Electroencephalography (EEG) signal is generated by electrical activity of human brain. EEG topographic maps (topomap) give an idea of the brain activation. Brain Mapping may be used to relate the connectivity and functionality of the brain through imaging. Brain functional connectivity helps to find functionally integrated relationship between spatially separated brain regions. Brain connectivity can be measured by several methods. The classical methods calculate the coherence and correlation of the signal. Brain connectivity can also be measured by using nonlinear methods like mutual information, generalized synchronization and phase synchronization. In this paper, we have developed an algorithm to map neural connectivity in brain by using full search block matching motion estimation algorithm. We have examined the behavior of human brain throughout a specific activity using Oddball Paradigm. In the first step the EEG signal is converted into topomaps. The activation between consecutive frames is tracked using motion vectors. Vector median filtering is used to obtain a smooth motion field by removing unwanted noise. In each activation several paths between brain lobes have been tracked.
['Lim Seng Hooi', 'Humaira Nisar', 'Yap Vooi Voon']
Tracking of EEG activity using topographic maps