Isabel Berwian

Isabel Berwian is an Associate Research Scholar at the Princeton Neuroscience Institute and Department of Psychology, affiliated with the Nivlab. Her work focuses on developing computational tools to understand psychotherapy mechanisms and predict treatment outcomes, particularly regarding antidepressant discontinuation relapse. She holds a PhD from the University of Zurich, where she studied relapse predictors after antidepressant cessation, and is licensed as a psychotherapist in Germany.

Research Interests: Computational Psychiatry, Neurocognitive Predictors, Depression Treatment Optimization, and Machine Learning Applications in Clinical Settings. Her studies combine neuroimaging, behavioral experiments, and computational models to identify biomarkers for therapy response.

Key Contributions: Pioneered work on frontal alpha asymmetry as a relapse predictor, validated EEG and fMRI biomarkers, and advanced reinforcement learning frameworks for psychotherapy analysis. Her 2025 machine learning studies highlight both potential and limitations in modeling affective physiology.

Labs/Teams: Active member of Nivlab, collaborating on interdisciplinary projects in computational psychiatry and translational neuroscience.