This seminar teaches problem solving skills for computational neuroimaging (incl. associated computational analyses of behavioural data). It deals with a variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich and beyond, e.g., concerning mass-univariate/multivariate analyses and generative models of fMRI, EEG, OPM-MEG, or behavioural data.

This six-day course teaches state-of-the-art methods in computational psychiatry. It covers various computational models of cognition (e.g., learning and decision-making) and brain function (e.g., effective connectivity) of relevance for psychiatric disorders. The course not only provides theoretical background, but also demonstrates open source software in application to concrete examples.

This seminar deals with the development of clinically relevant computational tools and/or their application to psychiatry and psychosomatics. Complementary to the annual Computational Psychiatry Course, it serves to build bridges between computational scientists and clinicians and is designed to foster in-depth exchange, with ample time for discussion

ETH Week is an innovative one-week course designed to foster critical thinking and creative learning. Students from all departments as well as professors and external experts will work together in interdisciplinary teams. They will develop interventions that could play a role in solving some of our most pressing global challenges. In 2021, ETH Week will focus on the topic of health and well-being.

This course teaches methods and models for fMRI data analysis, covering all aspects of statistical parametric mapping (SPM), incl. preprocessing, the general linear model, statistical inference, multiple comparison corrections, event-related designs, and Dynamic Causal Modelling (DCM), a Bayesian framework for identification of nonlinear neuronal systems from neurophysiological data.

The module Psychiatrie & Computational Psychiatry introduces the most common psychiatric disorders, including etiology, diagnostics and therapy. In addition, under the guidance of a clinician, the students will acquire practical skills for assessing psychopathology in patients. The module concludes with an introduction to concepts and practical applications of Computational Psychiatry.

Current topics in Biomedical Engineering presented by speakers from academia and industry.

This colloquium discusses research topics in Translational Neuromodeling (the development of mathematical models for diagnostics of brain diseases) and Computational Psychiatry/Psychosomatics (the application of these models to concrete clinical questions). The range of topics is broad, incl. computational techniques, experimental paradigms (fMRI, EEG, behaviour), and clinical questions.

This course provides an introduction to Translational Neuromodeling (the development of computational assays of neuronal and cognitive processes) and their application to concrete clinical questions (Computational Psychiatry/Psychosomatics). It focuses on a generative modeling strategy and Bayesian models of neuroimaging data and behaviour, incl. exercises and project work.