Epilepsy is one of the most common neurological disorders, and surgical intervention is usually used for drug-resistant focal epilepsy. Cortical electrical stimulation is widely used in preoperative evaluation of epilepsy to explore the anatomical-clinical electrical correlations between epileptogenic and functional networks through electrical stimulation, and the functional brain maps produced by cortical electrical stimulation depict areas of the functional cortex at an individual level, identifying the functional cortex with greater precision, as well as helping to establish epilepsy network, enabling more precise localization of seizure zones and providing a more accurate localization for surgical resection. Electrical cortical stimulation has become a standard technique for the preoperative assessment of brain region function in brain surgery. It is an indispensable part of preoperative evaluation.The main types of functional mapping by electrical stimulation include stereoelectroencephalography (SEEG) and subdural electrode (SDE), SEEG-guided cortical electrical stimulation is gradually becoming more mainstream compared to subdural electrodes, and is increasingly valuable and important as a preoperative evaluation of epilepsy. It is increasingly demonstrating its value and importance because it avoids craniotomy, takes less time for surgery, has fewer associated complications and infections, and can explore deep lesions, increasing the understanding of human functional neuroanatomy and enabling more precise localization of seizure zones.This article reviews the history of the development of cortical electrical stimulation technology, the intrinsic mechanisms, the value of the application of SEEG, and also provides a comprehensive comparison between SEEG and SDE, despite the irreplaceable advantages of SEEG, attention should be paid to the unresolved clinical and scientific issues of SEEG, and the establishment of a consensus-based clinical guideline, as the application of this technology will be more widely used in both clinical and scientific work.
Stereo-electroencephalography (SEEG) is widely used to record the electrical activity of patients' brain in clinical. The SEEG-based epileptogenic network can better describe the origin and the spreading of seizures, which makes it an important measure to localize epileptogenic zone (EZ). SEEG data from six patients with refractory epilepsy are used in this study. Five of them are with temporal lobe epilepsy, and the other is with extratemporal lobe epilepsy. The node outflow (out-degree) and inflow (in-degree) of information are calculated in each node of epileptic network, and the overlay between selected nodes and resected nodes is analyzed. In this study, SEEG data is transformed to bipolar montage, and then the epileptic network is established by using independent effective coherence (iCoh) method. The SEEG segments at onset, middle and termination of seizures in Delta, Theta, Alpha, Beta, and Gamma rhythms are used respectively. Finally, the K-means clustering algorithm is applied on the node values of out-degree and in-degree respectively. The nodes in the cluster with high value are compared with the resected regions. The final results show that the accuracy of selected nodes in resected region in the Delta, Alpha and Beta rhythm are 0.90, 0.88 and 0.89 based on out-degree values in temporal lobe epilepsy patients respectively, while the in-degree values cannot differentiate them. In contrast, the out-degree values are higher outside the temporal lobe in the patient with extratemporal lobe epilepsy. Based on the out-degree feature in low-frequency epileptic network, this study provides a potential quantitative measure for identifying patients with temporal lobe epilepsy in clinical.
ObjectiveTo explore the prognostic value of normal 24 hour video electroencephalography (VEEG) with different frequency on antiepileptic drugs (AEDs) withdrawal in cryptogenic epilepsy patients with three years seizure-free. MethodsA retrospective study was conducted in the Neurology outpatient and the Epilepsy Center of Xi Jing Hospital. The subject who had been seizure free more than 3 years were divided into continual normal twice group and once group according to the nomal frequence of 24 hour VEEG before discontinuation from January 2013 to December 2014, and then followed up to replase or to December 2015. The recurrence and cumulative recurrence rate of the two group after withdrawal AEDs were compared with chi-square or Fisher's exact test and Kaplan-Meier survival curve. A Cox proportional hazard model was used for multivariate analysis to identify the risk factors for seizure recurrence after univariate analysis. P value < 0.05 was considered significant, and all P values were two-tailed. Results95 epilepsy patients with cause unknown between 9 to 45 years old were recruited (63 in normal twice group and 32 in normal once group). The cumulated recurrence rates in continual two normal VEEG group vs one normal VEEG group were 4.8% vs 21.9% (P=0.028), 4.8% vs 25% (P=0.006) and 7.9% vs 25%(P=0.03) at 18 months, 24 months and endpoint following AEDs withdrawal and there was statistically difference between the two groups. Factors associated with increased risk were adolescent onset epilepsy (HR=2.404), history of withdrawal recurrence (HR=7.186) and abnormal VEEG (epileptic-form discharge) (HR=8.222) during or after withdrawal AEDs. The recurrence rate of each group in which abnormal VEEG vs unchanged VEEG during or after withdrawal AEDs was respectively 100% vs 4.92% (P=0.005), 80% vs 19.23%(P=0.009). ConclusionsContinual normal 24h VEEG twice before withdrawal AEDs had higher predicting value of seizure recurrence and it could guide physicians to make the withdrawal decision. Epileptic patients with adolescent onset epilepsy, history of seizure recurrence and abnormal VEEG (epileptic-form discharge) during or after withdrawal AEDs had high risk of replase, especially patients with the presence of VEEG abnormalities is associated with a high probability of seizures occurring. Discontinuate AEDs should be cautious.
