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Prediction of SSVEP-based BCI performance by the resting-state EEG network.
ISSN号:1741-2552
期刊名称:J Neural Eng
时间:2013.12
页码:066017-066017
相关项目:基于多模态分析方法的脑机接口运动想象盲神经机制研究
作者:
Zhang, Yangsong|Xu, Peng|Guo, Daqing|Yao, Dezhong|
同期刊论文项目
基于多模态分析方法的脑机接口运动想象盲神经机制研究
期刊论文 44
会议论文 2
同项目期刊论文
Multiple Frequencies Sequential Coding For SSVEP-based Brain-Computer Interface
Altered brain connectivity in patients with psychogenic non - epileptic seizures : A scalp electroen
Z-score linear discriminant analysis for EEG based brain-computer interfaces.
The enhanced information flow from visual cortex to frontal area facilitates SSVEP response: evidenc
Why do we need to use a zero reference? Reference influences on the ERPs of audiovisual effects.
A PRELIMINARY STUDY ON RECOGNIZING PSYCHOGENIC NONEPILEPTIC SEIZURES BASED ON SCALP RESTING EEG
An Efficient Frequency Recognition Method Based on Likelihood Ratio Test for SSVEP-Based BCI
Autoregressive model in the Lp norm space for EEG analysis
基于AdaBoost的脑机接口分类算法研究
Cortical network properties revealed by SSVEP in anesthetized rats.
L1 Norm based common spatial patterns decomposition for scalp EEG BCI
Predicting Inter-session Performance of SMR-Based Brain-Computer Interface Using the Spectral Entrop
An Adaptive Motion-Onset VEP-Based Brain-Computer Interface
Simultaneous EEG-fMRI: Trial level spatio-temporal fusion for hierarchically reliable information di
Differentiating Between Psychogenic Nonepileptic Seizures and Epilepsy Based on Common Spatial Patte
The Time-varying networksin P300: a task-evoked EEG study
A Method to remove MRI Artifact from Continuous EEG based on the combination of FASTR and ARX
The graph theoretical analysis of the SSVEP harmonicresponse networks
Relationships between the resting-state network and the P3: Evidence from a scalp EEG study.
基于静息态脑电的心因性非癫痫性发作患者脑功能网络分析及分类识别研究
基于运动想象的脑机接口关键技术研究
Enhanced Z-LDA for Small Sample Size Training in Brain-Computer Interface Systems.
L1 norm based common spatial patterns decomposition for scalp EEG BCI.
Using particle swarm to select frequency band and time interval for feature extraction of EEG based
Attentional orienting and response inhibition: insights from spatial-temporal neuroimaging.