampling strategy-albeit older TD children were more efficient as reflected by decreasing decision noise with age. Autistic children had lower prior beliefs about the trustee's trustworthiness compared to TD children. These lower priors indicate that children believed the trustees to be less trustworthy. Lower priors scaled with lower social skills across groups. Notably, groups did not differ in prior uncertainty, meaning that the priors of TD and autistic children were equally strong. Taken together, we found significant development in information sampling and cooperation in early adolescence and nuanced differences between TD and autistic children. Our study highlights the importance of deep phenotyping of children including clinical measures, behavioral experiments and computational modeling. RESEARCH HIGHLIGHTS: We specified how early adolescents with and without an autism diagnosis sampled information about their interaction partners and made cooperation decisions in a strategic game. Early adolescence is a significant developmental period for strategic decision making, marked by significant changes in information sampling efficiency and adaptivity to the partner's behavior. Autistic and non-autistic groups differed in how age and social skills modulated task behavior; in non-autistic children behavior was more indicative of overall social skills. Computational modeling revealed differences between autistic and non-autistic groups in their initial beliefs about cooperation partners; autistic children expected their partners to be less trustworthy.

A neuro-computational social learning framework to facilitate transdiagnostic classification and treatment across psychiatric disorders.

Social deficits are among the core and most striking psychiatric symptoms, present in most psychiatric disorders. Here, we introduce a novel social learning framework, which consists of neuro-computational models that combine reinforcement learning with various types of social knowledge structures. We outline how this social learning framework can help specify and quantify social psychopathology across disorders and provide an overview of the brain regions that may be involved in this type of social learning. We highlight how this framework can specify commonalities and differences in the social psychopathology of individuals with autism spectrum disorder (ASD), personality disorders (PD), and major depressive disorder (MDD) and improve treatments on an individual basis. We conjecture that individuals with psychiatric disorders rely on rigid social knowledge representations when learning about others, albeit the nature of their rigidity and the behavioral consequences can greatly differ. While non-clinical cohorts tend to efficiently adapt social knowledge representations to relevant environmental constraints, psychiatric cohorts may rigidly stick to their preconceived notions or overly coarse knowledge representations during learning.

Incorporating social knowledge structures into computational models.

To navigate social interactions successfully, humans need to continuously learn about the personality traits of other people (e.g., how helpful or aggressive is the other person?). However, formal models that capture the complexities of social learning processes are currently lacking. In this study, we specify and test potential strategies that humans can employ for learning about others. Standard Rescorla-Wagner (RW) learning models only capture parts of the learning process because they neglect inherent knowledge structures and omit previously acquired knowledge. We therefore formalize two social knowledge structures and implement them in hybrid RW models to test their usefulness across multiple social learning tasks. We name these concepts granularity (knowledge structures about personality traits that can be utilized at different levels of detail during learning) and reference points (previous knowledge formalized into representations of average people within a social group). In five behavioural experiments, results from model comparisons and statistical analyses indicate that participants efficiently combine the concepts of granularity and reference points-with the specific combinations in models depending on the people and traits that participants learned about. Overall, our experiments demonstrate that variants of RW algorithms, which incorporate social knowledge structures, describe crucial aspects of the dynamics at play when people interact with each other.

Risk perception and optimism during the early stages of the COVID-19 pandemic.

Slowing the spread of COVID-19 requires people to actively change their lives by following protective practices, such as physical distancing and disinfecting their hands. Perceptions about the personal risk of COVID-19 may affect compliance with these practices. In this study, we assessed risk perception and optimism about COVID-19 in a multinational (UK, USA and Germany), longitudinal design during the early stages of the pandemic (16 March 2020; 1 April 2020; 20 May 2020). Our main findings are that (i) people showed a comparative optimism bias about getting infected and infecting others, but not for getting severe symptoms, (ii) this optimism bias did not change over time, (iii) optimism bias seemed to relate to perceived level of control over the action, (iv) risk perception was linked to publicly available information about the disorder, (v) people reported adhering closely to protective measures but these measures did not seem to be related to risk perception, and (vi) risk perception was related to questions about stress and anxiety. In additional cross-sectional samples, we replicated our most important findings. Our open and partly preregistered results provide detailed descriptions of risk perceptions and optimistic beliefs during the early stages of the COVID-19 pandemic in three Western countries.

