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

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

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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 8
expected number of participants 12
Home institute Department of Psychology
participating institutes Graduate School Science, Medicine and Technology (Oltech)
Courses type Practical training in category Teaching
First date Wednesday, 05.10.2022 09:15 - 17:45, Room: 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

Rooms and times

A07 0-031
Wednesday, 05.10.2022 - Thursday, 06.10.2022, Monday, 10.10.2022 09:15 - 17:45

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.