Universität Wien
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200144 SE Seminar in Applied Psychology: Mind and Brain (2023W)

fMRi preprocessing

4.00 ECTS (2.00 SWS), SPL 20 - Psychologie
Continuous assessment of course work

Dieses Anwendungsseminar kann für alle Schwerpunkte absolviert werden!

Anwendungsseminare können nur fürs Pflichtmodul B verwendet werden! Eine Verwendung fürs Modul A4 Freie Fächer ist nicht möglich.
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 20 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 05.10. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 12.10. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 19.10. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 09.11. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 16.11. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 23.11. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 30.11. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 07.12. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 14.12. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 11.01. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 18.01. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5
  • Thursday 25.01. 15:00 - 16:30 Hörsaal H Psychologie KG Liebiggasse 5

Information

Aims, contents and method of the course

The course will teach the basics of data analyses for fMRI studies with a focus on preprocessing (using FSL) as well as further analyses of resting state data. Although previous experience with fMRI data analyses is not required, fMRI preprocessing is advanced. Students should all have a fundamental understanding of data analyses and statistics and should enjoy trouble-shooting on the computer and analyzing data. The students are required to install an virtual FSL package on their own computer. They will learn about the basics of MRI and fMRI, about how important preprocessing and noise reduction is and responsible conduct of research. The course is split in theoretical sessions and practical virtual sessions in which the students will be analyzing data in small groups.

Assessment and permitted materials

Assignments for each practical session (45%) will be graded as well as a mini paper at the end of class (45%). Participation and group discussion in the theoretical sessions will be graded with 10%. Students fail class if they do not hand in all assignments.

Minimum requirements and assessment criteria

Interest in neuroimaging, data analyses, and coding. Students should all have a fundamental understanding of data analyses and statistics and should enjoy trouble-shooting on the computer and analyzing data. English is a requirement.

Examination topics

Reading list

Association in the course directory

Last modified: Fr 13.10.2023 16:07