Cognitive scientist, computational neuroscientist, well-being researcher—it’s hard to choose only one label to describe Shawn Rhoads, PhD, who recently completed a postdoctoral research fellowship at the Center for Computational Psychiatry at the Mount Sinai Health System. But one title that sticks is recipient of the 2024 National Institute of Health (NIH) Director’s Early Independence Award. The prestigious award, part of the NIH’s High-Risk, High-Reward Research program, supports creative early-career scientists in launching independent research careers.

The award will support Dr. Rhoads as he launches his own lab at Mount Sinai, where he is transitioning to a faculty position as Assistant Professor of Psychiatry, Icahn School of Medicine at Mount Sinai. His research uses modern tools including neuroimaging and computational modeling to approach a modern—and growing—problem. “We’re in the midst of a loneliness epidemic,” Dr. Rhoads explains.

In 2023, the United States Surgeon General released a health advisory on social isolation, citing recent research that found half of U.S. adults report loneliness. Such social disconnection has been linked to a host of negative outcomes, including a greater risk of heart disease, dementia, depression, and early death.

Dr. Rhoads’s research aims to understand the cognitive and neural processes that drive social decision-making—work that could lead to interventions that boost social connection and improve well-being.

A New Way to Study Loneliness  

As an undergrad at the University of Southern California, Dr. Rhoads double majored in psychology and physics. “I was interested in physics as a potential research path, but it was missing that human element,” he says. Fortunately, he found the perfect marriage of his interests and talents in cognitive science and computational modeling. He went on to earn a PhD in the Laboratory on Social and Affective Neuroscience at Georgetown University.

In 2022, he joined Mount Sinai as a postdoctoral fellow in the lab of Xiaosi Gu, PhD, Director of the Center for Computational Psychiatry at the Mount Sinai Health System, and Associate Professor of Psychiatry, and Neuroscience, Icahn School of Medicine at Mount Sinai. It was a perfect fit. “Mount Sinai is one of the only places in the country with an integrated center using computational methods to better understand mental health,” he says.

Working with Dr. Gu, Dr. Rhoads set about designing a project to learn more about loneliness. One response to feeling lonely is to experience a craving or desire for social interaction. “We often think of craving as a negative thing, as in addiction,” he says. “But in this case, craving can be positive if it motivates us to go out into the world to seek connection.”

Some of Dr. Gu’s previous work explored craving in substance use disorders. Now, she and Dr. Rhoads are applying a similar framework to understand how social craving arises, and what happens when that process goes awry. Their model suggests that social craving changes in response to social cues, such as seeing a group of people having fun together. Such social cravings, they predict, are also influenced by expectations and experiences. What happens, for instance, if someone goes to a party expecting a fulfilling social interaction, but doesn’t end up connecting with anyone?

With support from the NIH award, he will use functional brain imaging to understand what happens in people’s brains when they experience social cravings and engage in social interactions. Ultimately, Dr. Rhoads hopes to determine whether those patterns of neural activity can predict negative mental health outcomes such as depression or anxiety.

Seeing Social Decision Making in Real Time

In another line of research, Dr. Rhoads is looking into the brain to see social decision-making in action. In collaboration with researchers, including Ignacio Saez, PhD, Associate Professor of Neuroscience, Neurosurgery, and Neurology, Icahn Mount Sinai, and leader of the invasive electrophysiology core at the Nash Family Center for Advanced Circuit Therapeutics at Mount Sinai, he is working with patients hospitalized while receiving 24/7 intracranial direct brain monitoring as part of their epilepsy treatment.

Dr. Rhoads designed a “gamified” cognitive task for two patients to play together. Each player can earn points working independently, but they have a better chance of high scores if they team up to work with one another. “In order to play together, you need to engage in higher-order social cognitive processes,” he says. For instance, the players have to think multiple steps into the future—not only about their own actions, but also about what they think their partner might do. “The player’s choices are contingent upon their beliefs about what the other person’s strategy is. If I go right, for example, I might assume you’ll go left,” he says.

This ability to consider another person’s mental state is known as theory of mind. By taking direct brain recordings while patients play the game, Dr. Rhoads and his colleagues can apply computational models to make predictions about the players’ beliefs and actions, and see how those predictions play out in the form of brain activity. By collecting brain recordings from two individuals as they interact, the researchers can see social learning and social decision-making in real time. “This is a dynamic system, with changing information as the two players adapt and make choices,” he says.

The ability to imagine another person’s thoughts and perspectives can be helpful, such as when two people are collaborating. But it can also go awry. A person with social anxiety, for example, might ruminate on what they think another person is thinking about them. A person with psychosis might have paranoia about other people being out to get them. “The idea is that we can adapt this model to examine when these cognitive processes can be maladaptive,” Dr. Rhoads says.

A Bright Future for Computational Psychiatry

Though Dr. Rhoads is launching his independent research career, he’s not interested in going it alone. He is eager to collaborate across disciplines, bringing together diverse tools and perspectives to answer questions with implications for individuals and for society.

Meanwhile, he hopes to make computational research accessible to more people. He’s co-director of the Summer Program in Computational Psychiatry Education (SPICE), a research program for high school and college students offered by the Center for Computational Psychiatry. He’s also helping to organize a computational psychiatry workshop for trainees of all levels.

“Computational psychiatry can seem like a daunting field to get into. But we need a diverse and well-represented future of researchers,” he says. “Making these tools more accessible will help us answer some big questions about social behavior and well-being.”