Abstract
EEG recordings are widely used in epilepsy research. We intend to address a question whether small world network property exists in neural networks when epileptic seizures occur. In this paper, we introduce a bispectrum analysis to calculate the interaction between two EEG recordings; then, a suitable threshold is chosen to convert the interaction of the six channels at five frequency bands to a sparse graph (node: n=30, edge: k=4-7). Through analyzing a real EEG recording, it is found the clustering coefficient is similar to that of regular graph; however the path length is less than that of regular graph. Thus a primary suggestion can be made that neural networks possess small world network characteristic. During epileptic seizures, the small world property of neural network is more significant.
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