Effective Connectivity in the Brain – An analysis on MEG data using causal discovery

dc.contributor.advisor	Hinne, M.
dc.contributor.advisor	Gerven, M.A.J. van
dc.contributor.author	Gugten, R.P. van der
dc.date.issued	2014-08-25
dc.description.abstract	Neuroimaging techniques have led to an increase of our knowledge of the brain, in particular with regard to connectivity between different brain regions. This study investigates how causal discovery is used for finding effective connectivity in task based MEG data. The PC (Peter-Clark) algorithm operates under the correctness of causal discovery and tests on simulated data show that it is feasible for finding effective connectivity on large sparse graphs. Data of two different tasks have been analysed for connectivity using the PC algorithm, a presented visual stimulus and the remembering of that visual stimulus. This study shows that differences in connectivity are found between the tasks, showing distinct different patterns.	en_US
dc.identifier.uri	http://theses.ubn.ru.nl/handle/123456789/152
dc.language.iso	en	en_US
dc.thesis.faculty	Faculteit der Sociale Wetenschappen	en_US
dc.thesis.specialisation	Bachelor Artificial Intelligence	en_US
dc.thesis.studyprogramme	Artificial Intelligence	en_US
dc.thesis.type	Bachelor	en_US
dc.title	Effective Connectivity in the Brain – An analysis on MEG data using causal discovery	en_US

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