Attention modulations of posterior alpha as a control signal for two-dimensional brain-computer interfaces
Attention modulations of posterior alpha as a control signal for two-dimensional brain-computer interfaces
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DOI：
10.1016/j.jneumeth.2009.01.016
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发表时间：
2009-04-30
影响因子：
3
通讯作者：
Jensen, Ole
中科院分区：
文献类型：
--
作者：
van Gerven, Marcel;Jensen, Ole
脑机接口（BCI）的研究正引起人们的浓厚兴趣。这是因为BCI适用于帮助残疾人，游戏，以及作为认知神经科学的工具。通常，运动想象用于产生（二进制）控制信号。然而，找到允许区分多个类别的其他类型的控制信号将有助于增加BCI的适用性。我们已经调查，如果调制后α活动的手段，在两个维度的隐蔽空间注意可以可靠地分类在单次试验。脑磁图（MEG）的数据收集了15名受试者谁从事的任务，他们偷偷地参加了视觉左，右，上或下在一段时间内的2500毫秒。然后，我们使用支持向量机分类的试验。四个方向的内隐注意可以可靠地分类到最高69%的正确分类试验（25%的机会水平），而不需要冗长和繁重的主题培训。低α信号解释了一些受试者的低分类性能。这些研究结果支持的情况下，调制α活动通过隐蔽的空间注意力是有前途的;一个二维BCI的控制信号。(C)2009 Elsevier B. V.保留所有权利。
Research on brain-computer interfaces (BCIs) is gaining strong interest. This is motivated by BCIs being applicable for helping disabled, for gaming, and as a tool in cognitive neuroscience. Often, motor imagery is used to produce (binary) control signals. However, finding other types of control signals that allow the discrimination of multiple classes would help to increase the applicability of BCIs. We have investigated if modulation of posterior alpha activity by means of covert spatial attention in two dimensions can be reliably classified in single trials. Magnetoencephalography (MEG) data were collected for 15 subjects who were engaged in a task where they covertly had to visually attend left, right, up or down during a period of 2500 ms. We then classified the trials using support vector machines. The four orientations of covert attention could be reliably classified up to a maximum of 69% correctly classified trials (25% chance level) without the need for lengthy and burdensome subject training. Low classification performance in some subjects was explained by a low alpha signal. These findings support the case that modulation of alpha activity by means of covert spatial attention is promising as; a control signal for a two-dimensional BCI. (C) 2009 Elsevier B.V. All rights reserved.