The brain-computer interface (BCI) based on motor imagery electroencephalography (EEG) shows great potential in neurorehabilitation due to its non-invasive nature and ease of use. However, motor imagery EEG signals have low signal-to-noise ratios and spatiotemporal resolutions, leading to low decoding recognition rates with traditional neural networks. To address this, this paper proposed a three-dimensional (3D) convolutional neural network (CNN) method that learns spatial-frequency feature maps, using Welch method to calculate the power spectrum of EEG frequency bands, converted time-series EEG into a brain topographical map with spatial-frequency information. A 3D network with one-dimensional and two-dimensional convolutional layers was designed to effectively learn these features. Comparative experiments demonstrated that the average decoding recognition rate reached 86.89%, outperforming traditional methods and validating the effectiveness of this approach in motor imagery EEG decoding.
ObjectiveTo explore the advantages and disadvantages of using two intracranial EEG (iEEG) monitoring methods—Subdural ectrodes electroencephalography (SDEG)and Stereoelectroencephalography (SEEG), in patients with “difficult to locate” Intractable Epilepsy. MethodsRetrospectively analyzed the data of 60 patients with SDEG monitoring (49 cases) and SEEG monitoring (11 cases) from January 2010 to December 2018 in the Department of Neurosurgery of the First Affiliated Hospital of Fujian Medical. Observe and statistically compare the differences in the evaluation results of epileptic zones, surgical efficacy and related complications of the two groups of patients, and review the relevant literature. ResultsThe results showed that the two groups of SDEG and SEEG had no significant difference in the positive rate and surgical resection rate of epileptogenic zones, but the bilateral implantation rate of SEEG (5/11, 45.5%) was higher than that of SDEG (18/49, 36.7%). At present, there was no significant difference in the postoperative outcome among patients with epileptic zones resected after SDEG and SEEG monitoring (P>0.05). However, due to the limitation of the number of SEEG cases, it is not yet possible to conclude that the two effects were the same. There was a statistically significant difference in the total incidence of serious complications of bleeding or infection between the two groups (SDEG 20 cases vs. SEEG 1 case, P<0.05). There was a statistically significant difference in the total incidence of significant headache or cerebral edema between the two groups (SDEG 26 cases vs. SEEG 2 cases, P<0.05). There was a statistically significant difference in the incidence of cerebrospinal fluid leakage, subcutaneous fluid incision, and poor healing of incision after epileptic resection (SDEG 14 cases vs. SEEG 0 case, P<0.05); there were no significant differences in dysfunction of speech, muscle strength between the two groups (P>0.05). ConclusionSEEG has fewer complications than SDEG, SEEG is safer than SDEG. The two kinds of iEEG monitoring methods have advantages in the localization of epileptogenic zones and the differentiation of functional areas. The effective combination of the two methods in the future may be more conducive to the location of epileptic zones and functional areas.
