EEG Discharges Research Articles

Secondary bilateral synchronization of interictal EEG discharges in focal epilepsy: prevalence and associated factors

BackgroundEpilepsy is commonly categorized based on etiology, treatment, and prognosis. Misclassification can occur due to the presence of interictal secondary bilateral synchronization (SBS) discharges seen on an electroencephalogram (EEG), misleading the classification process.ObjectiveTo examine the prevalence of interictal SBS discharges in patients with focal epilepsy and to identify predictors of these discharges.DesignRetrospective analysis of patients who underwent long-term video EEG monitoring (LTVEM) from August 2001 to May 2014.MethodsWe included patients with focal epilepsy. The patients were divided into two groups based on whether or not they had SBS discharges.ResultsWe found 1,017 patients who underwent LTVEM. Of the 221 patients included in the final analysis, 36 (16%) exhibited SBS discharges. Patients in the SBS group were younger and had an earlier onset age of epilepsy. They also had higher rates of unclear seizure onset zone and focal to bilateral tonic–clonic seizures. In the binary logistic regression analysis, young onset age of epilepsy was the only significant factor.ConclusionThe prevalence of SBS discharges in focal epilepsy is relatively high (16%), emphasizing the importance of cautious interpretation of interictal EEG in epilepsy classification. Young age of disease onset is associated with higher rates of SBS.

EEG Abnormalities and Phenotypic Correlates in Preschoolers with Autism Spectrum Disorder: A Single-Center Study.

Background: The literature suggests the existence of an association between autism spectrum disorders (ASDs) and subclinical electroencephalographic abnormalities (SEAs), which show a heterogeneous prevalence rate (12.5-60.7%) within the pediatric ASD population. The aim of this study was to investigate the EEG findings in a cohort of ASD preschoolers and their correlation with the phenotypic characteristics. Methods: We retrospectively reviewed data on 141 ASD preschoolers evaluated in a tertiary care university hospital over the period 2008-2018. All participants underwent at least one standard polygraphic electroencephalogram (EEG) and a clinical multidisciplinary assessment with standardized instruments. Results: 77 patients (55%) showed SEAs, which were mainly represented by epileptiform discharges (p < 0.00001), especially focal and multifocal (p = 0.010). Abnormal EEG (p = 0.035) and epileptiform discharges (p = 0.014) were associated with seizure onset and were predominant in sleep (p < 0.00001). Patients with abnormal tracing (p = 0.031) and slow abnormalities (p < 0.001) were significantly younger. ASD severity was not found to be correlated with EEG results, which showed a potential, albeit non-significant, association with some psychometric parameters. Very similar results were found when patients were divided according to sex. Conclusions: EEG abnormalities appear to correlate more with ASD internalizing, externalizing and emotional comorbidities, rather than with ASD core symptoms; larger samples are needed to further investigate this association.

Subclinical rhythmic EEG discharge of adults (SREDA) in pediatric population: A case series with systematic review of the literature.

Subclinical rhythmic electrographic discharge of adults (SREDA) is one of the rarest and most challenging non-epileptic electroencephalographic variants. Although the pathogenesis of this activity is unclear, an association with vascular insufficiency and cerebral hypoxia has been proposed. SREDA usually occurs in adulthood, but there are few reports in the pediatric population. We performed a systematic review of the literature, confirming the rarity of this condition in children, and added 5 more subjects. We report on a total of 16 children with SREDA. Sufficient data are available for 15 patients. The mean age at first detection of SREDA was 11.5 years. We observed that 67% (10/15) of the subjects had previous seizures: 80% (8/10) of them had an epilepsy diagnosis and 38% (3/8) had generalized epilepsy. Moreover, 8 of 13 subjects whose medical history was available (61%) had a neurodevelopmental disorder. From an electroencephalographic point of view, we noted a prevalence of bilateral SREDA with atypical localization and abrupt onset and end. Since SREDA can be incorrectly interpreted as an epileptic discharge, with possible therapeutic implications, it is important to consider its possible occurrence also in pediatric patients, perhaps more frequently in those with neurodevelopmental disorders.

