The topic is centered around an experimental paradigm where the subject has to solve an „invisible maze” game via limb movements. The „maze” consists of a camera connected to a computer, and peripherals providing auditory and visual stimuli. The camera records the position of the head in almost real time and compares it to a map and sends sound and/or visual feedback based on the relationship of the actual hand position and the map. To solve the maze game, the subject has to learn a given sequence of movements.
The wavelet transform coherence (WTC) is a powerful tool to directly compare EEG and motion tracking data in a broad frequency range and longer time windows. This technique is a promising method to explore the micro-structure of movement learning.

Tasks of the student:

- Understanding of the currently used measurement configuration to record motion capture, EEG, audio, and video in parallel.

- Review of the literature of basic EEG pre-processing methods.

- Analysis of EEG and motion tracking data.