Temporal and spatial dynamic propagation of electroencephalogram by combining power spectral and synchronization in childhood absence epilepsy

Lisha Zhong; Jiangzhong Wan; Jia Wu; Suling He; Xuefei Zhong; Zhiwei Huang; Zhangyong Li

doi:10.3389/fninf.2022.962466

Temporal and spatial dynamic propagation of electroencephalogram by combining power spectral and synchronization in childhood absence epilepsy

Front Neuroinform. 2022 Aug 16:16:962466. doi: 10.3389/fninf.2022.962466. eCollection 2022.

Authors

Lisha Zhong^{1

2}, Jiangzhong Wan², Jia Wu^{1

2}, Suling He¹, Xuefei Zhong³, Zhiwei Huang^{2

4}, Zhangyong Li^{1

5}

Affiliations

¹ School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
² School of Medical Information and Engineering, Southwest Medical University, Luzhou, China.
³ Children's Hospital of Chongqing Medical University, Chongqing, China.
⁴ Central Nervous System Drug Key Laboratory of Sichuan Province, Luzhou, China.
⁵ Research Center of Biomedical Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.

Abstract

Objective: During the transition from normal to seizure and then to termination, electroencephalography (EEG) signals have complex changes in time-frequency-spatial characteristics. The quantitative analysis of EEG characteristics and the exploration of their dynamic propagation in this paper would help to provide new biomarkers for distinguishing between pre-ictal and inter-ictal states and to better understand the seizure mechanisms.

Methods: Thirty-three children with absence epilepsy were investigated with EEG signals. Power spectral and synchronization were combined to provide the time-frequency-spatial characteristics of EEG and analyze the spatial distribution and propagation of EEG in the brain with topographic maps. To understand the mechanism of spatial-temporal evolution, we compared inter-ictal, pre-ictal, and ictal states in EEG power spectral and synchronization network and its rhythms in each frequency band.

Results: Power, frequency, and spatial synchronization are all enhanced during the absence seizures to jointly dominate the epilepsy process. We confirmed that a rapid diffusion at the onset accompanied by the frontal region predominance exists. The EEG power rapidly bursts in 2-4 Hz through the whole brain within a few seconds after the onset. This spatiotemporal evolution is associated with spatial diffusion and brain regions interaction, with a similar pattern, increasing first and then decreasing, in both the diffusion of the EEG power and the connectivity of the brain network during the childhood absence epilepsy (CAE) seizures. Compared with the inter-ictal group, we observed increases in power of delta and theta rhythms in the pre-ictal group (P < 0.05). Meanwhile, the synchronization of delta rhythm decreased while that of alpha rhythm enhanced.

Conclusion: The initiation and propagation of CAE seizures are related to the abnormal discharge diffusion and the synchronization network. During the seizures, brain activity is completely changed with the main component delta rhythm. Furthermore, this article demonstrated for the first time that alpha inhibition, which is consistent with the brain's feedback regulation mechanism, is caused by the enhancement of the network connection. Temporal and spatial evolution of EEG is of great significance for the transmission mechanism, clinical diagnosis and automatic detection of absence epilepsy seizures.

Keywords: EEG; childhood absence epilepsy; phase locking value; power spectral density; time-frequency-spatial characteristics.