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Psychiatric Control Systems

Our work focuses on investigating the engineering principles of behavioral, neural, and psychological dynamics in humans and how these dynamics change in psychiatric disorders. We use primarily techniques from dynamical systems theory, network control theory, and machine learning aiming to understand if and how these dynamics can be quantified, predicted, and controlled. Toward this end, we use cross-sectional and longitudinal behavioral and psychological data (such as symptoms trajectories) as well as neuroimaging (fMRI, DTI, T1, EEG) data together with neural stimulation techniques (ECT, tACS, etc.).

If and when we are successful in our scientific goals, our research will contribute to improvement of individualized treatment of psychiatric disorders using closed-loop interventions.