psy170 - Neurophysiology (Complete module description)

Module label	Neurophysiology
Module code	psy170
Credit points	6.0 KP
Workload	180 h
Institute directory	Department of Psychology
Applicability of the module	Master's Programme Neurocognitive Psychology (Master) > Mastermodule
Responsible persons	Debener, Stefan (module responsibility) Debener, Stefan (authorised to take exams)
Prerequisites	Enrolment in Master's programme Neurocognitive Psychology.
Skills to be acquired in this module	Goals of module: Students will understand the basic concepts of biomedical signal processing. They will use EEG analysis tools interactively and independently and will understand the complete chain of EEG analysis steps, from data import to the illustration of results. They will be able to use open source tools for EEG analysis and apply theoretical knowledge to practical problems of physiology. Competencies: ++ Neuropsychological / neurophysiological knowledge ++ experimental methods ++ statistics & scientific programming ++ ethics / good scientific practice / professional behavior + group work + project & time management
Module contents	Students will acquire specific knowledge about neurophysiology and neuroanatomy, learn the fundamental concepts of multi-channel EEG analysis, and acquire hands-on skills in recording EEG data and using EEGLAB, an open-source software toolbox for advanced EEG analysis. Part 1: Neurophysiology and neuroanatomy (lecture): winter Neurophysiology, EEG, EMG, ECG Neuroanatomy Time-domain and frequency-domain analysis methods Part 2: EEG recording and analysis (hands-on seminar): winter In small groups under supervision of the lecturer, all students will record EEG data of their fellow students and will serve as participants for their classmates. We cannot guarantee same-gender groups. Recording and analysis of biomedical signals Averaging, filtering, signal-to-noise Topographical EEG analysis Part 3: EEG analysis with Matlab (hands-on seminar): summer EEGLAB file I/O, data structure and scripting Preprocessing, artefact rejection and artefact correction Statistical decomposition Event-related potentials, topographical mapping and power spectra Illustration of results Literatur
Recommended reading	Kandel et al. (2000). Principles of Neural Science, McGraw-Hill Luck, S.J. (2005). An Introduction to the ERP Technique, The MIT Press Van Drongelen, W. (2006). Signal Processing for Neuroscientists, Academic Press
Links
Language of instruction	English
Duration (semesters)	2 Semester
Module frequency	The module will start every winter term.
Module capacity	18 ( The lecture is not restricted. )
Reference text	PLEASE NOTE: We strongly recommend to take either psy170, psy270, psy280, psy220 or psy290 to gain methodological competencies (EEG, fMRI, TBS, HCI, ambulatory assessment techniques) that are needed for most practical projects and Master's theses!
Type of module	Wahlpflicht / Elective
Module level	MM (Mastermodul / Master module)
Teaching/Learning method	Part 1: lecture; Part 2 and 3: seminars

Type of course	Comment	SWS	Frequency	Workload of compulsory attendance
Lecture	2 semester hours per week in first half of the winter term.	1	WiSe	14
Seminar	2 semester hours per week in second half of the winter term. 2 semester hours per week in summer term.	3	SuSe and WiSe	42
Total module attendance time				56 h

Examination	Prüfungszeiten	Type of examination
Final exam of module	exam period at the end of the summer term	The module will be tested with a written exam of 2 h duration. Required active participation for gaining credits: recording of electroencephalographic data of fellow students and serving as participant for classmates attendance of at least 70% in each seminar within one semester (will be checked in StudIP).