EEG intentions recognition in dynamic complex object control task by functional brain networks and regularized discriminant analysis

Fu, Rongrong; Wang, Han; Bao, Tiantian; Han, Mengmeng

doi:10.1016/j.bspc.2020.101998

Cited by 13 publications

(2 citation statements)

References 40 publications

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“…Unlike previous research, we proposed the characteristics of the event-related functional coupling change rate based on WPLI to describe the significant changes of brain connectivity during aiming. Then, we employed graph theory to analyze the brain network based on WPLI through exploration of the global and local topologies of the network analyzed in subjects when performing archery aiming tasks (Fu et al, 2020) and the neural characteristics correlated with archery performance to better understand the changing EEG characteristics of professional archers during the archery preparation process (Wang et al, 2010). In this study, it was assumed that there were significant differences in EEG functional coupling characteristics and brain network topologies between elite and expert archers in the archery preparation stage, and there was also a significantly close relationship between these brain network characteristics and the archery performance.…”

Section: Introductionmentioning

confidence: 99%

From Expert to Elite? — Research on Top Archer’s EEG Network Topology

Gong

et al. 2022

Front. Hum. Neurosci.

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It is not only difficult to be a sports expert but also difficult to grow from a sports expert to a sports elite. Professional athletes are often concerned about the differences between an expert and an elite and how to eventually become an elite athlete. To explore the differences in brain neural mechanism between experts and elites in the process of motor behavior and reveal the internal connection between motor performance and brain activity, we collected and analyzed the electroencephalography (EEG) findings of 14 national archers and 14 provincial archers during aiming and resting states and constructed the EEG brain network of the two archer groups based on weighted phase lag index; the graph theory was used to analyze and compare the network characteristics via local network and global network topologies. The results showed that compared with the expert archers, the elite archers had stronger functional coupling in beta1 and beta2 bands, and the difference was evident in the frontal and central regions; in terms of global characteristics of brain network topology, the average clustering coefficient and global efficiency of elite archers were significantly higher than that of expert archers, and the eigenvector centrality of expert archers was higher; for local characteristics, elite archers had higher local efficient; and the brain network characteristics of expert archers showed a strong correlation with archery performance. This suggests that compared with expert archers, elite archers showed stronger functional coupling, higher integration efficiency of global and local information, and more independent performance in the archery process. These findings reveal the differences in brain electrical network topologies between elite and expert archers in the archery preparation stage, which is expected to provide theoretical reference for further training and promotion of professional athletes.

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Section: Introductionmentioning

confidence: 99%

From Expert to Elite? — Research on Top Archer’s EEG Network Topology

Gong

et al. 2022

Front. Hum. Neurosci.

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“…With the development of complex network research [20]- [22], many researchers have applied the basic theory of complex network and corresponding analytical methods to the study of human brain [23]. At present, the study on the neural mechanism of human brain structure and function is no longer limited to the localization of brain function [24], but more on the analysis of structure, connection, and dynamic behavior of different hierarchical networks [25].…”

Section: Introductionmentioning

confidence: 99%

Effects of tDCS on Brain Functional Network of Patients After Stroke

Wang

Liu

et al. 2020

IEEE Access

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Transcranial direct current stimulation (tDCS) is an emerging brain intervention technique. However, the effects of tDCS on stroke patients are unclear. In this study, Granger Causality (GC) is used to construct brain functional networks of the tDCS group (9 cases) and the sham tDCS group (11 cases). Some parameters of brain functional networks are analyzed comparatively, such as degree, clustering coefficient, betweenness centrality, characteristic path length, and efficiency. In tDCS group, the results show that the distribution of degree changes greatly in left prefrontal lobe and left temporal lobe regions, the distribution of betweenness centrality transfers, characteristic path length decreases, clustering coefficient and efficiency increase significantly (p < 0.05) after stimulation. However, there is no significant difference in sham tDCS group. In this study, the positive effects of tDCS on the therapeutic of stroke are clarified and the evidence for the effects of tDCS on stroke is provided.INDEX TERMS Transcranial direct current stimulation (tDCS), brain functional network, stroke, electroencephalogram (EEG).

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Recognizing single-trial motor imagery EEG based on interpretable clustering method

Chen

et al. 2021

Biomedical Signal Processing and Control

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EEG intentions recognition in dynamic complex object control task by functional brain networks and regularized discriminant analysis

Cited by 13 publications

References 40 publications

From Expert to Elite? — Research on Top Archer’s EEG Network Topology

From Expert to Elite? — Research on Top Archer’s EEG Network Topology

Effects of tDCS on Brain Functional Network of Patients After Stroke

Recognizing single-trial motor imagery EEG based on interpretable clustering method

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