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用于检测和调制伽马波段活动的脑机接口。

A brain-computer-interface for the detection and modulation of gamma band activity.

机构信息

NeuroImage Nord, Department of Systems Neuroscience, University Medical Center Hamburg Eppendorf, Martinistrasse 52, D-20246 Hamburg, Germany.

出版信息

Brain Sci. 2013 Nov 18;3(4):1569-87. doi: 10.3390/brainsci3041569.

Abstract

Gamma band oscillations in the human brain (around 40 Hz) play a functional role in information processing, and a real-time assessment of gamma band activity could be used to evaluate the functional relevance more directly. Therefore, we developed a source based Brain-Computer-Interface (BCI) with an online detection of gamma band activity in a selective brain region in the visual cortex. The BCI incorporates modules for online detection of various artifacts (including microsaccades) and the artifacts were continuously fed back to the volunteer. We examined the efficiency of the source-based BCI for Neurofeedback training of gamma- and alpha-band (8-12 Hz) oscillations and compared the specificity for the spatial and frequency domain. Our results demonstrated that volunteers learned to selectively switch between modulating alpha- or gamma-band oscillations and benefited from online artifact information. The analyses revealed a high level of accuracy with respect to frequency and topography for the gamma-band modulations. Thus, the developed BCI can be used to manipulate the fast oscillatory activity with a high level of specificity. These selective modulations can be used to assess the relevance of fast neural oscillations for information processing in a more direct way, i.e., by the adaptive presentation of stimuli within well-described brain states.

摘要

人类大脑中的伽马波段振荡(约 40Hz)在信息处理中发挥着功能作用,实时评估伽马波段活动可以更直接地评估功能相关性。因此,我们开发了一种基于源的脑机接口(BCI),用于在线检测视觉皮层选择性脑区的伽马波段活动。该 BCI 结合了在线检测各种伪影(包括微扫视)的模块,并将伪影实时反馈给志愿者。我们检查了基于源的 BCI 用于神经反馈训练伽马和阿尔法波段(8-12Hz)振荡的效率,并比较了空间和频域的特异性。我们的结果表明,志愿者学会了选择性地在调节阿尔法或伽马波段振荡之间切换,并从在线伪影信息中受益。分析表明,对于伽马波段调制,在频率和地形上具有很高的准确性。因此,开发的 BCI 可用于以高度特异性操纵快速振荡活动。这些选择性调制可用于更直接地评估快速神经振荡对于信息处理的相关性,即通过在明确定义的大脑状态内自适应呈现刺激。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e25/4061891/3265419159c0/brainsci-03-01569-g001.jpg

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