227-0971-00L  Computational Psychiatry

SemesterAutumn Semester 2019
LecturersK. Stephan
Periodicityyearly recurring course
Language of instructionEnglish
CommentPlease note that participation in this course and the practical sessions requires additional registration until 23 August 2019 at: Link



Courses

NumberTitleHoursLecturers
227-0971-00 SComputational Psychiatry
Block course from September 2 - 6, 2019.
8:00 - 18:30h
60s hrs
02.09. - 06.09.08:15-19:00NO C 60 »
K. Stephan

Catalogue data

AbstractThis five-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 physiology (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.
ObjectiveThis course aims at bridging the gap between mathematical modelers and clinical neuroscientists by teaching computational techniques in the context of clinical applications. The hope is that the acquisition of a joint language and tool-kit will enable more effective communication and joint translational research between fields that are usually worlds apart.
ContentThis five-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 physiology (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.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersK. Stephan
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Additional information on mode of examinationOral exam (20 min) that assesses the understanding of general modeling principles and of specific mathematical models of behavioural and neuroimaging data taught by the course.

Learning materials

 
Main linkhttps://www.tnu.ethz.ch/de/teaching.html
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Biomedical Engineering MasterRecommended Elective CoursesWInformation
Computational Science and Engineering BachelorElectivesWInformation
Computational Science and Engineering MasterElectivesWInformation