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Christine Steinseifer-Jeske
Coordination

Oili Tsakmakis
Administration

Room W3 1-138

Phone.: +49 (0)441 - 798 3648/49

Contact options:
via e-mail and via phone form Mon-Thur 09:00-12:00

New: Online office hour on thursdays from 10:00-11:00, by appointment

Neurophysiological Imaging and Data Analysis - Complex network analyses of fMRI data

OLTECH OLTECH PhD study programme Neurosensory Science & Systems PhD study programme Interface Science PhD study programme Environmental Sciences and Biodiversity PhD programme Renewable Energy PhD programme Medicine and Health Sciences PhD programme Mathematics and Fundamental Physics

Online Workshop with Dr. Carsten Gießing

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.

A headset and a computer with the softare MATLAB is also required. Participants have to register via Stud.IP. Please register at least one week before the beginning of the course in order to receive further instructions by email.

Registration: Stud.IP

Registration deadline: 28.09.2020

Participants: max. 12

Credit Points: 3 KP

Modules: olt203, olt705

Times:

Mon, 05.10.2020 09:00 - 14:00
Tue, 06.10.2020 09:00 - 14:00
Wed, 07.10.2020 09:00 - 14:00

Start Time

05. October 2020, 09:00 – End date: 07. October 2020, 14:00

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