首页> 外文会议>International Conference on Natural Computation >A multimodal framework for integrating biological spectral characteristics and MEG/EEG in brain-source imaging
【24h】

A multimodal framework for integrating biological spectral characteristics and MEG/EEG in brain-source imaging

机译:一种用于整合生物光谱特性和脑源成像中的生物光谱特性和eEG的多模态框架

获取原文

摘要

This paper presents a multimodal framework that considers the spatio-temporal-spectral characteristics of biophysics provided by electrocorticographic (ECoG) and magnetoencephalography (MEG)/electroencephalography (EEG). In this framework, three strategies are proposed to integrate biological characteristics into MEG/EEG source imaging, the coefficient constraint (CoCo) gives a conservative estimate; the exponent constraint (ExCo) yields a polarized resolution; the hybrid constraint (HyCo) dynamically balances the reliance on CoCo and ExCo, based on the quality of the MEG/EEG data, and takes full advantages of both, providing the framework with heuristic ability. Our contribution is a framework with the potential to use biological characteristics information when doing source imaging.
机译:本文提出了一种多模式框架,其考虑了通过电加电光学表(ECOG)和磁性脑(MEEG)/脑电图(EEG)提供的生物物理学的时空谱特性。在该框架中,提出了三种策略来将生物学特性整合到MEG / EEG源成像中,系数约束(COCO)给予保守估计;指数约束(ICIC)产生极化分辨率;混合约束(Hyco)根据MEG / EEG数据的质量,动态平衡对COCO和ICO的依赖,并采取完全优势,提供具有启发式能力的框架。我们的贡献是在进行源成像时使用生物学特征信息的框架。

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