The regulation of emotion is vital for adaptive behavior in a social environment. Different strategies may be adopted to achieve successful emotion regulation, ranging from attentional control (e.g., distraction) to cognitive change (e.g., reappraisal). However, there is only scarce evidence comparing the different regulation strategies with respect to their neural mechanisms and their effects on emotional experience. We, therefore, directly compared reappraisal and distraction in a functional magnetic resonance imaging study with emotional pictures. In the distraction condition participants performed an arithmetic task, while they reinterpreted the emotional situation during reappraisal to downregulate emotional intensity. Both strategies were successful in reducing subjective emotional state ratings and lowered activity in the bilateral amygdala. Direct contrasts, however, showed a stronger decrease in amygdala activity for distraction when compared with reappraisal. While both strategies relied on common control areas in the medial and dorsolateral prefrontal and inferior parietal cortex, the orbitofrontal cortex was selectively activated for reappraisal. In contrast, the dorsal anterior cingulate and large clusters in the parietal cortex were active in the distraction condition. Functional connectivity patterns of the amygdala activation confirmed the roles of these specific activations for the 2 emotion regulation strategies.

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In parallel with the rise in interest and volume of social cognition research, there has been increasing awareness of a lack of agreement on the concepts and taxonomy used to study social processes. Two central concepts in the field, Empathy and Theory of Mind (ToM), have been applied as overlapping umbrella terms for a variety of different processes of limited convergence. Here, we review and integrate evidence of brain activation, brain organization, and behavior into a coherent model of social cognitive processes. We start with a meta-analytic clustering of neuroimaging data across different social cognitive tasks. Results show that understanding others' mental states can be described by a multilevel model of hierarchical structure, similar to models in intelligence and personality research. A higher level describes more broad and abstract classes of functioning, whereas a lower level explicates how functions are applied to concrete contexts, given by specific stimulus and task formats. Specifically, the higher level of our model suggests three groups of neurocognitive processes: (i) Predominantly cognitive processes that are engaged when mentalizing requires selfgenerated cognition decoupled from the physical world. (ii) More affective processes which are engaged when we witness emotions in others, based on shared emotional, motor, and somatosensory representations. (iii) Combined processes which engage cognitive and affective functions in parallel. We discuss how these processes are explained by an underlying principal gradient of structural brain organization. Finally, we validate the model by a review of Empathy and ToM task interrelations found in behavioral studies.

Altruistic behavior varies considerably across people and decision contexts. The relevant computational and motivational mechanisms that underlie its heterogeneity, however, are poorly understood. Using a charitable giving task together with multivariate decoding techniques, we identified three distinct psychological mechanisms underlying altruistic decision-making (empathy, perspective taking, and attentional reorienting) and linked them to dissociable neural computations. Neural responses in the anterior insula (AI) (but not temporoparietal junction [TPJ]) encoded trial-wise empathy for beneficiaries, whereas the TPJ (but not AI) predicted the degree of perspective taking. Importantly, the relative influence of both socio-cognitive processes differed across individuals: participants whose donation behavior was heavily influenced by affective empathy exhibited higher predictive accuracies for generosity in AI, whereas those who strongly relied on cognitive perspective taking showed improved predictions of generous donations in TPJ. Furthermore, subjectspecific contributions of both processes for donations were reflected in participants' empathy and perspective taking responses in a separate fMRI task (EmpaToM), suggesting that process-specific inputs into altruistic choices may reflect participants' general propensity to either empathize or mentalize. Finally, using independent attention task data, we identified shared neural codes for attentional reorienting and generous donations in the posterior superior temporal sulcus, suggesting that domain-general attention shifts also contribute to generous behavior (but not in TPJ or AI). Overall, our findings demonstrate highly specific roles of AI for affective empathy and TPJ for cognitive perspective taking as precursors of prosocial behavior and suggest that these discrete routes of social cognition differentially drive intraindividual and interindividual differences in altruistic behavior.

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Concerns have been growing about the veracity of psychological research. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions, or attempt to replicate prior research, in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time-limited), efficient (in terms of re-using structures and principles for different projects), decentralized, diverse (in terms of participants and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside of the network). The PSA and other approaches to crowdsourced psychological science will advance our understanding of mental processes and behaviors by enabling rigorous research and systematically examining its generalizability.

Training to understand the feelings and thoughts of others induces structural changes in two divergent social brain networks.