Project EMERALD
Evaluating Mechanisms of Emotion Regulation Across the Lifespan and in Depression (EMERALD). This project investigates the role of emotional regulation and the impact of depression across the lifespan. The ability to regulate one’s emotional responses is critical for maintaining emotional health in the face of adverse events that cumulate over time. We believe that multiple factors, including, age, depression status, neurocognitive functioning, and social support will impact the success of emotion regulation using reappraisal and distraction strategies. We also believe that the combined effect of those variables on strategy use will predict depressive symptoms further into a person’s lifespan. Ultimately, our goal for this project is to gain insights into how maturational changes influence the ability of depressed adults to reduce negative affect. This project is supported by a National Institute of Health R01 grant.
Neurocomputational Approaches to Emotion Decoding
This NIH-funded project uses machine learning and computational modeling to decode emotions from task-based and resting-state fMRI and psychophysiological signals. The project expands the set of emotions from the lab’s prior work on this topic and uses Markov modeling to infer how individuals dynamically transition across different emotional states. We are interested in linking these emotion profiles and dynamics with individual differences in affect and cognitive appraisals.
Mood and Memory
This project explores how mood biases episodic memory behaviorally and in the brain. We are especially interested in characterizing how mood impacts memory consolidation and how sustained moods interact with more acute emotional memory processes. This project is being led by graduate student Leonard Faul , with support from an NSF graduate fellowship, in collaboration with Felipe de Brigard.
Learning to Self-Regulate Using fMRI-based Neurofeedback
This project, funded by the Duke Institute for Brain Sciences seeks to understand how individuals learn to self-regulate through fMRI-based neurofeedback. This project extends the lab’s prior work that used interoceptive feedback signals as a basis for self-regulation. Graduate student Rachael Wright is leading this project as a joint effort between the LaBar and Adcock labs.
Neuromodulation of Emotions and Emotion Regulation
The lab is involved in several collaborative projects that use neuromodulation tools, such as TMS, in combination with structural or functional MRI, to modify emotional processing and regulation. The goal is to identify the critical nodes in the brain where neurostimulation impacts these processes as a potential therapeutic tool. Our initial work on this topic examined the role of the lateral parietal cortex in emotional distancing and was led by lab alumnus John Powers. Currently this line of work is being extended to mitigate emotion dysregulation in psychiatric disorders in collaboration with Andrada Neasciu and Greg Appelbaum in the Department of Psychiatry and Behavioral Sciences. These projects have received funding from the Duke Institute for Brain Sciences, the Charles Lafitte Foundation in Psychological Research, an NSF Graduate Fellowship, the Brain and Behavior Research Foundation, a KL2 professional development award, and the REAM foundation.
Neuroimaging of Emotions and Emotion-Cognition Interactions in PTSD
The lab has a long-standing collaboration with Rajendra Morey’s group at the Durham VA Hospital to examine the neural circuits involved in emotional processing and emotion-cognition interactions in PTSD. Our recent work has focused on characterizing how traumatic stress impacts the brain mechanisms for perceptual and conceptual fear generalization using conditioning-based paradigms. We are expanding our investigations to consider how PTSD affects the neural circuits of other emotions, such as shame and guilt, and their role in moral injury and moral decision-making. This work has been funded by the Department of Veterans Affairs.
Affect and Valuation
This project explores the relationship between affect and valuation using computational modeling, reinforcement learning tasks, and affect measures. We are particularly interested in how value computations influence affective experience, and how affect contributes to learning and decision-making. This project is led by graduate student Daniel Parr, and is being conducted in collaboration with Dr. Gregory Samanez-Larkin and Dr. Seth Madlon-Kay (Pearson lab).
Neural Dynamics of Emotional Prosody After Right Hemisphere Stroke
This project examines how right-hemisphere stroke affects the neural processing of emotional prosody using EEG. We're interested in understanding how the brain encodes and interprets emotional cues in speech, and how disruptions to these processes contribute to communication difficulty after stroke. By characterizing the timing and dynamics of these neural responses, the project aims to clarify why some individuals experience emotional aprosodia and how these patterns vary across right hemisphere stroke survivors. This work is led by graduate student Shanika I. Phillips Fullwood, in collaboration with the LaBar lab and the Minga Right Hemisphere Communication lab.
Creative Thinking in Emotion Regulation
This area of work seeks to measure emotion regulation processes from the theoretical and methodological lens of creative thinking. Beyond projects relating to the emotional benefits of making art, this effort also leverages idea generation as a level of analysis by which to model emotion regulation using creativity toolkits, both within strategies (e.g., reappraisal) and across. This work is spearheaded by graduate student Lucas Bellaiche with support from an NSF graduate fellowship, and has been also funded by grants such as the Charles Lafitte Foundation and DIBS' Impact Neuroscience fellowship. This highly interdisciplinary series of projects collaborates with individuals across the department (including Drs. Tamar Kushnir and Moria Smoski) and across the country (including Drs. Paul Seli and Leonard Faul).