Neurocognitive Mechanisms of Social Inferences in Typical and Autistic Adolescents.

BACKGROUND: Many of our efforts in social interactions are dedicated to learning about others. Adolescents with autism have core deficits in social learning, but a mechanistic understanding of these deficits and how they relate to neural development is lacking. The present study aimed to specify how adolescents with and without autism represent and acquire social knowledge and how these processes are implemented in neural activity. METHODS: Typically developing adolescents (n = 26) and adolescents with autism spectrum disorder (ASD) (n = 20) rated in the magnetic resonance scanner how much 3 peers liked a variety of items and received trial-by-trial feedback about the peers' actual preference ratings. In a separate study, we established the preferences of a new sample of adolescents (N = 99), used to examine population preference structures. Using computational models, we tested whether participants in the magnetic resonance study relied on preference structures during learning and how model predictions were implemented in brain activity. RESULTS: Typically developing adolescents relied on average population preferences and prediction error updating. Importantly, prediction error updating was scaled by the similarity between items. In contrast, preferences of adolescents with ASD were best described by a No-Learning model that relied only on the participant's own preferences for each item. Model predictions were encoded in neural activity. Typically developing adolescents encoded prediction errors in the putamen, and adolescents with ASD showed greater encoding of own preferences in the angular gyrus. CONCLUSIONS: We specified how adolescents represent and update social knowledge during learning. Our findings indicate that adolescents with ASD rely only on their own preferences when making social inferences.

Neurobiological mechanisms of social cognition treatment in high-functioning adults with autism spectrum disorder.

BACKGROUND: The promise of precision medicine for autism spectrum disorder (ASD) hinges on developing neuroscience-informed individualized interventions. Taking an important step in this direction, we investigated neuroplasticity in response to an ecologically-valid, computer-based social-cognitive training (SCOTT). METHODS: In an active control group design, 48 adults with ASD were randomly assigned to a 3-month SCOTT or non-social computer training. Participants completed behavioral tasks, a functional and structural magnetic resonance imaging session before and after the training period. RESULTS: The SCOTT group showed social-cognitive improvements on close and distant generalization tasks. The improvements scaled with reductions in functional activity and increases in cortical thickness in prefrontal regions. CONCLUSION: In sum, we provide evidence for the sensitivity of neuroscientific methods to reflect training-induced social-cognitive improvements in adults with ASD. These results encourage the use of neuroimaging data to describe and quantify treatment-related changes more broadly.

A Computational Account of Optimizing Social Predictions Reveals That Adolescents Are Conservative Learners in Social Contexts.

As adolescents transition to the complex world of adults, optimizing predictions about others' preferences becomes vital for successful social interactions. Mounting evidence suggests that these social learning processes are affected by ongoing brain development across adolescence. A mechanistic understanding of how adolescents optimize social predictions and how these learning strategies are implemented in the brain is lacking. To fill this gap, we combined computational modeling with functional neuroimaging. In a novel social learning task, male and female human adolescents and adults predicted the preferences of peers and could update their predictions based on trial-by-trial feedback about the peers' actual preferences. Participants also rated their own preferences for the task items and similar additional items. To describe how participants optimize their inferences over time, we pitted simple reinforcement learning models against more specific "combination" models, which describe inferences based on a combination of reinforcement learning from past feedback and participants' own preferences. Formal model comparison revealed that, of the tested models, combination models best described how adults and adolescents update predictions of others. Parameter estimates of the best-fitting model differed between age groups, with adolescents showing more conservative updating. This developmental difference was accompanied by a shift in encoding predictions and the errors thereof within the medial prefrontal and fusiform cortices. In the adolescent group, encoding of own preferences and prediction errors scaled with parent-reported social traits, which provides additional external validity for our learning task and the winning computational model. Our findings thus help to specify adolescent-specific social learning processes.SIGNIFICANCE STATEMENT Adolescence is a unique developmental period of heightened awareness about other people. Here we probe the suitability of various computational models to describe how adolescents update their predictions of others' preferences. Within the tested model space, predictions of adults and adolescents are best described by the same learning model, but adolescents show more conservative updating. Compared with adults, brain activity of adolescents is modulated less by predictions themselves and more by prediction errors per se, and this relationship scales with adolescents' social traits. Our findings help specify social learning across adolescence and generate hypotheses about social dysfunctions in psychiatric populations.

