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多模态成像和BCI
Multimodal Imaging and BCI |
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| 课程网址: |
http://videolectures.net/bbci2012_mueller_multimodal_imaging/
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| 主讲教师: |
Klaus-Robert Müller
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| 开课单位: |
柏林科技大学
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| 开课时间: |
2012-12-03
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| 课程语种: |
英语
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| 中文简介: |
每一种脑活动成像方法都有技术或生理上的限制。因此，可以减轻这些限制的神经成像方式的组合，如同时记录神经生理和血流动力学活动，已经变得越来越流行。多模态成像装置可以利用对神经活动的互补观点，增强我们对神经信息处理如何在每种模态中反映的理解。然而，需要专门的分析方法来挖掘多模态方法的潜力。本讲座将首先从机器学习的角度对多模态数据融合问题进行探讨，并介绍一些有用的算法。然后，我将讨论一种结合脑电图(EEG)和近红外光谱(NIRS)的混合非侵入式脑计算机接口(BCI)。特别地，我将展示近红外光谱(NIRS)可以用来增强eg - bci方法。在我们的研究中，这两种方法同时应用于基于实时感觉运动节律(SMR)的BCI范式，包括执行动作和运动图像。我们测试了NIRS数据的分类如何补充正在进行的实时脑电图分类。结果表明，同时测量NIRS和EEG可以显著提高90%以上被试的运动图像分类准确率，平均提高5%的性能。然而，血流动力学反应的长时间延迟可能会阻碍比特率的整体提高。此外，我们发现脑电图和近红外成像在信息内容上是互补的，因此是一种可行的多模态成像技术，适合于BCI。
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| 课程简介: |
Each method for imaging brain activity has technical or physiological limits. Thus, combinations of neuroimaging modalities that can alleviate these limitations such as simultaneous recordings of neurophysiological and hemodynamic activity have become increasingly popular. Multimodal imaging setups can take advantage of complementary views on neural activity and enhance our understanding about how neural information processing is reflected in each modality. However, dedicated analysis methods are needed to exploit the potential of multimodal methods. The talk will first spend some time on the multimodal data fusion problem from the Machine Learning point of view and introduce useful algorithms. Then I will discuss a hybrid noninvasive Brain Computer Interface (BCI) that combines electroencephalography (EEG) and near-infrared spectroscopy (NIRS). In particular I will show that near-infrared spectroscopy (NIRS) can be used to enhance the EEG-BCI approach. In our study both methods were applied simultaneously in a real-time Sensory Motor Rhythm (SMR)-based BCI paradigm, involving executed movements as well as motor imagery. We tested how the classification of NIRS data can complement ongoing real-time EEG classification. Our results show that simultaneous measurements of NIRS and EEG can significantly improve the classification accuracy of motor imagery in over 90% of considered subjects and increases performance by 5% on average. However, the long time delay of the hemodynamic response may hinder an overall increase of bit-rates. Furthermore we find that EEG and NIRS complement each other in terms of information content and are thus a viable multimodal imaging technique, suitable for BCI.
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| 关 键 词: |
神经影像学; 脑电图(EEG); 近红外光谱(NIRS); 脑计算机接口(BCI)
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| 课程来源: |
视频讲座网
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| 最后编审: |
2019-10-22：cwx
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| 阅读次数: |
76
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