Aiming at the problem that the feature extraction ability of forehead single-channel electroencephalography (EEG) signals is insufficient, which leads to decreased fatigue detection accuracy, a fatigue feature extraction and classification algorithm based on supervised contrastive learning is proposed. Firstly, the raw signals are filtered by empirical modal decomposition to improve the signal-to-noise ratio. Secondly, considering the limitation of the one-dimensional signal in information expression, overlapping sampling is used to transform the signal into a two-dimensional structure, and simultaneously express the short-term and long-term changes of the signal. The feature extraction network is constructed by depthwise separable convolution to accelerate model operation. Finally, the model is globally optimized by combining the supervised contrastive loss and the mean square error loss. Experiments show that the average accuracy of the algorithm for classifying three fatigue states can reach 75.80%, which is greatly improved compared with other advanced algorithms, and the accuracy and feasibility of fatigue detection by single-channel EEG signals are significantly improved. The results provide strong support for the application of single-channel EEG signals, and also provide a new idea for fatigue detection research.
Objective To research clinical manifestations, electrophysiological characteristics of epileptic seizures arising from diagonal sulci (DS), to improve the level of the diagnosis and treatment of frontal epilepsy. MethodsWe reviewed all the patients underwent a detailed presurgical evaluation, including 5 patients with seizures to be proved originating from diagonal sulci by Stereo-electroencephalography (SEEG). All the 5 patients with detailed medical history, head Magnetic resonance (MRI), the Positron emission computered tomography (PET-CT) and psychological evaluation, habitual seizures were recorded by Video-electroencephalography (VEEG) and SEEG, we review the intermittent VEEG and ictal VEEG, analyzing the symptoms of seizures. Results 5 patients were divided into 2 groups by SEEG, group 1 including 3 patients with seizures arising from the bottom of DS, group 2 including 2 patients with seizures arising from the surface of DS, all the tow groups with seizures characterized by both having tonic and complex motors, tonic seizures were prominent in seizures from left DS, and tonic seizures may absent in seizures from right DS. Intermittent discharges with group1 were diffused, and intermittent discharges with group 2 were focal, but both brain areas of frontal and temporal were infected. Ictal EEG findings were consistent with the characteristics of neocortical seizures, the onset EEG shows voltage attenuation, seizures from bottom of DS with diffused EEG onset, and seizures from surface of DS with more focal EEG onset, but both frontal and anterior temporal regions were involved. Conclusionthe symptom of seizures arising from DS characterized by tonic and complex motor, can be divided into seizures arising from the bottom of DS and seizures from the surface of DS, with different electrophysiological characters.
ObjectiveTo explore the clinical features and EEG features of gelastic seizures, and analyze its value of lateral localization of epileptogenic area. MethodsAll patients with gelastic seizures admitted to the Sanbo Brain Hospital of Capital Medical University between January 2014 and December 2023 were reviewed and analyzed for history, symptomatology, imaging, electroencephalographic features and surgical protocols in patients who met the inclusion criteria and were followed up for at least 1 year, and surgical efficacy was assessed by using the Engel grading. ResultsA total of 51 patients with gelastic seizures were included, there were 32 (62.75%) males and 19 (37.25%) females, 21 (41.18%) with hypothalamic hamartomas (HH) and 30 (58.82%) with non-hypothalamic hamartomas. The age of onset was earlier in the HH group than in the non-HH group, with a median age of onset of 24.00 (0.00 ~ 96.00) and 78.00 (1.00 ~ 396.00) months (P<0.001). There are three types of laughter according to their characteristics: smiling or pleasant expressions, laughing out loud, crying or bitter laughter, with smiling or pleasant expressions being the most common (49.02%). Simple laughter is rare in all patients and is often accompanied by other manifestations such as autonomic symptoms, automatic movements, complex movements, and tonic seizures. Most of the HH group started with laughter whereas in the non-HH group laughter appeared mostly in the mid to late stages (P=0.007). Most of the HH group (57.14%) had preserved consciousness whereas most of the non-HH group (83.33%) had loss of consciousness (P=0.003). The interictal discharges in the HH group were mostly diffuse or multiregional, whereas those in the non-HH group were mostly regional (P=0.035). The onset of EEG during the seizure period in the HH group was mostly diffuse, whereas those in the non-HH group were mostly regional, mainly in the frontal and temporal regions, but there was no significant difference between the two groups (P=0.148). The non-HH group was mostly seen in those with definite lesions, and the most common type of lesion was FCD (focal cortical dysplasia, FCD). All patients enrolled in the group underwent surgical treatment, and stereoelectroencephalogram (SEEG) electrode implantation was performed in 13 cases in the HH group and in 17 cases in the non-HH group. 61.90% of the patients in the HH group had an Engel grade I, and 73.33% of the patients in the non-HH group had an Engel grade I. ConclusionsGelastic seizures has a complex neural network, with common causes other than hypothalamic hamartomas, and is most commonly seen in frontal or temporal lobe epilepsy, as well as in the insula or parietal lobe, with the most common type of lesion being FCD. The symptomatology, stage of onset, and electroencephalographic features of gelastic seizures can help in the differential diagnosis, and SEEG can help define the origin of the seizure and its diffusion pathway. The overall prognosis of surgical treatment was better in both the hypothalamic hamartomas and non-hypothalamic hamartomas groups.