Emotional prosody processing in autism spectrum disorder.

Individuals with Autism Spectrum Disorder (ASD) are characterized by severe deficits in social communication, whereby the nature of their impairments in emotional prosody processing have yet to be specified. Here, we investigated emotional prosody processing in individuals with ASD and controls with novel, lifelike behavioral and neuroimaging paradigms. Compared to controls, individuals with ASD showed reduced emotional prosody recognition accuracy on a behavioral task. On the neural level, individuals with ASD displayed reduced activity of the STS, insula and amygdala for complex vs basic emotions compared to controls. Moreover, the coupling between the STS and amygdala for complex vs basic emotions was reduced in the ASD group. Finally, groups differed with respect to the relationship between brain activity and behavioral performance. Brain activity during emotional prosody processing was more strongly related to prosody recognition accuracy in ASD participants. In contrast, the coupling between STS and anterior cingulate cortex (ACC) activity predicted behavioral task performance more strongly in the control group. These results provide evidence for aberrant emotional prosody processing of individuals with ASD. They suggest that the differences in the relationship between the neural and behavioral level of individuals with ASD may account for their observed deficits in social communication.

Performance Feedback Processing Is Positively Biased As Predicted by Attribution Theory.

A considerable literature on attribution theory has shown that healthy individuals exhibit a positivity bias when inferring the causes of evaluative feedback on their performance. They tend to attribute positive feedback internally (e.g., to their own abilities) but negative feedback externally (e.g., to environmental factors). However, all empirical demonstrations of this bias suffer from at least one of the three following drawbacks: First, participants directly judge explicit causes for their performance. Second, participants have to imagine events instead of experiencing them. Third, participants assess their performance only after receiving feedback and thus differences in baseline assessments cannot be excluded. It is therefore unclear whether the classically reported positivity bias generalizes to setups without these drawbacks. Here, we aimed at establishing the relevance of attributions for decision-making by showing an attribution-related positivity bias in a decision-making task. We developed a novel task, which allowed us to test how participants changed their evaluations in response to positive and negative feedback about performance. Specifically, we used videos of actors expressing different facial emotional expressions. Participants were first asked to evaluate the actors' credibility in expressing a particular emotion. After this initial rating, participants performed an emotion recognition task and did--or did not--receive feedback on their veridical performance. Finally, participants re-rated the actors' credibility, which provided a measure of how they changed their evaluations after feedback. Attribution theory predicts that participants change their evaluations of the actors' credibility toward the positive after receiving positive performance feedback and toward the negative after negative performance feedback. Our results were in line with this prediction. A control condition without feedback showed that correct or incorrect performance alone could not explain the observed positivity bias. Furthermore, participants' behavior in our task was linked to the most widely used measure of attribution style. In sum, our findings suggest that positive and negative performance feedback influences the evaluation of task-related stimuli, as predicted by attribution theory. Therefore, our study points to the relevance of attribution theory for feedback processing in decision-making and provides a novel outlook for decision-making biases.

The role of the amygdala in naturalistic mentalising in typical development and in autism spectrum disorder.

BACKGROUND: The substantial discrepancy between mentalising in experimental settings v. real-life social interactions hinders the understanding of the neural basis of real-life social cognition and of social impairments in psychiatric disorders. AIMS: To determine the neural mechanisms underlying naturalistic mentalising in individuals with and without autism spectrum disorder. METHOD: We investigated mentalising with a new video-based functional magnetic resonance imaging task in 20 individuals with autism spectrum disorder and 22 matched healthy controls. RESULTS: Naturalistic mentalising implicated regions of the traditional mentalising network (medial prefrontal cortex, temporoparietal junction), and additionally the insula and amygdala. Moreover, amygdala activity predicted implicit mentalising performance on an independent behavioural task. Compared with controls, the autism spectrum disorder group did not show differences in neural activity within classical mentalising regions. They did, however, show reduced amygdala activity and a reduced correlation between amygdala activity and mentalising accuracy on the behavioural task, compared with controls. CONCLUSIONS: These findings highlight the crucial role of the amygdala in making accurate implicit mental state inferences in typical development and in the social cognitive impairments of individuals with autism spectrum disorder.