Development and validation of a nomogram for the estimation of the prognosis of patients presenting with a febrile seizure

BackgroundFebrile seizures constitute a prevalent emergency in early childhood. Previous studies indicated that certain febrile seizures in children may progress to epilepsy, exerting a substantial impact on children's health and developmental trajectory. The objective of this study was to formulate a predictive nomogram to assess the likelihood of transitioning from febrile seizures to epilepsy in pediatric patients, thereby facilitating informed decisions regarding medical interventions for febrile seizures.MethodsA total of 306 patients were enrolled and categorized into training (70%) and test (30%) cohorts. Clinical characteristics were subjected to comparison utilizing chi-squared and t tests. Multivariate logistic regression was employed to identify significant factors for predicting the risk of transitioning from febrile seizures to epilepsy, leading to the development of a nomogram. The nomogram’s performance was assessed through receiver operating characteristic curves, calibration, and decision curve analysis.ResultsPredictive factors associated with the transition to epilepsy encompassed lower Na, elevated RDW, IL-6, and increased background slow rhythm and epileptiform discharges in EEG. The nomogram, incorporating five factors, exhibited commendable predictive value (AUC train = 0.812, AUC test = 0.791) for assessing the risk of transitioning from febrile seizures to epilepsy. Calibration analyses confirmed reliability, and decision curve analysis underscored its clinical utility.ConclusionsLower Na, elevated RDW, IL-6, background slow rhythm, and epileptiform discharges are associated with the risk of transitioning from febrile seizures to epilepsy. The nomogram stands as a valuable tool for predicting this risk, aiding in the strategic implementation of medical interventions to enhance outcomes for patients with febrile seizures.

Clinical Spectrum and EEG Findings in Patients with Suspected Non-Convulsive Status Epilepticus

This study looked at the clinical spectrum as well as EEG results to help diagnose and treat patients with probable non-convulsive status epilepticus (NCSE). Patients were classified into two groups based on the degree of NCSE: mild to moderate and severe and their medical records revealed evidence of epilepsy in the form of rhythmic delta activity and localized slowing or widespread spike-and-wave (WSW) discharges in EEG. Severe NCSE was associated with increased antiepileptic drug use (90 vs 80%), longer treatment duration (10 vs 7days), and higher critical care unit admissions (40vs25%) (p&lt;0.05). EEG data showed a significant increase in the frequency of generalized spike-and-wave discharges (45 vs 30%) and localized slowing (32vs20%) (p&lt;0.05). Furthermore, these patients' neurological recovery was worse and they remained in the hospital longer. Finally, the severity of the NCSE and poor clinical outcomes were substantially linked to specific EEG patterns, especially localized slowing and WSW discharges.

Restricted Cortical Activity Involving Parietal Lobe and Sublobar Region Leads to Generalized Spike-Wave Discharges of Juvenile Myoclonic Epilepsy: Evidence from an EEG Source Localization Study.

Previous studies have localized the origin of "generalized" spike-wave discharges of idiopathic generalized epilepsies to specific brain regions. Although there are studies in juvenile myoclonic epilepsy (JME) which have investigated the origin of spike-wave discharges, reports on the propagation of discharges are sparse. The current study investigated the propagation of spike-wave discharges in JME, which was investigated by statistically comparing the electroencephalography (EEG)-derived cortical source activity during (a) various phases of spike-wave discharge versus background (eyes closed) activity, and (b) various phases of the first spike wave versus the corresponding phase of subsequent spike waves. Fourteen patients with JME who had generalized spike/polyspike and slow wave discharges in interictal EEG were included in the study. A total of 179 spike waves (first discernible spike wave - 55; subsequent spike waves - 124) were selected for source localization. Source analysis was carried out using exact low-resolution electromagnetic tomography (eLORETA). Statistical analyses to estimate the probability distribution of differences in cortical activity between (a) eight phases of epileptic discharge versus background (eyes closed) activity and (b) phases of the first spike wave versus the corresponding phases of subsequent spike waves were performed by paired t-tests and corrected for multiple testing using LORETA-KEY software. Widespread activation of cortical voxels (more than 94%) was observed during all phases of epileptic discharge except the initial phase (pre-first spike) and terminal phase (post-peak of the subsequent wave). The parietal lobe, which was the most activated lobe during the pre-first spike, was found to be the least activated during the post-peak of first and subsequent waves. More than 93% of voxels in the sublobar region were consistently activated during all eight phases of discharge. The study findings suggest that the activity generated from the restricted brain network involving parietal lobe could be propagated through sublobar structures to cause widespread cortical activation during the subsequent phases of the spike-wave cycle.

Postoperative EEG abnormalities in relation to neurodevelopmental outcomes after pediatric cardiac surgery.

