Two of our most recent projects apply our theory of emotion, stress, and empathy with multimodal physiological data collection and machine learning to study people's response to real-world events. In both studies, participants wear biometric devices (a watch or a ring) that measure their physiological response during a real-world event and then the data are aligned with self-report and analyzed through traditional inferential statistics and and machine learning and neural network approaches. In a collaboration with the Medical University of South Carolina and Clemson University we are testing physiological state matching (concordance) between caregivers and therapists during family-based therapy for African American adolescents with diabetes and between veterans and therapists during PTSD treatment. We predict that higher emotional concordance between the two individuals will improve their therapeutic alliance and predict better health outcomes. A current grant is also using a similar method to test for people's emotional and stress-based response to a ride in an autonomous vehicle (AV). With Toyota and MCity, we are again measuring people's psychophysiological response during an AV ride, using the biometric watch or ring. We examine the impact of how we explain AVs to people on their emotional and stress-based response during the ride, alongside comparing these responses by demographic attributes like race, age, and disability status. AV shuttles can solve municipal transportation problems that impact lower SES individuals, shift workers, older adults, and people with disabilities, but only if those populations feel safe to ride in them.
I have a diverse research background, which lends itself to my interdisciplinary approach. My undergraduate degree was in cognitive science at Virginia where I focused on philosophical and neuroscientific approaches to understanding consciousness (with Dan Willingham) while also working at NIMH studying the neurophysiology of monogamy in voles with Tom Insel. I later applied these concepts to study non-human animals' emotions, empathy, and social and resource decisions in captive primates (post-baccalaureate work at Emory University with Frans de Waal) and in food-storing rodents like kangaroo rats and squirrels (graduate school with Lucia Jacobs at Berkeley). After obtaining an MA and PhD in behavioral neuroscience from Berkeley, I transitioned back to studying human emotions and decisions in a post-doctoral fellowship in the Department of Neurology at University of Iowa Hospitals and Clinics, where they specialized in the study of how patient brain lesions impact their emotions and decisions. My work as faculty at Michigan has integrated all of these approaches to understand how people make decisions about key resources like altruistic aid, consumerism, and the natural environment, based on how the brain evolved to handle essential problems like acquiring food and mates and caring for offspring.
People's brains were designed to address problems that are immediate, directly sensed, and that impact them. They were also designed to feel empathy for others and to want to help those in distress and need but, again, for people who are immediate. In contrast, most of the world's current crises occur far from us, even if we often promote those issues through our own actions or inactions (e.g., we create poorly regulated factories, send waste, and remove natural resources like trees and minerals from other countries who do not benefit from the rewards as much as we do). Even though worldwide phenomena like illnesses, climate change, pollution, and global instability ultimately impact all of us, the most deadly consequences are less directly felt by Americans. We find it hard to wrap our heads around the issues, feel connected to the distress or destruction, or feel like we could do anything to help. I want to find better ways to capture and convey these problems to the public so they can better understand how their lives impact other people, animals, and the environment and can do something to help.
In physiology and neuroscience we can collect a tremendous amount of data. To date, much of the information in these data streams is lost due to the way we aggregate and simplify the data for our traditional inferential statistical methods. By working with data scientists and AI experts, social scientists can make more sophisticated inferences about people's feelings during real-world encounters and we can test ways to generate states like empathy and altruism for other people, animals, and the environment that can proceed more quickly and be rolled out more broadly to impact more people.
We started a new organization–SciFusion–to use fiction, media, and art to teach students and the public about science. We have had two small conferences to date at Michigan and the UK and are aggregating faculty from all around the world who share this interest. We write short stories to teach specific concepts in science, we create entertaining videos to teach science and critical thinking, and we use art to help people understand concepts in social and neural science. We aim to also use the stories to test the best ways to generate empathy for people outside of one's own social group. Join us! I also play a lot of tennis. We were state champions one summer!