Master’s thesis is aimed at familiarization with the principles of measurement and data processing functional magnetic resonance, focusing on the analysis of effective connectivity using dynamic causal modelling (DCM). The practical part includes three main thematic areas relating to the description of the processing and evaluation of measured or simulated data. First, there is on sample dataset described the neuroscientific SPM toolbox to analyze measured data. Then follows introduction of the proposed approach with which is investigated the behavior of the model estimation neural interactions with respect to the change of input parameters. This phenomenon is also simulated and on base of achieved results is recommended optimal approach to analyzing effective connectivity using dynamic causal modeling for the group of subjects. The last circuit in the practical part is assessment of shift the coordinates of brain areas on dynamic causal modelling results for the group of subjects from the data obtained from real measurements. Obtained results from simulated data and the results obtained from measured data are evaluated and discussed in the final part.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:220563 |
| Date | January 2014 |
| Creators | Veselá, Martina |
| Contributors | Harabiš, Vratislav, Lamoš, Martin |
| Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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