Understanding the Influences of EEG Reference: A Large-Scale Brain Network Perspective

理解脑电图参考的影响:基于大规模脑网络的视角

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Abstract

The influence of reference is a critical issue for the electroencephalography (EEG) and event-related potentials (ERPs) studies. However, previous investigations concentrated less on the location of source at a systematic neuroscience level. Our goal was to examine the EEG signal associated with the locations from a common network parcellation of the human brain function, offering a system perspective of the influence of EEG reference. In our simulation, vertices uniformly distributed in eight large-scale brain networks were adopted to generate the scalp EEG. The brain networks contain the visual, somatomotor, dorsal attention, ventral attention, limbic, frontoparietal, default networks, and the deep brain structure. The distributions of the most sensitive and neutral electrodes were calculated for each network based on the lead-field matrix. While the most sensitive electrode had a network-specific symmetric pattern, the electrodes in scalp surface had approximately equal chance to be the most neutral electrode. Simulated data were referenced at the FCz, the Oz, the mean mastoids (MM), the average (AVE), and the infinity reference obtained by the reference electrode standardization technique (REST). Intriguingly, the relative error followed the pattern REST

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