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癫痫脑电图信号半球间和半球内相干性的定量分析

Quantitative Analysis of Inter- and Intrahemispheric Coherence on Epileptic Electroencephalography Signal.

作者信息

Wijayanto Inung, Hartanto Rudy, Nugroho Hanung Adi

机构信息

Department of Electrical and Information Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia.

School of Electrical Engineering, Telkom University, Bandung, Indonesia.

出版信息

J Med Signals Sens. 2022 May 12;12(2):145-154. doi: 10.4103/jmss.JMSS_63_20. eCollection 2022 Apr-Jun.

Abstract

When an epileptic seizure occurs, the neuron's activity of the brain is dynamically changed, which affects the connectivity between brain regions. The connectivity of each brain region can be quantified by electroencephalography (EEG) coherence, which measures the statistical correlation between electrodes spatially separated on the scalp. Previous studies conducted a coherence analysis of all EEG electrodes covering all parts of the brain. However, in an epileptic condition, seizures occur in a specific region of the brain then spreading to other areas. Therefore, this study applies an energy-based channel selection process to determine the coherence analysis in the most active brain regions during the seizure. This paper presents a quantitative analysis of inter- and intrahemispheric coherence in epileptic EEG signals and the correlation with the channel activity to glean insights about brain area connectivity changes during epileptic seizures. The EEG signals are obtained from ten patients' data from the CHB-MIT dataset. Pair-wise electrode spectral coherence is calculated in the full band and five sub-bands of EEG signals. The channel activity level is determined by calculating the energy of each channel in all patients. The EEG coherence observation in the preictal ( ) and ictal ( ) conditions showed a significant decrease of in the most active channel, especially in the lower EEG sub-bands. This finding indicates that there is a strong correlation between the decrease of mean spectral coherence and channel activity. The decrease of coherence in epileptic conditions ( < ) indicates low neuronal connectivity. There are some exceptions in some channel pairs, but a constant pattern is found in the high activity channel. This shows a strong correlation between the decrease of coherence and the channel activity. The finding in this study demonstrates that the neuronal connectivity of epileptic EEG signals is suitable to be analyzed in the more active brain regions.

摘要

癫痫发作时,大脑神经元的活动会动态变化,这会影响脑区之间的连接性。每个脑区的连接性可以通过脑电图(EEG)相干性来量化,EEG相干性测量头皮上空间分离的电极之间的统计相关性。先前的研究对覆盖大脑所有部位的所有EEG电极进行了相干性分析。然而,在癫痫状态下,癫痫发作发生在大脑的特定区域,然后扩散到其他区域。因此,本研究应用基于能量的通道选择过程来确定癫痫发作期间最活跃脑区的相干性分析。本文对癫痫EEG信号的半球间和半球内相干性进行了定量分析,并分析了其与通道活动的相关性,以深入了解癫痫发作期间脑区连接性的变化。EEG信号来自CHB-MIT数据集中10名患者的数据。在EEG信号的全频段和五个子频段中计算成对电极的频谱相干性。通过计算所有患者每个通道的能量来确定通道活动水平。发作前( )和发作期( )条件下的EEG相干性观察表明,最活跃通道的相干性显著下降 ,尤其是在较低的EEG子频段。这一发现表明,平均频谱相干性的下降与通道活动之间存在很强的相关性。癫痫状态下相干性的下降( < )表明神经元连接性较低。在一些通道对中存在一些例外情况,但在高活动通道中发现了一种恒定的模式。这表明相干性的下降与通道活动之间存在很强的相关性。本研究的结果表明,癫痫EEG信号的神经元连接性适合在更活跃的脑区进行分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b8a2/9215829/a09e7e9f28b5/JMSS-12-145-g001.jpg

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