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Periventricular nodular heterotopia (PVNH) is a well-defined developmental disorder characterized by failed neuronal migration, which forms ectopic neuronal nodules along the ventricular walls. Previous studies mainly focus on clinical symptoms caused by the PVNH tissue, such as seizures. However, little is known about whether and how neurons in the PVNH tissue functionally communicate with neurons in the neocortex. To probe this, we applied magnetoencephalography (MEG) and stereo-electroencephalography (sEEG) recordings to patients with PVNH during resting and task states. By estimating frequency-resolved phase coupling strength of the source-reconstructed neural activities, we found that the PVNH tissue was spontaneously coupled with the neocortex in the α–β frequency range, which was consistent with the synchronization pattern within the neocortical network. Furthermore, the coupling strength between PVNH and sensory areas effectively modulated the local neural activity in sensory areas. In both MEG and sEEG visual experiments, the PVNH tissue exhibited visual-evoked responses, with a similar pattern and latency as the ipsilateral visual cortex. These findings demonstrate that PVNH is functionally integrated into cognition-related cortical circuits, suggesting a co-development perspective of ectopic neurons after their migration failure.

Periventricular nodular heterotopia (PVNH) is a well-defined developmental disorder characterized by failed neuronal migration, which forms ectopic neuronal nodules along the ventricular walls. Previous studies mainly focus on clinical symptoms caused by the PVNH tissue, such as seizures. However, little is known about whether and how neurons in the PVNH tissue functionally communicate with neurons in the neocortex. To probe this, we applied magnetoencephalography (MEG) and stereo-electroencephalography (sEEG) recordings to patients with PVNH during resting and task states. By estimating frequency-resolved phase coupling strength of the source-reconstructed neural activities, we found that the PVNH tissue was spontaneously coupled with the neocortex in the α to β frequency range, which was consistent with the synchronization pattern within the neocortical network. Furthermore, the coupling strength between PVNH and sensory areas effectively modulated the local neural activity in sensory areas. In both MEG and sEEG visual experiments, the PVNH tissue exhibited visual evoked responses, with a similar pattern and latency as the ipsilateral visual cortex. These findings demonstrate that PVNH is functionally integrated into cognition-related cortical circuits, suggesting a co-development perspective of ectopic neurons after their migration failure.

The mechanisms underlying the anterior nucleus of the thalamus (ANT) deep brain stimulation (DBS) for the treatment of drug-resistant epilepsy (DRE) have not been fully explored. The present study aimed to measure the changes in whole-brain activity generated by ANT DBS using interictal electroencephalography (EEG).Interictal EEG signals were retrospectively collected in 20 DRE patients who underwent ANT DBS surgery. Patients were classified as responders or non-responders depending on their response to ANT DBS treatment. The power spectrum (PS) and Phase Lag Index (PLI) were determined and data analyzed using a paired sample t-test to evaluate activity differences between pre-and-post-treatment on different frequency categories. Student's t-test, Mann-Whitney test (non-parametric test) and Fisher exact test were used to compare groups in terms of clinical variables and EEG metrics. P values0.05 were considered statistically significant, and FDR-corrected values were used for multiple testing.PS analysis revealed that whole-brain spectral power had a significant decrease in the beta (p = 0.005) and gamma (p = 0.037) bands following ANT DBS treatment in responders. The analysis of scalp topographic images of all patients showed that ANT DBS decreases PS in the beta band at the F3, F7 and Cz electrode sites. The findings indicated a decrease in PS in the gamma band at the Fp2, F3, Cz, T3, T5 and Oz electrode sites. After ANT DBS treatment, PLI analysis showed a significant decrease in PLI between Fp1 and T3 in the gamma band in responders.The findings showed that ANT DBS induces a decrease in power in the left frontal lobe, left temporal lobe and midline areas in the beta and gamma bands. Lower whole-brain power in the beta and gamma bands can be used as biomarkers for a favorable therapeutic response to ANT DBS, and decreased synchronization between the left frontal pole and temporal lobe in the gamma band can also be used as a biomarker for effective clinical stimulation to guide postoperative programming.

To analyze the impact of magnetoencephalography (MEG) results on surgical outcomes in patients with drug-resistant epilepsy secondary to encephalomalacia. We retrospectively reviewed 121 patients with drug-resistant epilepsy associated with encephalomalacia who underwent MEG followed by resection surgery. Patients were subdivided into concordant MEG group and dis-concordant MEG group for analysis based on whether the MEG results were in concordance with epileptogenic zones or not. 121 patients were included in the present study. The MEG spike sources of 73 (60.33%) patients were in concordance with epileptogenic zones while the MEG spike sources of the other 48 (39.67%) were in dis-concordance with epileptogenic zones. Favorable seizure outcomes were achieved in 79.45% (58 of 73) of patients with concordant MEG results while only 62.50% (30 of 48) of patients with dis-concordant MEG results were seizure free with a follow-up of 2–10 years. The differences of seizure-free rate between patients with concordant MEG results and dis-concordant MEG results were statistically significant. For patients with concordant MEG results, bilateral lesions on MRI are the only independent predictor of unfavorable seizure outcomes. For patients with discordant MEG results, duration of seizures is the only independent predictor of unfavorable seizure outcomes. Concordant MEG results are associated with favorable seizure outcomes. Bilateral lesions on MRI independently predict unfavorable seizure outcomes in patients with concordant MEG results while longer seizure durations independently predict unfavorable seizure outcomes in patients with dis-concordant MEG results.

