Prediction of SSVEP-based BCI performance by the resting-state EEG network.
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Combining Partial Directed Coherence and Graph Theory to Analyse Effective Brain Networks of Different Mental TasksThe enhanced information flow from visual cortex to frontal area facilitates SSVEP response: evidence from model-driven and data-driven causality analysis.Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity.The graph theoretical analysis of the SSVEP harmonic response networks.Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.Periodic Visual Stimulation Induces Resting-State Brain Network Reconfiguration.Heading for new shores! Overcoming pitfalls in BCI design.
P2860
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P2860
Prediction of SSVEP-based BCI performance by the resting-state EEG network.
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name
Prediction of SSVEP-based BCI performance by the resting-state EEG network.
@en
Prediction of SSVEP-based BCI performance by the resting-state EEG network.
@nl
type
label
Prediction of SSVEP-based BCI performance by the resting-state EEG network.
@en
Prediction of SSVEP-based BCI performance by the resting-state EEG network.
@nl
prefLabel
Prediction of SSVEP-based BCI performance by the resting-state EEG network.
@en
Prediction of SSVEP-based BCI performance by the resting-state EEG network.
@nl
P2093
P356
P1476
Prediction of SSVEP-based BCI performance by the resting-state EEG network
@en
P2093
P304
P356
10.1088/1741-2560/10/6/066017
P577
2013-11-27T00:00:00Z