200234 SE Theorie und Empirie wissenschaftlichen Arbeitens (Geist und Gehirn) 2 (2022W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Fr 02.09.2022 10:00 bis Mo 26.09.2022 10:00
- Abmeldung bis Mo 03.10.2022 10:00
Details
max. 20 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
This course is given in a block format of 9 units in November. Each unit will be around 4 hours long (including breaks) and divided into 2 parts: Unless otherwise instructed, we will always begin with theoretical lectures in HS H (at the dates/times below) before moving to the 'EEG Auswerteraum' on the 3rd floor for practical programming and analysis sessions.
Actual times for the course:Tuesdays 9:45 - 14:15
Thursdays 11:30 - 15:00Units may be moved online depending on the Covid-19 situation. You will be notified of any changes in advance.To register for this course please send an email to:moritz.stolte@univie.ac.atYou will receive a confirmation before the end of the registration period.It is highly recommended that you have access to a computer that meets the technical requirements to run MATLAB (https://de.mathworks.com/products/matlab.html), the Psychophysics Toolbox (http://psychtoolbox.org), and EEG Lab (https://sccn.ucsd.edu/eeglab/index.php). In addition, MATLAB should be installed and working already for the first session on 03.11.2022 (you may find a cheap student version online)! This will enable you to work on assignments on your own and is necessary in case we have to move the course online.The max. number of students for the course is 20.
The course is entirely given in English.
Students who have completed TEWA I will be prioritized.
- Donnerstag 03.11. 11:30 - 14:45 Hörsaal H Psychologie KG Liebiggasse 5
- Dienstag 08.11. 09:45 - 13:00 Hörsaal H Psychologie KG Liebiggasse 5
- Donnerstag 10.11. 11:30 - 14:45 Hörsaal H Psychologie KG Liebiggasse 5
- Dienstag 15.11. 09:45 - 13:00 Hörsaal H Psychologie KG Liebiggasse 5
- Donnerstag 17.11. 11:30 - 14:45 Hörsaal H Psychologie KG Liebiggasse 5
- Dienstag 22.11. 09:45 - 13:00 Hörsaal H Psychologie KG Liebiggasse 5
- Donnerstag 24.11. 11:30 - 14:45 Hörsaal H Psychologie KG Liebiggasse 5
- Dienstag 29.11. 09:45 - 13:00 Hörsaal H Psychologie KG Liebiggasse 5
- Donnerstag 01.12. 11:30 - 14:45 Hörsaal H Psychologie KG Liebiggasse 5
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
[ASSESSMENT]
The final grade considers active participation, oral presentations, and completion of assignments. Further details will be discussed in the course.
The final grade considers active participation, oral presentations, and completion of assignments. Further details will be discussed in the course.
Mindestanforderungen und Beurteilungsmaßstab
[REQUIREMENTS]
MATLAB or other programming skills are an advantage.
You must have access to a computer with a working version of MATLAB and required toolboxes!
MATLAB or other programming skills are an advantage.
You must have access to a computer with a working version of MATLAB and required toolboxes!
Prüfungsstoff
Discussed in class
Literatur
Discussed in class
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mi 14.09.2022 14:08
The course teaches the theoretical background and practical steps necessary to perform (and interpret the results of) electroencephalographic (EEG) experiments of the human brain.
We will use custom code in MATLAB (and EEGLAB) to analyze neural time-frequency data.Theory - Origin of the EEG signal
General data management in EEG Lab (MATLAB)
Data Preprocessing, e.g.:
- re-referencing/resampling
- filtering
- data visualization and artifact rejection
- independent component analysis
Fast Fourier Transform
Complex wavelet convolutionTheoretical motivation for event related potential (ERP) and time-frequency analyses.[METHODS:]
Practical MATLAB programming sessions, oral presentations by lecturer and students, in-class participation, weekly homework.