According to appraisal theory, emotions result from an individual's meaning analysis of the implications of his/her circumstances for personal well-being, and individual differences in emotion arise when individuals appraise similar situations differently. Relational models of appraisal attempt to describe the situational and dispositional antecedents of appraisals, and should allow one to predict such individual differences. In this article, we review three examples of our efforts toward developing relational appraisal models. In two, we start with a particular appraisal component, motivational relevance (...) and problem-focused coping potential (Smith & Lazarus, 1990), respectively, and describe and test the relational model proposed for that component. In the third, as a precursor to developing a true relational model, we examine another appraisal component, emotion-focused coping potential, from a more dispositional perspective. We conclude by considering both the potential value of relational appraisal models, and future directions in the development of these models. (shrink)

Physicians, nurses, and other clinicians readily acknowledge being troubled by encounters with patients who trigger moral judgments. For decades social scientists have noted that moral judgment of patients is pervasive, occurring not only in egregious and criminal cases but also in everyday situations in which appraisals of patients' social worth and culpability are routine. There is scant literature, however, on the actual prevalence and dynamics of moral judgment in healthcare. The indirect evidence available suggests that moral appraisals function via a (...) complex calculus that reflects variation in patient characteristics, clinician characteristics, task, and organizational factors. The full impact of moral judgment on healthcare relationships, patient outcomes, and clinicians' own well-being is yet unknown. The paucity of attention to moral judgment, despite its significance for patient-centered care, communication, empathy, professionalism, healthcare education, stereotyping, and outcome disparities, represents a blind spot that merits explanation and repair. New methodologies in social psychology and neuroscience have yielded models for how moral judgment operates in healthcare and how research in this area should proceed. Clinicians, educators, and researchers would do well to recognize both the legitimate and illegitimate moral appraisals that are apt to occur in healthcare settings. (shrink)

The appraisal theory formulations posited in this special section consider the appraisal process to afford flexibility to emotional responding by the malleability of how people appraise events. I argue that not only the way in which events are appraised but also the way in which appraisals drive changes in other emotion components is characterized by flexibility across persons and context. Accounting for such flexibility is crucial for the further development of appraisal theories and their application to other domains.

A theoretical framework for the reinforcement learning of aesthetic biases was recently proposed based on brain circuitries revealed by neuroimaging. A model grounded on that framework accounted for interesting features of human aesthetic biases. These features included individuality, cultural predispositions, stochastic dynamics of learning and aesthetic biases, and the peak-shift effect. However, despite the success in explaining these features, a potential weakness was the linearity of the value function used to predict reward. This linearity meant that the learning process employed (...) a value function that assumed a linear relationship between reward and sensory stimuli. Linearity is common in reinforcement learning in neuroscience. However, linearity can be problematic because neural mechanisms and the dependence of reward on sensory stimuli were typically nonlinear. Here, we analyze the learning performance with models including optimal nonlinear value functions. We also compare updating the free parameters of the value functions with the delta rule, which neuroscience models use frequently, vs. updating with a new Phi rule that considers the structure of the nonlinearities. Our computer simulations showed that optimal nonlinear value functions resulted in improvements of learning errors when the reward models were nonlinear. Similarly, the new Phi rule led to improvements in these errors. These improvements were accompanied by the straightening of the trajectories of the vector of free parameters in its phase space. This straightening meant that the process became more efficient in learning the prediction of reward. Surprisingly, however, this improved efficiency had a complex relationship with the rate of learning. Finally, the stochasticity arising from the probabilistic sampling of sensory stimuli, rewards, and motivations helped the learning process narrow the range of free parameters to nearly optimal outcomes. Therefore, we suggest that value functions and update rules optimized for social and ecological constraints are ideal for learning aesthetic biases. (shrink)

This essay discusses four definitions of beauty from Western philosophy in light of recent experimental work from the more modern fields of psychology and biology. The first idea, derived from Plato, that beauty consists of relationships between parts, is partially confirmed by recent psychological experiments on infants and adults. The second idea, that beauty consists of one salient feature amid a mass of details, is more recent, perhaps from Hume, and is confirmed by some experiments on adults, but this finding (...) has not been replicated in non-Western cultures. The third idea, that beauty is based on utility, occurs in Plato but is more difficult to support through experiments; biology suggests that a longing for beauty, not merely for survival, is an evolutionary target. Finally, the fourth idea, that beauty is a type of cognitive pleasure, is a constant thread from Plato through the work of Aquinas and Kant and seems to confirm a preference for an optimum level of complexity by adults, but cannot explain a parallel preference for complexity in human infants. (shrink)

How do we come to like the things that we do? Each one of us starts from a relatively similar state at birth, yet we end up with vastly different sets of aesthetic preferences. These preferences go on to define us both as individuals and as members of our cultures. Therefore, it is important to understand how aesthetic preferences form over our lifetimes. This poses a challenging problem: to understand this process, one must account for the many factors at play (...) in the formation of aesthetic values and how these factors influence each other over time. A general framework based on basic neuroscientific principles that can also account for this process is needed. Here, we present such a framework and illustrate it through a model that accounts for the trajectories of aesthetic values over time. Our framework is inspired by meta-analytic data of neuroimaging studies of aesthetic appraisal. This framework incorporates effects of sensory inputs, rewards, and motivational states. Crucially, each one of these effects is probabilistic. We model their interactions under a reinforcement-learning circuitry. Simulations of this model and mathematical analysis of the framework lead to three main findings. First, different people may develop distinct weighing of aesthetic variables because of individual variability in motivation. Second, individuals from different cultures and environments may develop different aesthetic values because of unique sensory inputs and social rewards. Third, because learning is stochastic stemming from probabilistic sensory inputs, motivations, and rewards, aesthetic values vary in time. These three theoretical findings account for different lines of empirical research. Through our study, we hope to provide a general and unifying framework for understanding the various aspects involved in the formation of aesthetic values over time. (shrink)