Computational psychiatry and cognitive neuroscience
Xiaosi Gu’s research combines computational modeling, cognitive neuroscience, neuroimaging, and intracranial recording to address fundamental questions about the human mind. Her early contributions established the framework of interoceptive inference, showing that the insular cortex integrates bodily and emotional signals in a Bayesian fashion to generate subjective feelings. She later extended this approach to addiction, proposing a computational model of drug craving as aberrant interoceptive inference—a framework that has reshaped how researchers conceptualize craving and its neural underpinnings. A second focus of the Gu lab is computational social neuroscience. This line of research has revealed the neural computations that support empathy, norm adaptation, and social controllability, and has more recently demonstrated distinct roles for dopamine and serotonin in social decision-making. These discoveries highlight the intricate ways in which brain circuits and neuromodulators shape social behavior, with direct implications for conditions such as depression, substance use disorder, and autism.
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Biography
Gu received her bachelor's degree in psychology and economics from Peking University and her PhD in Neuroscience from the Icahn School of Medicine at Mount Sinai, followed by postdoctoral training at University College London. In 2025, she joined Yale as a Professor of Psychiatry and Biomedical Informatics and Data Science, after serving as the Inaugural Director of the Center for Computational Psychiatry at Mount Sinai. Xiaosi's passion for neuroscience began in high school when she discovered the writings of Sigmund Freud, sparking her enduring fascination with the human mind.