McPsyt Lab
About Our Lab
Our Mission
Led by Dr. David Benrimoh, the McGill Lab for Computational Psychiatry and Translation (McPsyt) leverages Computational Psychiatry to bridge neurobiological, cognitive, clinical, social, and societal perspectives on mental illness. Our goal is to develop a deeper mechanistic understanding of psychiatric disorders and create predictive models that enhance diagnosis, treatment, and prevention.​
Through this approach, we design and test innovative interventions—including neuromodulation and digital mental health tools—to reduce the severity and burden of psychiatric conditions. Our current research focuses on early psychosis, aiming to transform care through cutting-edge computational methods and translational research.
Our Research Areas
-
​Computational phenotyping of patient symptoms using Bayesian approaches, with a particular emphasis on psychosis and individuals at risk for psychosis.
-
Digital phenotyping using smartphone sensors and ecological momentary assessments (EMAs) to more accurately assess and monitor psychiatric symptoms in real time.
-
Personalized neuromodulation treatments, such as repetitive transcranial magnetic stimulation (rTMS), guided by neurobiological markers identified through computational and digital phenotyping.
Core Themes
Developing a digital assessment tools for phenotyping, identifying, and screening patients for psychosis and psychosis risk at the population level.​
Developing coherent computational types, including subgroups of people at risk for psychosis and people at risk for developing psychosis onset, using longitudinal data.​
Translating computational phenotypes using imaging and neuromodulation to develop preventative treatments aimed at preventing psychosis onset.
