Epilepsy Center, Medical Center, University of Freiburg, Breisacher Str. 64, 79106 Freiburg im Breisgau, Germany.
Epilepsy Center, Medical Center, University of Freiburg, Breisacher Str. 64, 79106 Freiburg im Breisgau, Germany.
Neuroimage Clin. 2024;44:103673. doi: 10.1016/j.nicl.2024.103673. Epub 2024 Sep 16.
Alterations in brain networks may cause the lowering of the seizure threshold and hypersynchronization that underlie the recurrence of unprovoked seizures in epilepsy. The aim of this work is to estimate functional network characteristics, which may help predicting outcome of epilepsy surgery. Twenty patients were studied (11 females, 9 males, mean age 33 years) with scalp-recorded HD-EEG in resting state (eyes closed, no interictal discharges) before intracranial evaluation, which allowed the precise determination of the epileptogenic zone. Dipole source time courses in the brain were estimated using Weighted Minimum Norm Estimate based on HD-EEG signals. Information inflow and outflow of atlas-based brain regions were computed using partial directed connectivity. A set of graph measures for pairwise connections in standard EEG frequency bands was calculated. After epilepsy surgery 10 patients were seizure-free (Engel 1a) and 10 patients continued suffering from seizures (Engel outcome worse than 1a). Inflow of the regions containing the epileptogenic zone in the beta and delta frequency bands was significantly lower in patients who achieved seizure-freedom after surgery, compared with patients who continued to have seizures (p = 0.012, and p = 0.026, respectively). Average path length in the beta frequency band was significantly higher in patients who achieved seizure freedom (p = 0.012). In the delta frequency band, local efficiency and clustering coefficient were significantly higher in patients who achieved seizure freedom (0.033, 0.046). In patients who achieved seizure freedom after surgery, the preoperative analysis of the epileptic network exhibited stronger separation of the region containing the seizure onset zone, with less inflow of information. In contrast, shorter paths within the epileptic network may facilitate hypersynchronous neuronal activity and thus the recurrence of seizures in non-seizure free patients. This study supports the hypothesis that epileptic network properties might help to define suitable candidates for epilepsy surgery.
大脑网络的改变可能导致癫痫发作阈值降低和超同步，从而导致癫痫发作的无诱因复发。本研究旨在评估功能网络特征，这可能有助于预测癫痫手术的结果。20 名患者（11 名女性，9 名男性，平均年龄 33 岁）接受了头皮记录的 HD-EEG 研究（闭眼，无发作期放电），然后进行颅内评估，以精确定位致痫区。使用基于 HD-EEG 信号的加权最小范数估计（Weighted Minimum Norm Estimate）估计脑内偶极子源时程。使用偏定向连通性计算基于图谱的脑区的信息流和流出流。计算标准 EEG 频带中成对连接的一组图度量。在癫痫手术后，10 名患者无癫痫发作（Engel 1a），10 名患者继续癫痫发作（Engel 结果差于 1a）。在手术后无癫痫发作的患者中，β和δ频带中包含致痫区的区域的流入明显低于继续癫痫发作的患者（p=0.012 和 p=0.026）。β频带中的平均路径长度在无癫痫发作的患者中明显较高（p=0.012）。在δ频带中，无癫痫发作的患者的局部效率和聚类系数明显较高（0.033 和 0.046）。在手术后无癫痫发作的患者中，术前癫痫网络分析显示包含癫痫起始区的区域分离更强，信息流入减少。相反，癫痫网络内的较短路径可能促进超同步神经元活动，从而导致非无癫痫发作患者的癫痫发作复发。本研究支持这样一种假设，即癫痫网络特性可能有助于确定适合癫痫手术的患者。
