Winter Semester 2013-2014: Doing by Thinking


Proseminar: Introduction to the Functional Decoding of Brain Signals

Student Topic Supervisor Files
Oliver Vogt - Lukas Klein A first glance on Brain-Computer Interfaces (BCI) / Brain-Machine Interfaces (BMI) MT Slides Report
Moritz Freidank - Anja Blickensdörfer Neuroanatomical background of BCI/BMI. TB Slides Report
Benedikt Solf Signals for BCIs: Where do they come from, how do they look like? Part A: non-invasive signals (EEG/MEG/fMRI/fNIRS) TB Slides Report
Eva Brombacher - Hendrik Intveen Signals for BCIs: Where do they come from, how do they look like? Part B: (semi-) invasive signals (ECoG, SUA, LFP) TB Slides Report
Rick Gelhausen - Samuel Steinegger Signal processing and machine learning algorithms to decode evoked potentials of the EEG/ECoG. MT Slides Report
Jan Reisacher - Björn Hagemeister How to learn BMI control. TB Slides Report
Andre Biedenkapp - Julian Kunzelmann BCI-controlled robots: principles and applications WB Slides Report

Seminar: Invasive and Non-Invasive Methods to Decode Brain Signals in Realtime

Student Topic Supervisor Files
Gregor Enzian Data-driven spatial filtering to improve signal-to-noise ratio in evoked responses. MT Slides Report
Ingo Killmann Listen to write: auditory BCI for communication. MT Slides Report
Cem Uran - Tiago M. Rocha Félix Neurotechnology to restore memory and other cognitive functions. TB Slides Report
Maximilian Bergmann Unsupervised Classification of ERP paradigms MT Slides Report
Robin Tibor Schirrmeister Controlling robotic arms for self-feeding with the help of BMIs TB Slides Report

Albert-Ludwigs-Universität Freiburg
Brain State Decoding Lab
Albertstraße 23, 79104
Freiburg im Breisgau

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