Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.
Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.
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DOI：
10.1080/00207450902854627
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Yoo SS
中科院分区：
文献类型：
--
作者：
Lee JH;Oh S;Jolesz FA;Park H;Yoo SS
同时采集脑电图（EEG）和功能性MRI（fMRI）信号是潜在的优势，因为上级分辨率，分别在时间和空间域实现。然而，心冲击描记术伪影沿着眼部伪影是检测感兴趣的EEG特征的主要障碍。由于与这些伪影对应的源与产生EEG签名的源是独立的，因此我们应用基于Infomax的独立分量分析（伊卡）技术将EEG签名与伪影分离。分离的EEG特征被进一步用于对典型的血流动力学响应函数（HRF）进行建模。随后，从这些脑电图签名起源的大脑区域被确定为从功能磁共振成像数据分析的激活模式的区域。在识别和随后的评估脑区产生发作间期癫痫放电（IED）尖峰从癫痫受试者，所提出的方法被成功地应用于检测θ和α-节奏，睡眠开始相关的EEG签名沿着与随后的神经回路从睡眠剥夺志愿者。这些结果表明，伊卡技术可能是有用的预处理同步EEG-fMRI采集，特别是当一个参考范例是不可用的。
The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with the ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta- and alpha-rhythms that are sleep onset related EEG signatures along with the subsequent neural circuitries from a sleep deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG-fMRI acquisitions, especially when a reference paradigm is unavailable.
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DOI：
10.1073/pnas.0505210102
发表时间：
2005-12-20
影响因子：
11.1
作者：
deCharms, RC;Maeda, F;Mackey, SC
通讯作者：
Mackey, SC
影响因子：
2.5
作者：
Briselli, Ennio;Garreffa, Girolamo;Maraviglia, Bruno
通讯作者：
Maraviglia, Bruno
影响因子：
3.3
作者：
De Gennaro, L;Ferrara, M;Bertini, M
通讯作者：
Bertini, M
影响因子：
5.5
作者：
Kotajima, F;Meadows, GE;Corfield, DR
通讯作者：
Corfield, DR
影响因子：
5.7
作者：
Mantini, D.;Perrucci, M. G.;Del Gratta, C.
通讯作者：
Del Gratta, C.