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26.09.2021 08:54:25
neu305 - Essentials of fMRI Data Analysis with SPM and FSL (Complete module description)
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Module label Essentials of fMRI Data Analysis with SPM and FSL
Module code neu305
Credit points 6.0 KP
Workload 180 h
1 SWS Seminar (SE) fMRI: Experimental Design, Data Collection and Analysis
Total workload 45h: 14h contact / 31h literature work
3 SWS Supervised exercise (UE) Statistical Analysis of fMRI Data with SPM and FSL
Total workload 135h: 42h contact / 93h practice with sample fMRI data sets
Institute directory Department of Neurosciences
Applicability of the module
  • Master's Programme Neuroscience (Master) > Background Modules
Responsible persons
Weerda, Riklef (Authorized examiners)
Sörös, Peter (Authorized examiners)
Weerda, Riklef (Module responsibility)
Skills to be acquired in this module

+ Neurosci. knowlg.
++ Expt. Methods
+ Independent research
+ Scient. Literature
+ Social skills
+ Interdiscipl. knowlg.
++ Maths/Stats/Progr.
+ Data present./disc.
+ Scientific English
+ Ethics

This module offers a concise introduction to the basic principles of functional magnetic resonance imaging (fMRI). Students will gain essential knowledge about experimental design, data collection and analysis. Special emphasis will be laid on the statistical background of fMRI data analysis and a hands-on introduction to SPM and FSL, two widely-used and free software packages for fMRI data analysis and results visualisation.
Module contents
1. Methodological basics of functional magnetic resonance imaging (fMRI)
2. Basic principles of fMRI experimental design and data collection
3. Statistical background of fMRI data analysis
4. Hands-on training in fMRI data analysis and results visualisation with SPM and FSL
Reader's advisory
Recommended textbook(s) or other literature:
Huettel, S.A., Song, A.W., McCarthy, G. (3rd ed., 2014). Functional Magnetic Resonance Imaging. Sunderland, MA: Sinauer.
Friston, K.J., Ashburner, J.T., Kiebel, S. (Ed., 2006). Statistical Parametric Mapping: The Analysis of Functional Brain Images. Amsterdam etc.: Elsevier, Academic Press.
Language of instruction English
Duration (semesters) 1 Semester
Module frequency annually, winter term, first half
Module capacity 40
Modullevel / module level
Modulart / typ of module Wahlpflicht / Elective
Lehr-/Lernform / Teaching/Learning method
Vorkenntnisse / Previous knowledge Recommended previous knowledge / skills: statistics, MATLAB
Course type Comment SWS Frequency Workload of compulsory attendance
WiSe 0
WiSe 0
Total time of attendance for the module 0 h
Examination Time of examination Type of examination
Final exam of module
witten exam (multiple choice) In addition, mandatory but ungraded: continuous active participation