General information

Course name	Practical training: 6.02.141_3 Neurophysiological Imaging and Data Analysis
Subtitle	Complex network analyses of fMRI data
Course number	6.02.141_3
Semester	WiSe22/23
Current number of participants	6
expected number of participants	12
Home institute	Department of Psychology
Associated institutions	Graduate School Science, Medicine and Technology (Oltech)
Courses type	Practical training in category Teaching
First date	Wednesday, 05.10.22, 09:15 - 17:45 o'clock A07 0-031
Type/Form	PhD Student Course, Minor for Neurocognitive Psychology
Pre-requisites	Profound knowledge in programming (MATLAB, C, r-statistics, or comparable languages)
Lehrsprache	englisch
ECTS points	3

Lecturers

Dr. rer. nat. Carsten Gießing

Rooms and times

A07 0-031

Wednesday, 05.10.22, 09:15 - 17:45 o'clock
Thursday, 06.10.22, 09:15 - 17:45 o'clock
Monday, 10.10.22, 09:15 - 17:45 o'clock

Fields of study

Campusmanagementsystem Stud.IP
- Fakultät VI - Medizin und Gesundheitswissenschaften
  - Weitere Veranstaltungen: Psychologie
    - Neurocognitive Psychology
- Interdisziplinäre Lehreinrichtungen
  - PhD Programmes
    - Graduate School Science, Medicine and Technology
      - Interdisziplinäre Veranstaltungen / Interdisciplinary courses
    - Medicine and Health Sciences
      - Verbreiterung und Vertiefung von Fachwissen
        
        olt703 - Clinical Epidemiology and Biometry
        
        olt705 - Research methods and techniques

Module assignments

Campusmanagementsystem Stud.IP
- Neurosensory Science and Systems - Structured Doctoral Programme
  - Module
    - olt203 - Special techniques in Neurosensory Science and Systems
      - VA-Auswahl
- Neurocognitive Psychology - Master's Programme
  - General Part
    - psy141 - Minor
      - VA-Auswahl

Comment/Description

presence

The course takes place as classroom teaching. If this is not possible, as online lessons. Students are asked to bring their own computer with MATLAB installed.

During last years there has been a growing interest in analysing the human brain as a complex system of interconnected processing nodes. Such analyses have provided important new insights into the correlation between the organization, dynamics and functions of brain networks and human behaviour. During the course an introduction will be given how to analyse an fMRI data as complex network using graph theory. The course will focus on the analysis of ‘fMRI’ data which need specific analysis approaches to deal with the requirements inherent to the quality of the measured data.

Literature: Bullmore, E., Sporns, O., 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10, 186-198.

Profound knowledge in programming (MATLAB, C, r-statistics, or comparable languages) is required.

Admission settings

The course is part of admission "Anmeldung gesperrt (global)".

Erzeugt durch den Stud.IP-Support
The following rules apply for the admission:

Admission locked.

Practical training: 6.02.141_3 Neurophysiological Imaging and Data Analysis - Details

A07 0-031