Relationships between the resting-state network and the P3: Evidence from a scalp EEG study.

Fali Li,Fei Wang,Diankun Gong,Yi Jiang,Rui Zhang,Yin Tian,Daqing Guo,Dezhong Yao,He Li,Tiejun Liu,Peng Xu

doi:10.1038/srep15129

Abstract

The P3 is an important event-related potential that can be used to identify neural activity related to the cognitive processes of the human brain. However, the relationships, especially the functional correlations, between resting-state brain activity and the P3 have not been well established. In this study, we investigated the relationships between P3 properties (i.e., amplitude and latency) and resting-state brain networks. The results indicated that P3 amplitude was significantly correlated with resting-state network topology, and in general, larger P3 amplitudes could be evoked when the resting-state brain network was more efficient. However, no significant relationships were found for the corresponding P3 latency. Additionally, the long-range connections between the prefrontal/frontal and parietal/occipital brain regions, which represent the synchronous activity of these areas, were functionally related to the P3 parameters, especially P3 amplitude. The findings of the current study may help us better understand inter-subject variation in the P3, which may be instructive for clinical diagnosis, cognitive neuroscience studies, and potential subject selection for brain-computer interface applications.

Highlights

P3 amplitude and latency vary among subjects
Constructed networks containing these regions have been found to be correlated with higher-order cognitive processes, such as attention, intelligence, and working memory, and simultaneous interactions between these regions contribute to the P34,39
These existing studies converge to suggest that the P3 represents a complex summation of activity from the interaction of multiple brain regions, the association areas of the cerebral cortex[24,41]

Summary

Introduction

P3 amplitude and latency vary among subjects. An earlier report by Ou et al revealed that a larger P3 amplitude was acquired over different brain regions from poor navigators in driving tasks[12]. Network analysis has become an increasingly important part of the study of human brain function. The dynamic interactions of distributed brain areas in large-scale networks, rather than the isolated operations of these regions, greatly contribute to human cognition[23]. Studies of P3 topology have demonstrated the importance of various neural networks for the P324 These studies have mainly concentrated on task-related networks without considering the relationship between the resting-state network and the P3. The findings from three related experiments conducted by Polich, which concentrated on the relationship between EEG parameters (spectral power and mean frequency) and P3 properties, consistently demonstrated that scalp EEG variations significantly contributed to individual variations in the P335, the related resting-state network analysis has rarely been considered[34,36,37]. In the current study, we investigated the relationships between the resting-state network and the P3 to deepen our understanding of the P3

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Conclusion