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A novel method for the identification of synchronization effects in multichannel ECoG with an application to epilepsy

机译:一种识别多通道心电图同步效应的新方法及其在癫痫中的应用

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摘要

In this paper, we present a novel method for the identification of synchronization effects in multichannel electrocorticograms (ECoG). Based on autoregressive modeling, we define a dependency measure termed extrinsic-to-intrinsic power ratio (EIPR) which quantifies directed coupling effects in the time domain. Hereby, a dynamic input channel selection algorithm assures the estimation of the model parameters despite the strong spatial correlation among the high number of involved ECoG channels. We compare EIPR to the partial directed coherence, show its ability to indicate Granger causality and successfully validate a signal model. Applying EIPR to ictal ECoG data of patients suffering from temporal lobe epilepsy allows us to identify the electrodes of the seizure onset zone. The results obtained by the proposed method are in good accordance with the clinical findings.
机译:在本文中,我们提出了一种新的方法来识别多通道皮层图(ECoG)中的同步效应。基于自回归建模,我们定义了一种称为外在与内在功率比(EIPR)的相关性度量,该度量可量化时域中的定向耦合效应。因此,尽管大量参与的ECoG通道之间存在很强的空间相关性,但动态输入通道选择算法仍可确保模型参数的估计。我们将EIPR与部分定向相干性进行了比较,显示了其指示Granger因果关系并成功验证信号模型的能力。将EIPR应用于颞叶癫痫患者的短暂ECoG数据可以使我们确定癫痫发作区的电极。通过提出的方法获得的结果与临床发现非常吻合。

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