A disease warranting attention from neurosurgeons: primary central nervous system post-transplant lymphoproliferative disorder.

Background: Primary central nervous system post-transplant lymphoproliferative disorder (PCNS-PTLD) is a rare condition, posing diagnostic and treatment challenges, with histological biopsy essential for diagnosis. Standardized treatment protocols are lacking. This disease requires urgent attention due to the increasing number of organ transplant surgeries and the use of immunosuppressive agents. Methods: From 2020 to 2023, our center diagnosed five patients with PCNS-PTLD. We reviewed their clinical records and conducted a comprehensive analysis of 22 literatures on PCNS-PTLD cases following renal transplantation or allogeneic hematopoietic stem cell transplantation (HSCT). Results: Four patients had previously received a kidney transplant, one had undergone allogeneic HSCT. The median time from the last transplant surgery to the diagnosis of PCNS-PTLD differs between kidney transplant (21.5 years) and allogeneic HSCT (9 months). Common symptoms included motor weakness (n = 4), headache (n = 2), confusion (n = 2), and nausea (n = 2), with ring-enhancing (n = 5), typically solitary (n = 3) and supratentorial (n = 3) lesions on imaging. Diagnosis involved robot-assisted stereotactic brain biopsy (n = 4) or craniotomy (n = 1), all showing Epstein-Barr virus and CD20 positivity. Most cases (n = 4) were monomorphic diffuse large B-cell lymphoma. Treatment included rituximab (n = 3), surgical resection (n = 2), zanubrutinib (n = 1), whole-brain radiation (n = 1), and methotrexate (n = 1). At the last follow-up, the median duration of follow-up for all patients was 19 months. During this time, 3 patients had died and 2 patients were still alive. Conclusion: In patients with a history of kidney transplantation or allogeneic HSCT who are on long-term immunosuppressive therapy, any neurological symptoms, particularly the presence of supratentorial ring-enhancing masses in the brain on imaging, whether solitary or multiple, should raise high suspicion for this disease, warranting a timely brain biopsy. Additionally, we found that besides reducing immunosuppressants, zanubrutinib may be a potential, safe, and effective treatment for this condition. Moreover, post-surgical administration of rituximab in conjunction with whole-brain radiotherapy also appears to be a potentially safe and effective approach.

Wearable sensor devices can automatically identify the ON-OFF status of patients with Parkinson's disease through an interpretable machine learning model.

Introduction: Accurately and objectively quantifying the clinical features of Parkinson's disease (PD) is crucial for assisting in diagnosis and guiding the formulation of treatment plans. Therefore, based on the data on multi-site motor features, this study aimed to develop an interpretable machine learning (ML) model for classifying the "OFF" and "ON" status of patients with PD, as well as to explore the motor features that are most associated with changes in clinical symptoms. Methods: We employed a support vector machine with a recursive feature elimination (SVM-RFE) algorithm to select promising motion features. Subsequently, 12 ML models were constructed based on these features, and we identified the model with the best classification performance. Then, we used the SHapley Additive exPlanations (SHAP) and the Local Interpretable Model agnostic Explanations (LIME) methods to explain the model and rank the importance of those motor features. Results: A total of 96 patients were finally included in this study. The naive Bayes (NB) model had the highest classification performance (AUC = 0.956; sensitivity = 0.8947, 95% CI 0.6686-0.9870; accuracy = 0.8421, 95% CI 0.6875-0.9398). Based on the NB model, we analyzed the importance of eight motor features toward the classification results using the SHAP algorithm. The Gait: range of motion (RoM) Shank left (L) (degrees) [Mean] might be the most important motor feature for all classification horizons. Conclusion: The symptoms of PD could be objectively quantified. By utilizing suitable motor features to construct ML models, it became possible to intelligently identify whether patients with PD were in the "ON" or "OFF" status. The variations in these motor features were significantly correlated with improvement rates in patients' quality of life. In the future, they might act as objective digital biomarkers to elucidate the changes in symptoms observed in patients with PD and might be used to assist in the diagnosis and treatment of patients with PD.

