Research

The Yu Emotion Science Lab (YES Lab) seeks to understand the neural and psychological basis of social emotions and moral cognition. To achieve this, we integrate novel experimental tasks, ecologically valid measures, computational methods, and neuroscience to explore the “why” (social adaptive goals), the “what” (cognitive operations), and the “how” (biological implementation) of the psychological phenomena we are interested in (we summarize this approach in a recent Perspective paper in Nature Reviews Psychology, Yu et al., 2024). 

While our publication page offers insight into our past work, below you can find a summary of both our past and new research directions:

Neurocognitive basis of social emotions

One of our most established lines of research focuses on the neurocognitive basis of social emotions, including guilt (Yu et al., 2014; Yu et al., 2020; Li et al., 2020; Gao et al., 2021), gratitude (Yu et al., 2017; Yu et al., 2018), and indebtedness (Gao et al., 2024). The novelty of our research lies in the creative combination of interpersonal tasks and computational models, which allows us to better understand the complex behavioral motivations behind these emotions (Yu et al., 2017; Gao et al., 2018; Shen et al., 2023). Additionally, we investigate how these emotions explain individual differences in moral decision-making (Yu et al., 2022; Hu et al., 2023).

Along this line, our lab is currently exploring the cross-cultural generalizability and differences in the neural and computational bases of social emotions and moral cognition. In one project, we developed a computational model that explains the type and intensity of social emotions people feel about actions within different social relationships. In another project, we investigated whether and how failure to fulfill social expectations is related to negative emotions (such as guilt and anxiety) in Chinese and American college students.

 The roles of moral evaluation in social emotions?

Moral cognition, which primarily coordinates and permeates day-to-day social interactions, should play a crucial role in the appraisal of social emotions. Theories and debates in moral philosophy regarding moral considerations as an integral component of social emotions have inspired some of our recent research aiming to expand the psychological models of social emotions to better incorporate a rich and complex role of moral cognition in social emotions.

In a recent research, we highlight how gratitude is sensitive to the moral status of the helper and helping act. My former undergraduate trainee Yubo Zhou (now a PhD student at UPenn) and I carried out a series of studies where we manipulated the moral status of the helping behavior and the helper in hypothetical vignettes (Yu et al., 2024). We found that participants felt less grateful and more uneasy when offered immoral help, and when offered morally neutral help by an immoral helper, even after controlling for the antecedents in the classic model of gratitude. Another example that demonstrates the complex moral nature of social emotions is the moral sensitivity of compassion. Do we feel compassion equally for all human beings, including morally bad people who are suffering? Or should we? Inspired by research and theories in sociology and philosophy surrounding the role of moral judgment in compassion, my former undergraduate trainees Jie Chen (now a PhD student at U Chicago) and Bernadette Dardaine (now a therapist at Sharp HealthCare) carried out a series of experiments to fill in the gap in the empirical psychological research regarding the role of moral judgment in compassion (Yu et al., 2023). 

Neurocognitive basis of moral cognition

Another line of our research seeks to understand the neurocognitive basis of moral cognition. We have proposed a computational framework to unify various techniques and vocabularies in moral cognition research (Yu et al., 2019).This framework centers on the tendency of harm aversion, a moral sentiment defined as a distaste for harming others, and integrates economic utility models of harm aversion with various moral cognition tasks to shed light on the neurocognitive mechanisms behind different domains of moral cognition (e.g., decision-making, judgment, inference) and their intersections. One prominent theoretical value of studying moral cognition in the unifying framework is a shared set of tasks, measurements, and terminology across different domains of moral cognition. This set of “common language” makes it easier to quantitatively compare psychological processes across domains of moral cognition and thus facilities the investigation of the phenomena at the intersections of multiple domains of moral cognition.

For example, moral hypocrisy is an interesting moral phenomenon lying at the intersection of moral decision-making (“what one does”) and moral judgment (“what one says”). We combined a model-based moral decision-making and moral judgment task with fMRI, which revealed the neurocognitive processes underlying hypocritical behavior (Yu et al., 2022). Another interesting example is moral influence, the phenomenon where observing others' moral or immoral behaviors modifies one's own moral decision-making. We combined drift diffusion model (DDM) with the harm aversion task to understand the cognitive mechanisms underlying moral influence (Yu et al., 2021).

Emotion and morality across cultures and times

How do we know whether an American and a German feel the same way when one claims to feel ‘guilty’ whereas the other claims to feel ‘schuldig’? Perhaps the subjective experience is obscure to observers, however we can track and analyze the events that lead to the agent’s using a given emotional term to express themselves. By applying machine learning algorithms to large-scale corpus data (e.g., online social network, digital libraries), we can capture the evolution of meanings, attitudes, and values across historical periods and cultures. Combining historical materials and neuroimaging, we are also able to identify brain-based signatures of psychological constructs (e.g., sense of justice), and to examine its generalizability across times and space.

A new direction of our lab focuses on the historical evolution of moral and emotional concepts. In a recent project, we examined the evolution of moral attitudes towards effort and efficiency in Chinese and American history (Chen et al., 2024). Using word embedding techniques, we developed computational linguistic indicators for these concepts and analyzed their historical evolution in Chinese and American corpora. We are currently obtaining a Chinese historical text corpus, which will allow us to study the evolution of moral and emotional concepts over a much longer period.

Neural computational mechanisms of social trait perception

Another new direction of my lab aims to understand how individuals perceive social traits from faces and how perception of others’ social traits influences our social emotions during interactions. In a recent theoretical paper (Yu et al., 2023), we promote the use of multimodal cognitive neuroscience approaches to study the interplay between social trait perception and emotions. We propose that the processes underlying social trait perception and the processes underlying social emotions have mutual influence on each other: how we perceive a social partner’s social traits (e.g., warm, competent) matters for the type and intensity of social emotions we would feel when we engage in various kinds of social interactions with the social partner; similarly, the social emotional contexts in which we encounter a social partner (e.g., do we feel guilty or angry with the partner) may also bias how we perceive social traits from them.

In an ongoing project, we examine two routes of social trait perception – visual features of the face and conceptual knowledge of the person. We asked participants to evaluate an array of naturalistic celebrity faces for a comprehensive set of social traits, while also inputting these faces and identities to face-based and text-based deep neural network models. Supporting our hypothesis, variance in human social trait judgments was significantly associated with variance in visual and conceptual features of the faces (Chen et al., in prep). 

The knowledge of a partner’s social traits (e.g., warm vs. critical) should also guide how one reacts to and interacts with the social partner during social interactions. In a recent work, we combined the above social trait perception task with the interpersonal harm task to elicit guilt. We found that the tendency to perceive others’ faces as critical was positively associated with the tendency to feel guilty for causing unpleasant outcome to a social partner in neurotypical participants, but the opposite pattern was true for the ASD participants (Zhao et al., 2024).

We collaborate closely with social psychoogists and neuroscientists of social trait perception such as Professor Shuo Wang at Washington University in St. Louis and Professor Chujun Lin at UCSD on these projects.