首页> 外文会议>Human vision and electronic imaging XV >Human Brain Imaging During Controlled and Natural Viewing
【24h】

Human Brain Imaging During Controlled and Natural Viewing

机译:在受控和自然观看过程中的人脑成像

获取原文
获取原文并翻译 | 示例

摘要

Assorted technologies such as; EEG, MEG, fMRI, BEM, MRI, TMS and BCI are being integrated to understand how human visual cortical areas interact during controlled laboratory and natural viewing conditions. Our focus is on the problem of separating signals from the spatially close early visual areas. The solution involves taking advantage of known functional anatomy to guide stimulus selection and employing principles of spatial and temporal response properties that simplify analysis. The method also unifies MEG and EEG recordings and provides a means for improving existing boundary element head models. In going beyond carefully controlled stimuli, in natural viewing with scanning eye movements, assessing brain states with BCI is a most challenging task. Frequent eye movements contribute artifacts to the recordings. A linear regression method is introduced that is shown to effectively characterize these frequent artifacts and could be used to remove them. In free viewing, saccadic landings initiate visual processing epochs and could be used to trigger strictly time based analysis methods. However, temporal instabilities indicate frequency based analysis would be an important adjunct. The class of Cauchy filter functions is introduced that have narrow time and frequency properties well matched to the EEG/MEG spectrum for avoiding channel leakage.
机译:各种技术,例如; EEG,MEG,fMRI,BEM,MRI,TMS和BCI进行了整合,以了解在受控实验室和自然观察条件下人类视觉皮层区域如何相互作用。我们的重点是从空间上较近的早期视觉区域分离信号的问题。该解决方案包括利用已知的功能解剖结构来指导刺激选择,并采用简化分析的时空响应特性原理。该方法还统一了MEG和EEG记录,并提供了一种改进现有边界元首模型的方法。在超越自然控制的刺激范围内,通过扫描眼球运动自然观察,用BCI评估大脑状态是一项最具挑战性的任务。频繁的眼球运动会给录音带来伪影。引入了一种线性回归方法,该方法被证明可以有效地表征这些频繁出现的伪影,并且可以用来去除它们。在免费观看中,有声着陆会启动视觉处理时代,并可用于触发严格基于时间的分析方法。但是,时间不稳定性表明基于频率的分析将是重要的辅助手段。引入了柯西滤波器函数类,它们具有窄的时间和频率特性,可以很好地匹配EEG / MEG频谱,从而避免了信道泄漏。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号