Aberrant individual structure covariance network in patients with mesial temporal lobe epilepsy.

Objective: Mesial temporal lobe epilepsy (mTLE) is a complex neurological disorder that has been recognized as a widespread global network disorder. The group-level structural covariance network (SCN) could reveal the structural connectivity disruption of the mTLE but could not reflect the heterogeneity at the individual level. Methods: This study adopted a recently proposed individual structural covariance network (IDSCN) method to clarify the alternated structural covariance connection mode in mTLE and to associate IDSCN features with the clinical manifestations and regional brain atrophy. Results: We found significant IDSCN abnormalities in the ipsilesional hippocampus, ipsilesional precentral gyrus, bilateral caudate, and putamen in mTLE patients than in healthy controls. Moreover, the IDSCNs of these areas were positively correlated with the gray matter atrophy rate. Finally, we identified several connectivities with weak associations with disease duration, frequency, and surgery outcome. Significance: Our research highlights the role of hippo-thalamic-basal-cortical circuits in the pathophysiologic process of disrupted whole-brain morphological covariance networks in mTLE, and builds a bridge between brain-wide covariance network changes and regional brain atrophy.

EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.

Background: At the intersection of neural monitoring and decoding, event-related potential (ERP) based on electroencephalography (EEG) has opened a window into intrinsic brain function. The stability of ERP makes it frequently employed in the field of neuroscience. However, project-specific custom code, tracking of user-defined parameters, and the large diversity of commercial tools have limited clinical application. Methods: We introduce an open-source, user-friendly, and reproducible MATLAB toolbox named EPAT that includes a variety of algorithms for EEG data preprocessing. It provides EEGLAB-based template pipelines for advanced multi-processing of EEG, magnetoencephalography, and polysomnogram data. Participants evaluated EEGLAB and EPAT across 14 indicators, with satisfaction ratings analyzed using the Wilcoxon signed-rank test or paired t-test based on distribution normality. Results: EPAT eases EEG signal browsing and preprocessing, EEG power spectrum analysis, independent component analysis, time-frequency analysis, ERP waveform drawing, and topological analysis of scalp voltage. A user-friendly graphical user interface allows clinicians and researchers with no programming background to use EPAT. Conclusion: This article describes the architecture, functionalities, and workflow of the toolbox. The release of EPAT will help advance EEG methodology and its application to clinical translational studies.

The Interplay Between Epilepsy and Parkinson's Disease: Gene Expression Profiling and Functional Analysis.

The results of many epidemiological studies suggest a bidirectional causality may exist between epilepsy and Parkinson's disease (PD). However, the underlying molecular landscape linking these two diseases remains largely unknown. This study aimed to explore this possible bidirectional causality by identifying differentially expressed genes (DEGs) in each disease as well as their intersection based on two respective disease-related datasets. We performed enrichment analyses and explored immune cell infiltration based on an intersection of the DEGs. Identifying a protein-protein interaction (PPI) network between epilepsy and PD, and this network was visualised using Cytoscape software to screen key modules and hub genes. Finally, exploring the diagnostic values of the identified hub genes. NetworkAnalyst 3.0 and Cytoscape software were also used to construct and visualise the transcription factor-micro-RNA regulatory and co-regulatory networks, the gene-microRNA interaction network, as well as gene-disease association. Based on the enrichment results, the intersection of the DEGs mainly revealed enrichment in immunity-, phosphorylation-, metabolism-, and inflammation-related pathways. The boxplots revealed similar trends in infiltration of many immune cells in epilepsy and Parkinson's disease, with greater infiltration in patients than in controls. A complex PPI network comprising 186 nodes and 512 edges were constructed. According to node connection degree, top 15 hub genes were considered the kernel targets of epilepsy and PD. The area under curve values of hub gene expression profiles confirmed their excellent diagnostic values. This study is the first to analyse the molecular landscape underlying the epidemiological link between epilepsy and Parkinson's disease. The two diseases are closely linked through immunity-, inflammation-, and metabolism-related pathways. This information was of great help in understanding the pathogenesis, diagnosis, and treatment of the diseases. The present results may provide guidance for further in-depth analysis about molecular mechanisms of epilepsy and PD and novel potential targets.

