University of Twente Student Theses


Mathematical modeling to better understand the dynamics of epilepsy

Jonkheer, M.F. (2016) Mathematical modeling to better understand the dynamics of epilepsy.

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Abstract:Recently a lot of research has been conducted to increase the understanding of the brain dynamics, particularly regarding abnormal behavior. One of the most common neurological disorders is epilepsy and is therefore an important research topic. However, so far this disorder has only been theoretically characterized as being associated with abnormal synchronization between brain regions. Therefore Schmidt et al. (2014) tested a new method for analyzing this synchronization. For this they used the Kuramoto model. This model is said to be a good way of modeling the brain dynamics associated with epilepsy. Using this model they found markers to distinguish between healthy subjects and epilepsy patients using rest- EEGs. This research was conducted to confirm their findings. This study has indeed found a reduction in the critical coupling strength required to synchronize the global network in the low-alpha (6-9 Hz) band. However, their other findings could not be confirmed. Furthermore in this research, thresholds were established for distinguishing between healthy subjects and epilepsy patients. Together these findings demonstrate that this model could be used to provide significant additional information from rest-EEGs. This could ultimately lead to a better tool for identifying people with epilepsy leading to improved diagnostics and therapeutics.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:31 mathematics
Programme:Science Education and Communication MSc (60708)
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