Thesis topic proposal
György Kozmann
Advanced EEG imaging and data processing


Institute: University of Pannonia
computer sciences
Doctoral School of Information Science and Technology

Thesis supervisor: György Kozmann
co-supervisor: Zoltán Juhász
Location of studies (in Hungarian): University of Pannonia ,H-8200 Veszprém Egyetem u. 10.
Abbreviation of location of studies: PE

Description of the research topic:

EEG measures the electrical activity of our brain using scalp electrodes with sub millisecond temporal resolution, for which it is the most popular tool in investigating task execution in the brain. Traditional imaging devices have a much lower time resolution. Recent advances in technology allow the use of very high number of electrodes (128 or 256) which increase the spatial resolution of EEG making it suitable for creating images of the dynamics of our neural system. There are several challenges to be solved in order to create such systems. Signals need extensive cleaning to remove unwanted artefacts, perform spatio-temporal analysis on the datasets and perform classification to find characteristic features, just to name a few. The goal of the project is to advance our knowledge by developing new methods and algorithms for a selected sets of problems related to EEG imaging.

Preliminary results can be found in the following publications:

1. Michel, C.M. and Murray, M.M., 2012. Towards the utilization of EEG as a brain imaging tool. Neuroimage, 61(2), pp.371-385.
2. Nunez, P. L., R. B. Silberstein, P. J. Cadusch, R. S. Wijesinghe, A. F. Westdorp, and R. Srinivasan. "A theoretical and experimental study of high resolution EEG based on surface Laplacians and cortical imaging." Electroencephalography and clinical neurophysiology 90, no. 1 (1994): 40-57.

Further requirements: 
Besides a solid foundation in computer science, the applicant should be fluent in English, and have a strong knowledge of advanced mathematics, physics, signal processing methods as well as an interest in biology and neuroscience.

Number of students who can be accepted: 1

Deadline for application: 2020-02-28

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