Projects

The goal of this project is to use self-report and behavioral assessments in individual’s daily lives to better understand how emotional processes unfold over time. The project idea includes the use of daily surveys and behavioral data sampling via periodic, random recordings of ambient sounds to better capture and understand how individuals experience a variety of emotional and interpersonal states in real time. Through this line of work, we are better able to (a) compare naturalistic data with cross-sectional data to determine how much they converge, (b) compare self-report with behavioral data to determine how much they converge, (c) model the self-report and behavioral compositions of latent emotional constructs such as anxiety, depression, and other emotional states, and (d) test predictors of emotional and interpersonal change over time.

This project examines the neural bases of one important form of emotion regulation, namely reappraisal, which involves altering the emotional significance of a stimulus by changing how one thinks about that stimulus. Using fMRI measures of brain activation, this project tests hypotheses concerning specific prefrontal regions thought to be associated with cognitive control, as well as specific subcortical structures such as the amygdala, thought to be associated with emotion.

One major postulate of many contemporary theories of emotion is that emotion imposes coherence across multiple response systems (e.g., experiential, behavioral, and physiological). Surprisingly, few studies have tested this core hypothesis, and those that have done so have yielded mixed results. In this project, we are obtaining continuous measures of emotion experience, expression, and physiology, and examining the conditions under which responses coherence is evident.

The goal of this project is to create a computational model that will help us understand the unfolding of emotions at the group level (collective emotion) and to correlate this model with real life events. The project includes three parts. In the first part, we conduct lab experiments to learn how people perceive collective emotions and how they are influenced by these emotions. In the second part, we use these insights as a basis for a computational model (agent-based model) of collective emotion. In the third part we correlate our model with data from social networks. In the current project, we use Twitter data from the Michael Brown shooting in Ferguson for our analyses.

This project explores the relations between personality (measured at multiple levels, ranging from the broad - e.g. Extroversion, Neuroticism - to the specific -e.g., emotional expressivity) and measures of typical emotional experience, expression, and regulation. One goal of this work is to understand the role individual differences play in basic emotion and emotion regulation processes.

This project examines the role of emotion and emotion regulation in social functioning. Social functioning is assessed in multiple contexts ranging from peer reports of typical behavior to conflict conversations between dating partners. One goal of this research is to understand how different forms of emotion regulation affect social functioning. A second goal of this project is to better understand the impact of individual differences in emotion regulation on important outcomes such as social networks and relationship longevity.

This project studies emotion regulation in the context of emotionally ambiguous cues. Stimuli are often not univocal, clear, and well defined regarding their emotional meaning, but are rather under-determined and ambivalent. To better understand the regulatory strategies that influence the responses to situations that may elicit mixed emotional feelings, we systematically elicit such feelings in the lab. One goal of this project is to discern how different emotion regulation strategies alter the emotional response to ambiguous situations.

This project uses EEG/ERP methods to examine how the processes involved in emotion generation and regulation unfold over time. The central assumption guiding this line of research is that the temporal features of such processes can inform our understanding of how they operate, as well as how they may be rendered dysfunctional in certain forms of psychopathology.

Emotional disturbances are commonly observed in individuals with autism spectrum disorder (ASD), however, the scientific understanding of causes and consequences of such emotional disturbances are limited. The SPL lab has examined in a multi-method, multi-session study emotion reactivity and emotion regulation in children and adolescents with ASD. On the basis of the insights from this study, a parenting workshop has been developed to support parents of children on the spectrum. In the workshop we present evidence based strategies to help parents regulate both their emotions as well as their children's.

We are conducting clinical interventions using cognitive-behavioral therapy and mindfulness meditation based stress reduction for adults with social anxiety disorder. These clinical fMRI research studies are examining the brain-behavioral mechanisms of therapeutic change associated with two distinct psychotherapy treatment programs.

Middle school represents a critical transition for students, and many students show a decline in academic achievement and emotional well-being during this time. To reverse these negative outcomes, we are developing an online intervention designed to teach sixth- and seventh-graders a growth mindset of emotion regulation and give them emotion regulation strategies, with the goal of improving academic performance. This research is supported by the Institute of Education Sciences, U.S. Department of Education.