Quantification of brain hemispheric differences with functional magnetic resonance imaging

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http://urn.fi/URN:NBN:fi-fe201804208615
Title: Quantification of brain hemispheric differences with functional magnetic resonance imaging
Author: Nousiainen, Katri
Contributor: University of Helsinki, Faculty of Science, Department of Physics
Publisher: Helsingin yliopisto
Date: 2018
Language: eng
URI: http://urn.fi/URN:NBN:fi-fe201804208615
http://hdl.handle.net/10138/273572
Thesis level: master's thesis
Discipline: Physics
Fysiikka
Fysik
Abstract: The human brain is divided into left and right hemisphere, and there are functional differences between the hemispheres. A hemispheric difference is called the lateralization of the brain function, and the degree of lateralization is described by the laterality index. The most investigated domain of the lateralized brain functions is language, which is a left hemisphere dominant function in the majority of the population. Functional magnetic resonance imaging provides a noninvasive method for studying the brain functions indirectly through the bloodoxygenation-level-dependent effect. The language-related functional magnetic resonance imaging can be used in the localization of the Broca’s speech area and determination of the dominant hemisphere in epileptic patients. The purpose of this thesis is to assess a method for calculating the laterality index from functional magnetic resonance imaging data. The data is acquired during three language task paradigms with five subjects and analyzed statistically. The methods used for the laterality index calculations are reviewed, and a new calculation method is presented. Result tables of laterality indices and hemispheric dominances per used regions of interest are generated. The presented laterality index calculation method successfully determined the speech laterality of three subjects out of five as a left hemispheric dominance. The language laterality of two subjects was not successful due to corrupted functional data and contradicted results between different paradigms. The major source of error is the subject’s head motion during the functional imaging. Together with the information about the head motion’s extent, the generated table could provide relevant extra information to epileptic patients’ functional magnetic resonance imaging data and could serve for clinical purposes in the future.


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