An EEG motor imagery dataset for brain computer interface in acute stroke patients.

The brain-computer interface (BCI) is a technology that involves direct communication with parts of the brain and has evolved rapidly in recent years; it has begun to be used in clinical practice, such as for patient rehabilitation. Patient electroencephalography (EEG) datasets are critical for algorithm optimization and clinical applications of BCIs but are rare at present. We collected data from 50 acute stroke patients with wireless portable saline EEG devices during the performance of two tasks: 1) imagining right-handed movements and 2) imagining left-handed movements. The dataset consists of four types of data: 1) the motor imagery instructions, 2) raw recording data, 3) pre-processed data after removing artefacts and other manipulations, and 4) patient characteristics. This is the first open dataset to address left- and right-handed motor imagery in acute stroke patients. We believe that the dataset will be very helpful for analysing brain activation and designing decoding methods that are more applicable for acute stroke patients, which will greatly facilitate research in the field of motor imagery-BCI.

IDH1 mutation predicts seizure occurrence and prognosis in lower-grade glioma adults.

Epileptic seizures are frequently the first symptom in glioma patients. However, the causal relationship between glioma and epilepsy is not yet fully understood, as it cannot be explained solely by tumor mass effect or peritumoral factors. In this study, we retrospectively enrolled 320 patients with grade 2-4 glioma who received treatment between January 2019 and July 2022, and explored the biomarkers of seizure occurrence and seizure outcome prediction using univariate and multivariate logistic regression analyses. Our results showed that IDH1 R132H mutation was an independent risk factor for seizure occurrence in lower-grade glioma (LGG) patients (OR = 4.915, 95%CI = 1.713 - 14.103, P = 0.003). Additionally, IDH1 R132H mutation predicted higher seizure-free ratios in LGG patients with intact ATRX expression (OR = 6.793, 95%CI = 1.217 - 37.923, P = 0.029) one year after diagnosis. Therefore, our findings suggest that IDH1 mutation can predict seizure occurrence and control in LGG patients, providing further insights into the relationship between glioma and epilepsy.

Structural and functional changes in the brain after chronic complete thoracic spinal cord injury.

This study aimed to investigate whether brain anatomical structures and functional network connectivity are altered after chronic complete thoracic spinal cord injury (cctSCI) and to determine how these changes impact clinical outcomes. Structural and resting-state functional MRI was performed for 19 cctSCI patients (18 for final statistics) and 19 healthy controls. Voxel-based morphometry (VBM) was used to assess gray matter volume (GMV) with differences between cctSCI patients and controls. VBM results were used as seeds for whole-brain functional connectivity (FC) analysis. The relationship between brain changes and clinical variables was investigated. Compared with those of the control group, the left triangular inferior frontal gyrus, middle frontal gyrus, orbital inferior frontal gyrus, precuneus and parietal superior gyrus volumes of SCI patients decreased, while the left superior frontal gyrus and supplementary motor area volumes increased. Additionally, when the regions with increased GMV were used as seeds, the FC of the parahippocampus and thalamus increased. Subsequent partial correlation analysis showed a positive correlation between FC and total sensorimotor score based on the ASIA criteria (p = 0.001, r = 0.746). Overall, the structural and functional changes in the brain after cctSCI occurred in some visual and cognitive areas and sensory or motor control areas. These findings aid in improving our understanding of the underlying brain injury mechanisms and the subsequent structural and functional reorganization to reveal potential therapeutic targets and track treatment outcomes.

Stereo-electroencephalography-guided three-dimensional radiofrequency thermocoagulation for mesial temporal lobe epilepsy with hippocampal sclerosis: A retrospective study with long-term follow-up.

