200144 SE Seminar in Applied Psychology: Mind and Brain (2021W)
fMRi data preprocessing
Continuous assessment of course work
Labels
REMOTE
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.
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).
- Registration is open from We 01.09.2021 07:00 to Th 23.09.2021 07:00
- Deregistration possible until Mo 04.10.2021 07:00
Details
max. 20 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
The course is split in theoretical sessions and sessions in which the students will be analyzing data at home in small groups.
Thursday
07.10.
13:15 - 14:45
Digital
Thursday
14.10.
13:15 - 14:45
Digital
Thursday
21.10.
13:15 - 14:45
Digital
Thursday
28.10.
13:15 - 14:45
Digital
Thursday
04.11.
13:15 - 14:45
Digital
Thursday
11.11.
13:15 - 14:45
Digital
Thursday
18.11.
13:15 - 14:45
Digital
Thursday
25.11.
13:15 - 14:45
Digital
Thursday
02.12.
13:15 - 14:45
Digital
Thursday
09.12.
13:15 - 14:45
Digital
Thursday
16.12.
13:15 - 14:45
Digital
Thursday
13.01.
13:15 - 14:45
Digital
Thursday
20.01.
13:15 - 14:45
Digital
Thursday
27.01.
13:15 - 14:45
Digital
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 FSL package on their own computer. They will learn about the basics of MRI and fMRI, about how important preprocessing and noise reduction is, responsible conduct of research, and a career in academia. The course is split in theoretical sessions and practical sessions in which the students will be analyzing data at home in small groups.
Assessment and permitted materials
Assignments for each practical session (40%) will be graded as well as a mini paper at the end of class (40%). Participation and group discussion in the theoretical sessions will be graded with 20%. 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: We 21.06.2023 00:18