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利用瞬态视觉诱发电位信号的时间模式:一种对脑机接口有影响的统计单试验方法。

Exploiting the temporal patterning of transient VEP signals: a statistical single-trial methodology with implications to brain-computer interfaces (BCIs).

作者信息

Liparas D, Dimitriadis S I, Laskaris N A, Tzelepi A, Charalambous K, Angelis L

机构信息

Department of Informatics, Aristotle University of Thessaloniki, Greece.

AIIA Laboratory, Department of Informatics, Aristotle University of Thessaloniki, Greece.

出版信息

J Neurosci Methods. 2014 Jul 30;232:189-98. doi: 10.1016/j.jneumeth.2014.04.032. Epub 2014 May 29.

Abstract

BACKGROUND

When visual evoked potentials (VEPs) are deployed in brain-computer interfaces (BCIs), the emphasis is put on stimulus design. In the case of transient VEPs (TVEPs) brain responses are never treated individually, i.e. on a single-trial (ST) basis, due to their poor signal quality. Therefore their main characteristic, which is the emergence during early latencies, remains unexplored.

NEW METHOD

Following a pattern-analytic methodology, we investigated the possibility of using single-trial TVEP responses to differentiate between the different spatial locations where a particular visual stimulus appeared and decide whether it was attended or unattended by the subject.

RESULTS

Covert spatial attention modulates the temporal patterning of TVEPs in such a way that a brief ST-segment, from a single synthesized sensor, is sufficient for a Mahalanobis-Taguchi (MT) system to decode subject's intention.

COMPARISON WITH EXISTING METHOD(S): In contrast to previous VEP-based approaches, stimulus-related information and user's intention are being decoded from transient ST-signals via exploiting aspects of brain response in the temporal domain.

CONCLUSIONS

We demonstrated that in the TVEP signals there is sufficient discriminative information, coming in the form of a temporal code. We were able to introduce an efficient scheme that can fully exploit this information for the benefit of online classification. The measured performance brings high expectations for incorporating these ideas in BCI-control.

摘要

背景

当视觉诱发电位(VEP)应用于脑机接口(BCI)时,重点在于刺激设计。对于瞬态VEP(TVEP),由于其信号质量较差,大脑反应从未在个体层面,即单试次(ST)基础上进行处理。因此,其主要特征,即在早期潜伏期出现的情况,仍未得到探索。

新方法

遵循模式分析方法,我们研究了使用单试次TVEP反应来区分特定视觉刺激出现的不同空间位置,并确定受试者是否注意到该刺激的可能性。

结果

隐蔽空间注意以这样一种方式调节TVEP的时间模式,即来自单个合成传感器的一段短暂的ST段足以让马氏田口(MT)系统解码受试者的意图。

与现有方法的比较

与以前基于VEP的方法不同,刺激相关信息和用户意图是通过利用时域中大脑反应的各个方面从瞬态ST信号中解码出来的。

结论

我们证明了在TVEP信号中存在足够的判别信息,其形式为时间编码。我们能够引入一种有效的方案,该方案可以充分利用这些信息以利于在线分类。所测得的性能为将这些想法纳入BCI控制带来了很高的期望。

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