OBJECTIVE: Stereo-electroencephalography-guided three-dimensional radiofrequency thermocoagulation (SEEG-3D RFTC) is a minimally invasive treatment for mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). This study aimed to investigate the long-term prognosis after SEEG-3D RFTC treatment in patients with MTLE-HS. METHODS: This single-center retrospective study included 28 patients with MTLE-HS treated with SEEG-3D RFTC from January 2016 to May 2018. Postoperative curative effects were evaluated using the Engel classification, and the patients were followed up for 5 years. RESULTS: The proportions of patients categorized as Engel I between 1 and 5 years after surgery were 72.41% (12 months after surgery), 67.86% (18 months after surgery), 62.07% (24 months after surgery), 50.00% (36 months after surgery), 42.86% (48 months after surgery), and 42.86% (60 months after surgery), respectively. Regarding long-term efficacy, based on the Engel classification, SEEG-3D RFTC showed room for improvement. SIGNIFICANCE: This was the first study to evaluate the efficacy of SEEG-3D RFTC for MTLE-HS with long-term follow-up. SEEG-3D RFTC is a promising alternative for patients with MTLE-HS. PLAIN LANGUAGE SUMMARY: This study explored the potential of stereoelectroencephalography-guided three-dimensional radiofrequency thermocoagulation, a minimally invasive approach, for treating medial temporal lobe epilepsy with hippocampal sclerosis. Involving 28 patients, the research tracked the treatment's success over five years using the Engel classification. Initial results were promising, with 72.41% of patients achieving the most favorable outcome (Engel I) at one year. While there was a gradual decrease in this proportion over time, 42.86% of patients maintained this positive outcome at five years, highlighting the treatment's potential for long-term efficacy.

A bibliometric and knowledge-map analysis of the glymphatic system from 2012 to 2022.

Objective: To explore the development context, research hotspots and frontiers in the glymphatic system (GS) field from 2012 to 2022 by bibliometric analysis. Methods: The Web of Science Core Collection (WoSCC) database was searched for articles published between 2012 and 2022. Microsoft Excel was used to manage the data. VOSviewer, CiteSpace, GraphPad Prism, the Web of Science, and an online analysis platform for bibliometrics (http://bibliometric.com/) were used to analyze the countries, institutions, journals, and collaboration networks among authors and the types of articles, developmental directions, references, and top keywords of published articles. Results: A total of 412 articles were retrieved, including 39 countries/regions, 223 research institutes and 171 academic journals. The subject classifications related to the GS were Neuroscience, Clinical Neuroscience and Radiology/Nuclear Medicine/Medical Imaging. The United States has maintained its dominant and most influential position in GS research. Among research institutions and journals, the Univ Rochester and Journal of Cerebral Blood Flow and Metabolism had the highest number of academic articles, respectively. Nedergaard M had the most published article, and Iliff JJ had the most co-citations. The top two keywords with the highest frequency were "glymphatic system" and "cerebrospinal fluid." Conclusion: This research provides valuable information for the study of the GS. The bibliometric analysis of this area will encourage potential collaborations among researchers, defining its frontiers and directions for development.

Short-term surgical outcomes of spontaneous intracerebral hemorrhage in China from 2019 to 2021: a retrospective cohort study.

