227-0969-00L  Methods & Models for fMRI Data Analysis

SemesterAutumn Semester 2022
LecturersK. Stephan
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
227-0969-00 VMethods & Models for fMRI Data Analysis4 hrs
Tue08:15-12:00ETZ E 6 »
K. Stephan

Catalogue data

AbstractThis 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.
ObjectiveTo obtain in-depth knowledge of the theoretical foundations of SPM
and DCM and of their practical application to empirical fMRI data.
ContentThis course teaches state-of-the-art methods and models for fMRI data analysis in lectures and exercises. It covers all aspects of statistical parametric mapping (SPM), incl. preprocessing, the general linear model, frequentist and Bayesian inference, multiple comparison corrections, and event-related designs, and Dynamic Causal Modelling (DCM), a Bayesian framework for identification of nonlinear neuronal systems from neurophysiological data. A particular emphasis of the course will be on methodological questions arising in the context of clinical studies in psychiatry and neurology. Practical exercises serve to consolidate the skills taught in lectures.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits6 credits
ExaminersK. Stephan
Typeend-of-semester examination
Language of examinationEnglish
RepetitionA repetition date will be offered in the first two weeks of the semester immediately consecutive.
Mode of examinationoral 10 minutes
Additional information on mode of examinationMündliche 30-minütige Prüfung in Dreiergruppen (je 10 Minuten pro Kandidat*in).
Oral examination of 30 minutes in groups of three (10 minutes per candidate).

Learning materials

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Only public learning materials are listed.

Groups

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Restrictions

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Offered in

ProgrammeSectionType
Biomedical Engineering MasterRecommended Elective CoursesWInformation
Health Sciences and Technology MasterElective CoursesWInformation
Interdisciplinary Brain Sciences MasterElective Core ModulesWInformation
MAS in Medical PhysicsElectivesWInformation