Annual review of psychology最新文献

Motivational processes are complex and multifaceted, with both directional and activational aspects. Behavioral activation and exertion of effort are functions that enable organisms to overcome obstacles separating them from significant outcomes. In a complex environment, organisms make cost/benefit decisions, assessing work-related response costs and reinforcer preference. Animal studies have challenged the general idea that dopamine (DA) is best viewed as the reward transmitter and instead have illustrated the involvement of DA in activational and effort-related processes. Mesocorticolimbic DA is a key component of the effort-related motivational circuitry that includes multiple neurotransmitters and brain areas. Human studies have identified brain areas and transmitter systems involved in effort-based decision making and characterized the reduced selection of high-effort activities associated with motivational symptoms of depression and schizophrenia. Animal and human research on the neurochemistry of behavioral activation and effort-related processes makes an important conceptual contribution by illustrating the dissociable nature of distinct aspects of motivation.

Nearly five billion people around the world now use social media, and this number continues to grow. One of the primary goals of social media platforms is to capture and monetize human attention. One means by which individuals and groups can capture attention and drive engagement on these platforms is by sharing morally and emotionally evocative content. We review a growing body of research on the interrelationship of social media and morality as well its consequences for individuals and society. Moral content often goes viral on social media, and social media makes moral behavior (such as punishment) less costly. Thus, social media often acts as an accelerant for existing moral dynamics, amplifying outrage, status seeking, and intergroup conflict while also potentially amplifying more constructive facets of morality, such as social support, prosociality, and collective action. We discuss trends, heated debates, and future directions in this emerging literature.

Determining the psychological, computational, and neural bases of confidence and uncertainty holds promise for understanding foundational aspects of human metacognition. While a neuroscience of confidence has focused on the mechanisms underpinning subpersonal phenomena such as representations of uncertainty in the visual or motor system, metacognition research has been concerned with personal-level beliefs and knowledge about self-performance. I provide a road map for bridging this divide by focusing on a particular class of confidence computation: propositional confidence in one's own (hypothetical) decisions or actions. Propositional confidence is informed by the observer's models of the world and their cognitive system, which may be more or less accurate-thus explaining why metacognitive judgments are inferential and sometimes diverge from task performance. Disparate findings on the neural basis of uncertainty and performance monitoring are integrated into a common framework, and a new understanding of the locus of action of metacognitive interventions is developed.

Moral psychology was shaped around three categories of agents and patients: humans, other animals, and supernatural beings. Rapid progress in artificial intelligence has introduced a fourth category for our moral psychology to deal with: intelligent machines. Machines can perform as moral agents, making decisions that affect the outcomes of human patients or solving moral dilemmas without human supervision. Machines can be perceived as moral patients, whose outcomes can be affected by human decisions, with important consequences for human-machine cooperation. Machines can be moral proxies that human agents and patients send as their delegates to moral interactions or use as a disguise in these interactions. Here we review the experimental literature on machines as moral agents, moral patients, and moral proxies, with a focus on recent findings and the open questions that they suggest.

Music training is generally assumed to improve perceptual and cognitive abilities. Although correlational data highlight positive associations, experimental results are inconclusive, raising questions about causality. Does music training have far-transfer effects, or do preexisting factors determine who takes music lessons? All behavior reflects genetic and environmental influences, but differences in emphasis-nature versus nurture-have been a source of tension throughout the history of psychology. After reviewing the recent literature, we conclude that the evidence that music training causes nonmusical benefits is weak or nonexistent, and that researchers routinely overemphasize contributions from experience while neglecting those from nature. The literature is also largely exploratory rather than theory driven. It fails to explain mechanistically how music-training effects could occur and ignores evidence that far transfer is rare. Instead of focusing on elusive perceptual or cognitive benefits, we argue that it is more fruitful to examine the social-emotional effects of engaging with music, particularly in groups, and that music-based interventions may be effective mainly for clinical or atypical populations.

Achievement goals have been defined as the purpose of competence-relevant behavior. In this respect they connect one of the basic human needs, i.e., competence, to one of society's core values, i.e., achievement. We propose to look at achievement goals through the lens of social influence. We review both the influence that cultural, structural, and contextual factors have on achievement goal endorsement and the influence that endorsing achievement goals allows people to have within their social space. The review allows us to propose a circular model of the influence on and of achievement goals: The culture, social structures, and contexts that are typical of a certain society shape the specific environments in which individuals develop their achievement goals, which in turn has an influence on the expression and circulation of these achievement goals into society, in a social influence cycle.

Disasters cause sweeping damage, hardship, and loss of life. In this article, we first consider the dominant psychological approach to disasters and its narrow focus on psychopathology (e.g., posttraumatic stress disorder). We then review research on a broader approach that has identified heterogeneous, highly replicable trajectories of outcome, the most common being stable mental health or resilience. We review trajectory research for different types of disasters, including the COVID-19 pandemic. Next, we consider correlates of the resilience trajectory and note their paradoxically limited ability to predict future resilient outcomes. Research using machine learning algorithms improved prediction but has not yet illuminated the mechanism behind resilient adaptation. To that end, we propose a more direct psychological explanation for resilience based on research on the motivational and mechanistic components of regulatory flexibility. Finally, we consider how future research might leverage new computational approaches to better capture regulatory flexibility in real time.

Similarity and categorization are fundamental processes in human cognition that help complex organisms make sense of the cacophony of information in their environment. These processes are critical for tasks such as recognizing objects, making decisions, and forming memories. In this review, we provide an overview of the current state of knowledge on similarity and psychological spaces, discussing the theories, methods, and empirical findings that have been generated over the years. Although the concept of similarity has important limitations, it plays a key role in cognitive modeling. The review surfaces three key themes. First, similarity and mental representations are merely two sides of the same coin, existing as a similarity-representation duality that defines a psychological space. Second, both the brain's mental representations and the study of mental representations are made possible by exploiting second-order isomorphism. Third, similarity analysis has near-universal applicability across all levels of cognition, providing a common research language.

There is always room for moral improvement. However, very few prior reviews have focused on the phenomenon of moral improvement of self, social relations, or society. We first consider prevailing notions of the self-concept by highlighting the niche of theory and research that identifies an improving self as a possible identity and basis of motivation to act better and to be better. Second, we discuss moral improvement in the context of social relations, especially the close interpersonal relations that should most facilitate moral improvement. Third, we examine the moral improvement of society, focusing on the factors that facilitate or inhibit caring about potential immorality despite the fact that issues such as inequality, discrimination, and the climate crisis seem to be morally distant and impersonal. Finally, we discuss future directions for theory, research, and application.

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.