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Computational Psychiatry
Last Updated: 2026-06-03 00:07:31
Abstract
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.
Objective
This course teaches computational techniques to students/researchers (from both clinical and computational backgrounds) in the context of clinical applications. The goal is to equip students with concepts and tools that enable them to engage in multidisciplinary computational research on mental health problems.
Content
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. Furthermore, practical exercises provide in-depth exposure to different software packages. Please see http://www.translationalneuromodeling.org/cpcourse/ for details.
General Information
- Language
- English
- Levels
- BSC , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar |
Computational Psychiatry
Block course 07.09.-12.09.2026
|
No time listed | 60 h semesterly |
Offered In
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed.)
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Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed. All courses listed as core courses (not electives) for one of the following ETH MSc programmes, MSc Statistics, MSc Physics, MSc Computer Science, MSc (Applied) Mathematics, MSc Neural Systems and Computation, MSc Robotics, Systems, and Control, MSc Data Science, MSc Electrical Engineering and Information Technology, can be taken as an elective course in the MSc CSE without prior permission.)
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Recommended Elective Courses (These courses are particularly recommended for the Bioimaging track. Please consult your track advisor if you wish to select other subjects.)
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Track: Biomedical Engineering (The core courses and specialisation courses below are a selection for students who wish to specialise in the area of "Biomedical Engineering", see . The individual study plan is subject to the tutor's approval.)
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Specialisation Courses (These specialisation courses are particularly recommended for the area of "Biomedical Engineering" but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialisation courses during the Master's Programme.)
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Elective Core Modules (Courses listed here take place at ETH Zurich. Further courses and a complete list of the Elective Core Modules can be found here: Please register for ETH-courses at ETH Zurich, for UZH-courses at UZH.)
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