Bistriceanu Cătălina Elena, Vulpoi Georgiana-Anca, Ciubotaru Alin, Stoleriu Iulian, Cuciureanu Dan Iulian
Neurology Department, Faculty of Medicine, University of Medicine and Pharmacy "Grigore T. Popa", 16 Universitatii Street, 700115 Iasi, Romania.
Elytis Hospital Hope, 43A Gheorghe Saulescu Street, 700010 Iasi, Romania.
Biomedicines. 2024 Dec 2;12(12):2756. doi: 10.3390/biomedicines12122756.
Recent studies have described unique aspects of default mode network connectivity in patients with idiopathic generalized epilepsy (IGE). A complete background in this field could be gained by combining this research with spectral analysis. An important objective of this study was to compare linear connectivity and power spectral densities across different activity bands of patients with juvenile absence epilepsy (JAE), juvenile myoclonic epilepsy (JME), generalized tonic-clonic seizures alone (EGTCSA), and drug-resistant IGE (DR-IGE) with healthy, age-matched controls. This was an observational case-control study. We performed EEG spectral analysis in MATLAB and connectivity analysis with LORETA for 39 patients with IGE and 12 drug-resistant IGE (DR-IGE) and healthy, age-matched subjects. We defined regions of interest (ROIs) from the default mode network (DMN) and performed connectivity statistics using time-varying spectra for paired samples. Using the same EEG data, we compared mean power spectral density (PSD) with epilepsy subgroups and controls across different activity bands. We obtained a modified value for the mean power spectral density in the beta band for the JME group as follows. The connectivity analysis showed that, in general, there was increased linear connectivity in the DMN for the JAE, JME, and EGCTSA groups compared to the healthy controls. Reduced linear connectivity between regions of the DMN was found for DR-IGE. Spectral analysis of electroencephalography (EEG) for generalized epilepsy syndromes seems to be less informative than connectivity analysis for DMN. DMN connectivity analysis, especially for DR-IGE, opens up the possibility of finding biomarkers related to drug response in IGE.
近期研究描述了特发性全身性癫痫(IGE)患者默认模式网络连接的独特方面。将这项研究与频谱分析相结合,可全面了解该领域的背景知识。本研究的一个重要目标是比较青少年失神癫痫(JAE)、青少年肌阵挛癫痫(JME)、单纯性全身强直 - 阵挛发作(EGTCSA)以及耐药性IGE(DR - IGE)患者与年龄匹配的健康对照在不同活动频段的线性连接性和功率谱密度。这是一项观察性病例对照研究。我们在MATLAB中对39例IGE患者、12例耐药性IGE(DR - IGE)患者以及年龄匹配的健康受试者进行了脑电图频谱分析,并使用LORETA进行连接性分析。我们从默认模式网络(DMN)定义了感兴趣区域(ROI),并使用配对样本的时变频谱进行连接性统计。利用相同的脑电图数据,我们比较了癫痫亚组和对照组在不同活动频段的平均功率谱密度(PSD)。我们得到了JME组在β频段平均功率谱密度的修正值,如下所示。连接性分析表明,总体而言,与健康对照相比,JAE、JME和EGCTSA组在DMN中的线性连接性增加。DR - IGE组DMN区域之间的线性连接性降低。对于全身性癫痫综合征,脑电图(EEG)的频谱分析似乎不如DMN的连接性分析信息丰富。DMN连接性分析,尤其是对于DR - IGE,为发现与IGE药物反应相关的生物标志物开辟了可能性。