To identify prognostic factors and long-term seizure outcomes for patients with tuberous sclerosis complex (TSC) who underwent resective treatment for epilepsy.We enrolled 81 patients with TSC who had undergone resective epilepsy surgery at Sanbo Brain Hospital, Capital Medical University, between April 2004 and June 2019. We estimated cumulative probability of remaining seizure-free and plotted survival curves. Variables were compared using Mann-Whitney U, Pearson's correlation, continuity correction, and Fisher's exact chi-square tests. Prognostic predictors were analysed using log-rank (Mantel-Cox) tests and Cox regression models.At the last follow-up, 48 (59.3%) patients were classified as International League Against Epilepsy Class 1 (including 14 patients who had seizures3 times postoperatively on the same or different day and were seizure-free at all other times). The estimated cumulative probability of remaining seizure-free postoperatively was 69.0% (95% confidence interval [CI] 58.8-79.2%), 61.9% (95% CI 51.1-72.7%), and 55.0% (95% CI 42.8-67.2%) at 2, 5, and 10 years, respectively. The mean time of remaining seizure-free was 7.24 ± 0.634 years (95% CI 6.00-8.49); en bloc resection was an essential positive predictor of postoperative seizure freedom, as was age at seizure onset, regional interictal video-electroencephalography pattern, and temporal lobe surgery. The longer the seizure-free time, the less likely a relapse. Patients who postoperatively experienced seizures remained likely to recover.We demonstrated the efficacy of surgical treatment for patients with TSC and intractable epilepsy. Detailed perioperative tests are a reliable predictor of postoperative seizure freedom.

The human auditory sensory area, which includes primary and non-primary auditory cortices, has been considered to locate in the supra-temporal lobe for more than a century. Recently, accumulating evidence shows that the posterior part of insula responses to sounds under non-task states with relevant short latencies. However, whether posterior insula (InsP) contribute to forming auditory sensation remains unclear. Here we addressed this issue by recording and stimulation directly on the supra-temporal and insular areas via intracranial electrodes from 53 epileptic patients. During passive listening to a non-speech sound, the high-γ (60-140 Hz) active rate of InsP (68.8%) was approximate to the non-primary auditory areas (72.4% and 79.0%). Moreover, we could not distinguish InsP from supra-temporal subareas by either activation, latency, temporal pattern or lateral dominance of sound induce high-γ. On the contrary, direct electrical stimulation evoked auditory sensations effectively on supra-temporal subareas (> 65%), while sparsely on InsP (9.49%). The results of cortico-cortical evoked potentials (CCEPs) showed strong bidirectional connectivity within supra-temporal areas, but weak connectivity between supra-temporal areas and InsP. These findings suggest that even the InsP has similar basic auditory response properties to the primary or non-primary cortex, it may not directly participate in the formation of auditory perception.

This study investigated the dynamic and long-term efficacy of vagus nerve stimulation (VNS) in patients with drug-resistant epilepsy (DRE) induced by tuberous sclerosis complex (TSC). In addition, the impact of VNS on cognition and emotion after a one-year follow-up was evaluated.A total of 17 patients diagnosed with DRE induced by TSC were retrospectively recruited between 2008 and 2019. Dynamic changes in seizure frequency were observed in the responders (≥50% reduction of seizure frequency at last follow-up) and non-responders. Clinical characteristics and seizure outcomes were comprehensively analyzed to determine factors associated with seizure outcomes. The Wechsler intelligence scale was applied in a subgroup of six pediatric patients, whereas the Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS) were assessed in a subgroup of nine patients to determine the impact of VNS therapy on cognitive performance and emotional state.The follow-up duration for the 17 patients who underwent VNS treatment ranged from 0.5 to 10 years (mean ± SD: 4.1 ± 3.2 years). Monthly seizures decreased significantly from three months to four years post-treatment (p 0.05). At the last follow-up, 70.6% of the patients achieved at least a 50% reduction in seizure frequency, and three patients were completely seizure free. Comparatively, non-responder patients experienced deterioration of seizure frequency after the first year. Notably, after one-year follow-up the mean standard score of full-scale intelligence quotient increased from 67.33 to 69.5 (p = 0.078) while the mean, standard score of SDS decreased from 49.22 to 45.67 (p = 0.003) compared to preoperative neuropsychological evaluation results.VNS is a safe and effective treatment for patients with DRE caused by TSC. Although early outcomes were encouraging, a follow-up of at least one-year was required to predict long-term outcomes in patients receiving VNS treatment. Moreover, VNS may improve depressive mood in patients with DRE caused by TSC. Further investigations are needed to validate the present results.

Epilepsy is a neurological disorder characterized by sudden and unpredictable epileptic seizures, which incurs significant negative impacts on patients’ physical, psychological and social health. A practical approach to assist with the clinical assessment and treatment planning for patients is to process magnetoencephalography (MEG) data to identify epileptogenic zones. As a widely accepted biomarker of epileptic foci, epileptic MEG spikes need to be precisely detected. Given that the visual inspection of spikes is time consuming, an automatic and efficient system with adequate accuracy for spike detection is valuable in clinical practice. However, current approaches for MEG spike autodetection are dependent on hand-engineered features. Here, we propose a novel multiview Epileptic MEG Spikes detection algorithm based on a deep learning Network (EMS-Net) to accurately and efficiently recognize the spike events from MEG raw data. The results of the leave-k-subject-out validation tests for multiple datasets (i.e., balanced and realistic datasets) showed that EMS-Net achieved state-of-the-art classification performance (i.e., accuracy: 91.82% – 99.89%; precision: 91.90% – 99.45%; sensitivity: 91.61% – 99.53%; specificity: 91.60% – 99.96%; f1 score: 91.70% – 99.48%; and area under the curve: 0.9688 – 0.9998).