A novel method for tracking and analysis of EEG activation across brain lobes. (February 2018) - Lim, Seng Hooi; Nisar, Humaira; Thee, Kang Wei; Yap, Vooi Voon
Graphical abstract: Highlights: We have considered computer vision based Horn and Schunck optical flow estimation method to generate motion field for EEG topo-maps. We have developed an algorithm to track the activation across brain lobes for different visual oddball tasks. It is observed that for different Oddball tasks, our method is able to differentiate the pattern of average activation across different brain lobes. High activation has been observed in the frontal lobe for target with response case. Abstract: Electroencephalography (EEG) measures the electrical activity of brain that is generated by the synchronized activity of thousands of neurons. In this paper, our first goal is to develop a novel method totrack the EEG activation in different brain regions involved in the processing of target and non-target stimuli in oddball paradigm. Secondly we want to identify the difference in the pattern of activation for different oddball tasks. The EEG data has been acquired from twenty healthy volunteers for the visual oddball experiment. In the task two types of visual stimuli target (rare) and non-target (frequent) were randomly presented. The subjects were instructed to press the enter button when they identify the target stimuli. The EEG data acquired is converted into EEG topo-maps. In our method the flow of activation between consecutive topo-maps is estimated by using Horn and Schunck Optical Flow estimation method. It helps to generate the motion field between consecutive topo-maps which is considered as flow of activation between two time frames. Different motion vectors are clustered into a group based on the activation level. These clusters are tracked between different frames as a measure of the activation flow. Finally we analyze the flow of activation across different brain lobes for different cases encountered in the Oddball paradigm by plotting average activation graph with respect to time.Analysis of the data has revealed that high activation has been observed in the Frontal and Occipital lobes in general for the oddball task. Frontal lobe shows high activation for target with response case, this is followed by the Occipital lobe. The activation in frontal lobe starts increasing from frame no 60 (240 ms) (out of 125 frames). Occipital lobe shows high activation for target with no response and no target no response cases in the region from 40 to 60 frames. Parietal lobe shows high activation for target with response near the end of task from frame no. 100 onwards. Hence, we have been able to identify different patterns in the activation flow that differentiates different Oddball tasks. This activation pattern is consistent with the event related potential signal generated by the Oddball paradigm. The pattern for the individual subjects also follow the average pattern of high activation in the frontal and occipital region for target and non target stimuli. We have also used cross correlation (a classical connectivity method) for comparison of the results. A subjective comparison of the results show that our proposed method is capable of tracking the EEG activation.