The G-Node Course on Neural Data Analysis offers hands-on experience in state-of-the-art methods for analyzing complex neural data to PhD students and postdocs. Participants may have a theoretical background with interest in analyzing biological data, or they may come from an experimental background, interested in new ways of analyzing their data.
Applicants should have an elementary understanding of linear algebra and statistics, as well as basic programming knowledge in either Matlab or Python. Most analysis tools will have to be programmed by the individual participant, under the guidance of tutors. Participants should show interest in model-driven analyses and be open to theoretical approaches to data analysis. Likewise, they should be interested in the practical analysis of real biological data.
· Spectral analysis · Mutual information · Machine learning · Neural tuning and decoding · Signal Detection Theory · Multi-Channel Recording Analysis · Population Dynamics · Synchronization · Noise ·
Please send your application with the following material as a single pdf file to email@example.com:
There will be a non-refundable participation fee of 50 Euros, payable immediately after notification of acceptance.
Credits (2 ECTS) are granted to PhD students where applicable. Acceptance of credits is subject to the rules of the respective graduate program.
Deadline: May 15, 2017
Early application is encouraged because number of participants is limited
Jan Grewe, Eberhard-Karls-Universität Tübingen
Fabian Sinz · Baylor College of Medicine, Houston
Monika Volk, LMU München
German Neuroinformatics Node (G-Node)
Großhaderner Str. 2
Course Room C 00.005
Download map and directions [pdf]
The German Neuroinformatics Node receives funding from the Bundesministerium für Bildung und Forschung (BMBF)