Background: China has the highest prevalence of spontaneous intracerebral hemorrhage (sICH) worldwide. To date, no national-level report has revealed sICH surgical performance. We aimed to investigate the current status and short-term outcomes of patients who underwent surgical treatment for sICH between 2019 and 2021. Methods: Data from 7451 patients undergoing sICH surgical treatment in China between 2019 and 2021, including demographic information, disease severity, surgical treatments for sICH, complications, and follow-up information, were retrieved from the Bigdata Observatory Platform for Stroke of China. Propensity score matching (PSM) was applied to balance the baseline characteristics. The surgical treatment performance on 3-month mortality and functional outcome were then explored by regression analysis. The influence of stroke center level and region on surgical performance was then explored. Findings: The numbers of sICH patients undergoing open craniotomy (OC), cranial puncture (CP), decompressive craniectomy (DC) and endoscopic evacuation (EE) were 2404 (32.3%), 3030 (40.7%), 1700 (22.8%) and 317 (4.3%), respectively. The 3-month mortality rate was 20.2%. Among the surviving patients, the 3-month poor functional prognosis (mRS 3-5) rate was 46.5%. After PSM, regression analysis showed that DC was associated with a higher mortality risk (OR = 1.31, 95% CI 1.06-1.61) than OC. CP was associated with a lower risk of poor mRS scores than OC (OR = 0.84, 95% CI 0.70-1.01), especially in stroke prevention centers and specific regions. Interpretation: Outcome improvements in Chinese sICH patients undergoing surgical treatment are worth expecting. Inconsistent surgical performance, especially functional outcome, affected by inhomogeneity of the hospital should be addressed. Funding: This work was supported by the Beijing Hospitals Authority Youth Programme (QML20230804), the National Natural Science Foundation of China (81701796, 82030037, 81871009), Capital Health Research and Development of Special Fund (2020-2Z-2019), Science and Technology Innovation 2030-Major Project (2021ZD0201801), and the Translational and Application Project of Brain-inspired and Network Neuroscience on Brain Disorders (11000022T000000444685).

Advances in hypothalamic hamartoma research over the past 30 years (1992-2021): a bibliometric analysis.

Background: Hypothalamic hamartoma (HH) is a rare intracranial disease whose manifestations include gelastic seizures and precocious puberty. The diagnosis and treatment of HH have changed substantially over the past three decades as medical care has improved. Bibliometrics can reveal the evolution and development of a scientific field. Methods: Documents on HH were retrieved from the Web of Science Core Collection (WoSCC) database on September 8, 2022. The search terms were as follows: "hypothalamic hamartoma" or "hamartoma of the hypothalamus" or "hypothalamic hamartomas." The types of documents were restricted to articles, case reports, and reviews. VOSviewer, CiteSpace, and the R package "bibliometrix" were used for a bibliometric analysis. Results: A total of 667 independent documents on HH were obtained from the WoSCC database. The most common types of documents were articles (n = 498, 75%) and reviews (n = 103, 15%). The number of annual publications fluctuated but showed an upward trend overall, and the annual growth rate was 6.85%. The cumulative publication data indicated that the most influential journals in the HH field include Epilepsia, Epileptic Disorders, Child's Nervous System, Neurosurgery, and the Journal of Neurosurgery. Kerrigan JF, Ng YT, Rekate HL, Regis J, and Kameyama S were among the most prominent authors in the field of HH, with numerous publications and citations. American research institutions, especially the Barrow Neurological Institute, occupied a pivotal position in HH research. Other countries and institutions were catching up and producing considerable research results. Research on HH has steadily switched its emphasis from Pallister-Hall syndrome (PHS) and precocious puberty to epilepsy and new diagnostic and therapeutic techniques, including Gamma Knife, laser ablation, and interstitial thermal therapy. Conclusion: HH remains a special neurological disease with significant research prospects. The development of novel technologies, including MRI-guided laser-induced thermal therapy (MRg-LiTT) and stereotactic radiofrequency thermocoagulation (RF-TC), has enabled the efficient treatment of gelastic seizures in HH while minimizing the risks associated with craniotomies. Through bibliometric analysis, this study points out the direction for future HH research.

Intracranial electrophysiological and structural basis of BOLD functional connectivity in human brain white matter.

