227-0967-00L  Computational Neuroimaging Clinic

SemesterAutumn Semester 2020
LecturersK. Stephan
Periodicityevery semester recurring course
Language of instructionEnglish
CommentPrerequisite: Successful completion of course "Methods & Models for fMRI Data Analysis", "Translational Neuromodeling" or "Computational Psychiatry"



Courses

NumberTitleHoursLecturers
227-0967-00 VComputational Neuroimaging Clinic2 hrs
Wed14-16ETZ H 91 »
K. Stephan

Catalogue data

AbstractThis seminar teaches problem solving skills for computational neuroimaging, based on joint analyses of neuroimaging and behavioural data. It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich, e.g. mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.
Objective1. Consolidation of theoretical knowledge (obtained in the following courses: 'Methods & models for fMRI data analysis', 'Translational Neuromodeling', 'Computational Psychiatry') in a practical setting.
2. Acquisition of practical problem solving strategies for computational modeling of neuroimaging data.
ContentThis seminar teaches problem solving skills for computational neuroimaging, based on joint analyses of neuroimaging and behavioural data. It deals with a wide variety of real-life problems that are brought to this meeting from the neuroimaging community at Zurich, e.g. mass-univariate and multivariate analyses of fMRI/EEG data, or generative models of fMRI, EEG, or behavioural data.
Prerequisites / NoticeThe participants are expected to have successfully completed at least one of the following courses:
'Methods & models for fMRI data analysis',
'Translational Neuromodeling',
'Computational Psychiatry'

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.
Admission requirementThe participants are expected to have successfully completed at least one of the following courses: 'Methods & models for fMRI data analysis', Translational Neuromodeling', or 'Computational Psychiatry'
Additional information on mode of examinationOral presentation and oral exam (20 min) concerning methods related to one of the practical problems the seminar dealt with.

Learning materials

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

Groups

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Restrictions

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Offered in

ProgrammeSectionType
Biomedical Engineering MasterRecommended Elective CoursesWInformation
MAS in Medical PhysicsElectivesWInformation