Repetitive transcranial magnetic stimulation (rTMS) can influence the stimulated brain regions and other distal brain regions connecting to them. The purpose of the study is to investigate the effects of low-frequency rTMS over primary motor cortex on brain by analyzing the brain functional connectivity and coordination between brain regions. 10 healthy subjects were recruited. 1 Hz rTMS was used to stimulate primary motor cortex for 20 min. 1 min resting state electroencephalography (EEG) was collected before and after the stimulation respectively. By performing phase synchronization analysis between the EEG electrodes, the brain functional network and its properties were calculated. Signed-rank test was used for statistical analysis. The result demonstrated that the global phase synchronization in alpha frequency band was decreased significantly after low-frequency rTMS (P<0.05). The phase synchronization was down-regulated between motor cortex and ipsilateral frontal/parietal cortex, and also between contralateral parietal cortex and bilateral frontal cortex. The mean degree and global efficiency of brain functional networks in alpha frequency band were significantly decreased (P<0.05), and the mean shortest path length were significantly increased (P<0.05), which suggested the information transmission of the brain networks and its efficiency was reduced after low-frequency rTMS. This study verified the inhibition function of the low-frequency rTMS to brain activities, and demonstrated that low-frequency rTMS stimulation could affect both stimulating brain regions and distal brain regions connected to them. The findings in this study could be of guidance to clinical application of low-frequency rTMS.
ObjectiveTo investigate characteristics of motor semiology of epileptic seizure originated from dorsolateral frontal lobe. MethodsRetrospectively analysis the clinical profiles of patients who were diagnosed dorsolateral frontal lobe epilepsy (FLE) based on stereoelectroencephalography (SEEG) and underwent respective surgeries subsequently. Component of motor semiology in a seizure can be divided into elementary motor (EM, include tonic, versive, clonic, and myoclonic seizures) and complex motor (CM, include automotor, hypermotor, and so on). A Talairach coordinate system was constructed in the sagittal series of MRI images in each case. From the cross point of VAC and the Sylvian Fissure, a line was drawn antero-superiorly, which made an angle of 60° with the AC-PC line, then the frontal lobe could be divided into anterior and posterior portion. The epileptogenic zone, which was defined as ictal onset and early spreading zone in SEEG, was classified into three types, according to the positional relationship of the responding electrodes contacts and the "60° line": the anterior, posterior, and intermediate FLE. The correlation of the components of motor semiology in seizures and the location of the epileptogenic zone was analyzed. ResultsFive cases (26.3%) were verified as anterior FLE, among which there were 2 of EM, one of CM, and 2 of EM+CM. In 7 cases (36.8%) of intermediate FLE, there were one of EM, none of CM, and 6 of EM+CM. In the rest 7 cases of posterior FLE, there were 6 of EM, none of CM, and one of EM+CM. Compared with the cases that the epileptogenic zone involved anterior portion, the posterior FLE is more likely to present EM seizures (85.7%), and less likely to show CM components (P < 0.05). And Compared with the anterior FLE and posterior FLE, the intermediate FLE is more likely to present EM+CM seizures (85.7%)(P < 0.05). ConclusionThe motor seizure semiology of dorsolateral FLE has significant correlation with the localization of the epileptogenic zone. Posterior FLE mainly present a pure elementary motor seizure, and once the epileptogenic zone involved anteriorly beyond the "60° line", the component of complex motor seizure would be seen. Intermediate FLE, as its specialty of transboundary, is more likely to show "comprised semiology" of EM and CM. Construction of the "60° line" with AC-PC coordinate system in the MRI images may play an useful role in semiology analysis in presurgical evaluation of FLE.