The Anatomo-Electrical Network Underlying Hypermotor Seizures - Wang, Xiu; Hu, Wenhan; Zhang, Kai; Shao, Xiaoqiu; Ma, Yanshan; Sang, Lin; Zheng, Zhong; Zhang, Chao; Li, Junjv; Zhang, Jian-guo (Frontiers in Neurology, 2018)
Purpose: Hypermotor seizures (HMS) can be triggered by different epileptogenic foci and thus common symptomatic networks generating HMS may exist among these patients. The goal of the present study was to investigate the specialized networks underlying HMS by analyzing interictal 18FDG-PET imaging and ictal stereo-electroencephalography (SEEG) recordings. Methods: Fourteen patients with HMS were retrospectively analyzed. HMS were classified into HMS1 and HMS2 according to the speed and intensity of the motor seizure behavior. Then, the interictal PET data of patients was compared with those of 18 healthy controls using statistical parametric mapping to identify regions with significant hypometabolism. Ictal SEEG recordings were reviewed to identify the spreading areas at the beginning of HMS occurrence. Results: Compared to controls, patients with HMS presented significant hypometabolism in the bilateral anterosuperior insular lobes, mesial premotor cortex (MPMC), middle cingulate cortex (MCC), as well as in the bilateral caudate nuclei. When comparing patients in the two HMS subgroups with controls, more extensive hypometabolic areas were seen in HMS1 patients than in HMS2 patients, including the orbitofrontal cortex (OFC), the temporal pole and the anterior cingulate cortex (ACC). OFC and ventromedial prefrontal cortex was also found significantly hypometabolic in patients with HMS1 when compared with HMS2 directly. SEEG recordings further suggested that insula, MCC and MPMC were commonly recruited at the beginning of HMS. Conclusions: We have identified a specialized interictal hypometabolic pattern in patients with HMS. A network involving the anterosuperior insula, mesiofrontal cortex (MCC-MPMC) and caudate nucleus may contribute to the generation of HMS. ACC, OFC and temporal pole are possibly associated with the affective components of HMS. Our findings provide further insight into understanding the network basis of HMS semiology.