Quantitative EEG analysis in typical absence seizures: unveiling spectral dynamics and entropy patterns

Frontiers in Human Neuroscience

Human Neuroscience

Alejandra Genel-Espinoza¹  Evelin Ramírez-Ponce²  Rebeca Romo-Vazquez²  Hugo Vélez-Pérez²  Oscar Ramos-Quezada²  Omar Paredes³  Erick Guzmán-Quezada⁴  Alioth Guerrero-Aranda⁵ 

[1] Centro Infantil para el Desarrollo Neuroconductual, Hermosillo, Sonora, Mexico;Depto. de Bioingeniería Traslacional, Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico;Depto. de Bioingeniería Traslacional, Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico;Mecatrónica, Instituto Tecnológico y de Estudios Superiores de Monterrey, Escuela de Ingenierías y Ciencias (ITESM) Campus Guadalajara, Zapopan, Mexico;Depto. de Ciencias Computacionales, Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico;Depto. de Electromecánica, Universidad Autónoma de Guadalajara, Zapopan, Jalisco, Mexico;Depto. de Ciencias de la Salud, Centro Universitario de Los Valles, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico;Clínica de Epilepsia, Hospital “Country 2000, ” Guadalajara, Jalisco, Mexico;

关键词: EEG;    entropy;    epilepsy;    ictal;    interictal;    spectral analysis;    spike-and-wave;    typical absence seizure;   

DOI  :  10.3389/fnhum.2023.1274834

 received in 2023-08-08, accepted in 2023-09-21,  发布年份 2023

来源: Frontiers

【 摘 要 】

A typical absence seizure is a generalized epileptic event characterized by a sudden, brief alteration of consciousness that serves as a hallmark for various generalized epilepsy syndromes. Distinguishing between similar interictal and ictal electroencephalographic (EEG) epileptiform patterns poses a challenge. However, quantitative EEG, particularly spectral analysis focused on EEG rhythms, shows potential for differentiation. This study was designed to investigate discernible differences in EEG spectral dynamics and entropy patterns during the pre-ictal and post-ictal periods compared to the interictal state. We analyzed 20 EEG ictal patterns from 11 patients with confirmed typical absence seizures, and assessed recordings made during the pre-ictal, post-ictal, and interictal intervals. Power spectral density (PSD) was used for the quantitative analysis that focused on the delta, theta, alpha, and beta bands. In addition, we measured EEG signal regularity using approximate (ApEn) and multi-scale sample entropy (MSE). Findings demonstrate a significant increase in delta and theta power in the pre-ictal and post-ictal intervals compared to the interictal interval, especially in the posterior brain region. We also observed a notable decrease in entropy in the pre-ictal and post-ictal intervals, with a more pronounced effect in anterior brain regions. These results provide valuable information that can potentially aid in differentiating epileptiform patterns in typical absence seizures. The implications of our findings are promising for precision medicine approaches to epilepsy diagnoses and patient management. In conclusion, our quantitative analysis of EEG data suggests that PSD and entropy measures hold promise as potential biomarkers for distinguishing ictal from interictal epileptiform patterns in patients with confirmed or suspected typical absence seizures.

【 授权许可】

Unknown   
Copyright © 2023 Guerrero-Aranda, Ramírez-Ponce, Ramos-Quezada, Paredes, Guzmán-Quezada, Genel-Espinoza, Romo-Vazquez and Vélez-Pérez.