While functional MRI (fMRI) studies have mainly focused on gray matter, recent studies have consistently found that blood-oxygenation-level-dependent (BOLD) signals can be reliably detected in white matter, and functional connectivity (FC) has been organized into distributed networks in white matter. Nevertheless, it remains unclear whether this white matter FC reflects underlying electrophysiological synchronization. To address this question, we employ intracranial stereotactic-electroencephalography (SEEG) and resting-state fMRI data from a group of 16 patients with drug-resistant epilepsy. We find that BOLD FC is correlated with SEEG FC in white matter, and this result is consistent across a wide range of frequency bands for each participant. By including diffusion spectrum imaging data, we also find that white matter FC from both SEEG and fMRI are correlated with white matter structural connectivity, suggesting that anatomical fiber tracts underlie the functional synchronization in white matter. These results provide evidence for the electrophysiological and structural basis of white matter BOLD FC, which could be a potential biomarker for psychiatric and neurological disorders.

Nuclear lamina erosion-induced resurrection of endogenous retroviruses underlies neuronal aging.

The primate frontal lobe (FL) is sensitive to aging-related neurocognitive decline. However, the aging-associated molecular mechanisms remain unclear. Here, using physiologically aged non-human primates (NHPs), we depicted a comprehensive landscape of FL aging with multidimensional profiling encompassing bulk and single-nucleus transcriptomes, quantitative proteome, and DNA methylome. Conjoint analysis across these molecular and neuropathological layers underscores nuclear lamina and heterochromatin erosion, resurrection of endogenous retroviruses (ERVs), activated pro-inflammatory cyclic GMP-AMP synthase (cGAS) signaling, and cellular senescence in post-mitotic neurons of aged NHP and human FL. Using human embryonic stem-cell-derived neurons recapitulating cellular aging in vitro, we verified the loss of B-type lamins inducing resurrection of ERVs as an initiating event of the aging-bound cascade in post-mitotic neurons. Of significance, these aging-related cellular and molecular changes can be alleviated by abacavir, a nucleoside reverse transcriptase inhibitor, either through direct treatment of senescent human neurons in vitro or oral administration to aged mice.

PMotion: an advanced markerless pose estimation approach based on novel deep learning framework used to reveal neurobehavior.

Objective.The evaluation of animals' motion behavior has played a vital role in neuromuscular biomedical research and clinical diagnostics, which reflects the changes caused by neuromodulation or neurodamage. Currently, the existing animal pose estimation methods are unreliable, unpractical, and inaccurate.Approach.Data augmentation (random scaling, random standard deviation Gaussian blur, random contrast, and random uniform color quantization) is adopted to augment image dataset. For the key points recognition, we present a novel efficient convolutional deep learning framework (PMotion), which combines modified ConvNext using multi-kernel feature fusion and self-defined stacked Hourglass block with SiLU activation function.Main results.PMotion is useful to predict the key points of dynamics of unmarked animal body joints in real time with high spatial precision. Gait quantification (step length, step height, and joint angle) was performed for the study of lateral lower limb movements with rats on a treadmill.Significance.The performance accuracy of PMotion on rat joint dataset was improved by 1.98, 1.46, and 0.55 pixels compared with deepposekit, deeplabcut, and stacked hourglass, respectively. This approach also may be applied for neurobehavioral studies of freely moving animals' behavior in challenging environments (e.g.Drosophila melanogasterand openfield-Pranav) with a high accuracy.

Integrative roles of human amygdala subdivisions: Insight from direct intracerebral stimulations via stereotactic EEG.

Substantial studies of human amygdala function have revealed its importance in processing emotional experience, autonomic regulation, and sensory information; however, the neural substrates and circuitry subserving functions have not been directly mapped at the level of the subnuclei in humans. We provide a useful overview of amygdala functional characterization by using direct electrical stimulation to various amygdala regions in 48 patients with drug-resistant epilepsy undergoing stereoelectroencephalography recordings. This stimulation extends beyond the anticipated emotional, neurovegetative, olfactory, and somatosensory responses to include visual, auditory, and vestibular sensations, which may be explained by the functional connectivity with cortical and subcortical regions due to evoked amygdala-cortical potentials. Among the physiological symptom categories for each subnucleus, the most frequently evoked neurovegetative symptoms were distributed in almost every subnucleus. Laterobasal subnuclei are mainly associated with emotional responses, somatosensory responses, and vestibular sensations. Superficial subnuclei are mainly associated with emotional responses and olfactory and visual hallucinations. Our findings contribute to a better understanding of the functional architecture of the human amygdala at the subnuclei level and as a mechanistic basis for the clinical practice of amygdala stimulation in treating patients with neuropsychiatric disorders.