An integrative neural model of social perception, action observation, and theory of mind.

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder.

Approximating implicit and explicit mentalizing with two naturalistic video-based tasks in typical development and autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) have been proposed to show greater impairments in implicit than explicit mentalizing. To test this proposition, we developed two comparable naturalistic tasks for a performance-based approximation of implicit and explicit mentalizing in 28 individuals with ASD and 23 matched typically developed (TD) participants. Although both tasks were sensitive to the social impairments of individuals with ASD, implicit mentalizing was not more dysfunctional than explicit mentalizing. In TD participants, performance on the tasks did not correlate with each other, whereas in individuals with ASD they were highly correlated. These findings suggest that implicit and explicit mentalizing processes are separable in typical development. In contrast, in individuals with ASD implicit and explicit mentalizing processes are similarly impaired and closely linked suggesting a lack of developmental specification of these processes in ASD.

Face puzzle-two new video-based tasks for measuring explicit and implicit aspects of facial emotion recognition.

Recognizing others' emotional states is crucial for effective social interaction. While most facial emotion recognition tasks use explicit prompts that trigger consciously controlled processing, emotional faces are almost exclusively processed implicitly in real life. Recent attempts in social cognition suggest a dual process perspective, whereby explicit and implicit processes largely operate independently. However, due to differences in methodology the direct comparison of implicit and explicit social cognition has remained a challenge. Here, we introduce a new tool to comparably measure implicit and explicit processing aspects comprising basic and complex emotions in facial expressions. We developed two video-based tasks with similar answer formats to assess performance in respective facial emotion recognition processes: Face Puzzle, implicit and explicit. To assess the tasks' sensitivity to atypical social cognition and to infer interrelationship patterns between explicit and implicit processes in typical and atypical development, we included healthy adults (NT, n = 24) and adults with autism spectrum disorder (ASD, n = 24). Item analyses yielded good reliability of the new tasks. Group-specific results indicated sensitivity to subtle social impairments in high-functioning ASD. Correlation analyses with established implicit and explicit socio-cognitive measures were further in favor of the tasks' external validity. Between group comparisons provide first hints of differential relations between implicit and explicit aspects of facial emotion recognition processes in healthy compared to ASD participants. In addition, an increased magnitude of between group differences in the implicit task was found for a speed-accuracy composite measure. The new Face Puzzle tool thus provides two new tasks to separately assess explicit and implicit social functioning, for instance, to measure subtle impairments as well as potential improvements due to social cognitive interventions.

Functional neuroanatomy of emotion processing in major depressive disorder is altered after successful antidepressant therapy.

Major Depressive Disorder (MDD) is associated with impaired processing and regulation of emotions. A vast body of research has elucidated the altered neural processes that occur in response to emotional stimuli, while little is known about anticipatory processes. Here we used functional magnetic resonance imaging (fMRI) to investigate neural activation during the presentation and anticipation of negative stimuli. Furthermore, we examined the effects of an 8-week antidepressant treatment with escitalopram. We matched 12 unmedicated MDD patients and 12 healthy control participants to perform a task involving affective pictures. The design of our event-related task consisted of presenting positive, negative, and neutral pictures from the International Affective Picture System (IAPS) across two runs and under opposite conditions. For the 'expected' condition, the pictures were cued by a word indicating their emotional valence; whereas the 'unexpected' condition had a combination of random letters precede the emotion picture. MDD patients displayed greater amygdala activation when anticipating negative pictures and greater prefrontal activation when confronted with them without the anticipatory cues. After antidepressant treatment, both amygdala and prefrontal activation decreased significantly in the treated MDD patients relative to controls. These findings show that the neural mechanisms of emotion anticipation and processing are altered in patients with MDD and that these alterations are able to normalize after treatment with an antidepressant.