Long-term follow-up seizure outcomes after corpus callosotomy: A systematic review with meta-analysis.

BACKGROUND: Corpus callosotomy (CC) is appropriate for patients with seizures of a bilateral or diffuse origin, or those with seizures of a unilateral origin with rapid spread to the contralateral cerebral hemisphere. The efficiency of CC in patients with drug-resistant epilepsy is a long-term concern because most articles reporting the surgical results of CC arise from small case series, and the durations of follow-up vary. METHODS: PubMed, Embase, Cochrane Library, and Web of Science were searched to identify papers published before November 8, 2021. The systematic review was completed following PRISMA guidelines. Outcomes were analyzed by meta-analysis of the proportions. RESULTS: A total of 1644 patients with drug-resistant epilepsy (49 retrospective or prospective case series studies) underwent CC, and the follow-up time of all patients was at least 1 year. The rate of complete seizure freedom (SF) was 12.38% (95% confidence interval [CI], 8.17%-17.21%). Meanwhile, the rate of complete SF from drop attacks was 61.86% (95% CI, 51.87%-71.41%). The rates of complete SF after total corpus callosotomy (TCC) and anterior corpus callosotomy (ACC) were 11.41% (95% CI, 5.33%-18.91%) and 6.75% (95% CI, 2.76%-11.85%), respectively. Additionally, the rate of complete SF from drop attacks after TCC was significantly higher than that after ACC (71.52%, 95% CI, 54.22%-86.35% vs. 57.11%, 95% CI, 42.17%-71.49%). The quality of evidence for the three outcomes by GRADE assessment was low to moderate. CONCLUSION: There was no significant difference in the rate of complete SF between TCC and ACC. TCC had a significantly higher rate of complete SF from drop attacks than did ACC. Furthermore, CC for the treatment of drug-resistant epilepsy remains an important problem for further investigation because there are no universally accepted standardized guidelines for the extent of CC and its benefit to patients. In future research, we will focus on this issue.

The role of the orbitofrontal cortex and insula for prognosis of mesial temporal lobe epilepsy.

OBJECTIVE: We investigated the network between the medial temporal lobe (MTL) and extratemporal structures in patients with mesial temporal lobe epilepsy (MTLE) in order to explain the recurrence of MTLE after surgery. This study contributes to our current understanding of MTLE with stereotactic electroencephalography (SEEG). METHODS: We conducted a retrospective study of SEEG in 20 patients with MTLE in order to observe and analyze the intensity of interictal high-frequency oscillations (HFOs), as well as the dynamic course of coherence connectivity values of the MTL and extratemporal structures during the initial phase of the seizure. The results correlated with the patient prognosis. RESULTS: First, the presence of HFOs was observed during the interictal period in all 20 patients; these were localized to the MTL in 17 patients and the orbitofrontal cortex in seven patients and the insula in six patients. The better the prognosis, the greater the localization of the HFOs concentration in the MTL structures (p < 0.05). Second, significantly enhanced connectivity of MTL structures with the orbitofrontal cortex and insula was observed in most patients with MTLE, before and after the seizure onset (p < 0.05). Finally, the connectivity between extratemporal structures, such as the orbitofrontal cortex and insula, and MTL structures was significantly stronger in patients who had a worse prognosis than in other patients, before and after seizure onset (p < 0.05). INTERPRETATION: The epileptogenic network in recurrent MTLE is not limited to MTL structures but is also associated with the orbitofrontal cortex and insula. This can be used as a potential indicator for predicting the prognosis of patients after surgery, providing an important avenue for future clinical evaluation.