We had reported that postoperative EEG background including sleep-wake cycle (SWC) and discharge (seizures, spikes/sharp waves) abnormalities were significantly correlated with adverse early outcomes in children after cardiac surgery. We aimed to analyze the relations between these EEG abnormalities and neurodevelopmental outcomes at about2 years after cardiac surgery. We enrolled 121 patients undergoing cardiac surgery at 3.3 months (0.03 ~ 28 months). EEG abnormalities described above during the first postoperative 48 h were evaluated. Griffiths Mental Development Scales-Chinese was used to evaluate the quotients of overall development and 5 subscales of the child's locomotor, language, personal-social, eye-hand coordination and performance skills at 16 ~ 31 months of age. EEG background abnormalities occurred in 59/121 (48.8%) patients and 33 (55.9%) unrecovered to normal by 48 h. Abnormal SWC occurred in 15 (12.4%) patients and 7 (5.8%) unrecovered to normal by 48 h. EEG seizures occurred in 11 (9.1%) patients with frontal lobe seizures in 4. Spikes/sharp waves occurred in 100 (82.6%). EEG background abnormalities, number of spikes/sharp waves and frontal lobe seizures were significantly associated with neurodevelopmental impairment at about 1 ~ 2 year after surgery (Ps ≤ 0.05). Most parameters of EEG abnormalities were significantly associated with neurodevelopmental impairment after cardiac surgery. Neurodevelopmental impairment in children with congenital heart disease remain poorly understood. Previous studies had reported that either EEG seizures or background abnormalities were associated with worse neurodevelopmental outcomes. Our present study showed that all the EEG background and discharge abnormalities including EEG background, seizures and spikes/sharp waves in the early postoperative period were significantly associated with neurodevelopmental impairment at about 1 ~ 2 years after cardiac surgery. Comprehensive evaluation of early postoperative EEG may provide further insights about postoperative brain injury, its relation with neurodevelopmental impairment, and guide to improve clinical management.

Benign epileptiform variants in EEG: A comprehensive study of 3000 patients

BackgroundThe analysis of EEG demands expertise and keen observation to distinguish epileptiform discharges from benign epileptiform variants (BEVs), a frequent source of erroneous interpretation. The prevalence of BEVs varies based on geographical, racial, and ethnic characteristics. However, most data on BEVs originates from Western populations, and additional studies on different cohorts would enrich the existing literature. MethodsWe reviewed EEGs from our institutional database to study the prevalence of benign epileptiform variants and analyzed their frequency, topography, and other characteristics. Additionally, we investigated the co-existence of epileptiform discharges with BEVs. ResultsWe identified 296 patients with BEVs after reviewing 3000 EEGs (9.9%). The most common BEV was small sharp spikes (SSS), observed in 114 patients (3.8%). Wicket waves, 6 Hz spike and slow wave, 14 and 6 Hz positive bursts, and Rhythmic Temporal Theta of Drowsiness (RTTD) were identified in 67 (2.2%), 40 (1.3%), 39 (1.3%), and 35 (1.16%) patients, respectively and one patient with Subclinical Rhythmic EEG Discharges in Adults (SREDA). Additionally, we observed the co-existence of epileptiform discharges with BEVs, most commonly with SSS (27.8%). ConclusionsThe present study is a large study with 3000 EEGs to describe the BEV characteristics. BEVs were seen in 9.9% of patients, BSSS being the most common. There were minor differences in frequency, gender or age distribution compared to existing literature. We demonstrated the co-existence of epileptiform discharges. Morphological characteristics remain the cornerstone in recognising BEVs. EEG readers need to be aware of features of BEVs to avoid wrongly interpretation.

Valine and Inflammation Drive Epilepsy in a Mouse Model of ECHS1 Deficiency.

ECHS1 Deficiency (ECHS1D) is a rare and devastating pediatric disease that currently has no defined treatments. This disorder results from missense loss-of-function mutations in the ECHS1 gene that result in severe developmental delays, encephalopathy, hypotonia, and early death. ECHS1 enzymatic activity is necessary for the beta-oxidation of fatty acids and the oxidation of branched-chain amino acids within the inner mitochondrial matrix. The pathogenesis of disease remains unknown, however it is hypothesized that disease is driven by an accumulation of toxic metabolites from impaired valine oxidation. To expand our knowledge on disease mechanisms, a novel mouse model of ECHS1D was generated that possesses a disease-associated knock-in (KI) allele and a knock-out (KO) allele. To investigate the behavioral phenotype, a battery of testing was performed at multiple time points, which included assessments of learning, motor function, endurance, sensory responses, and anxiety. Neurological abnormalities were assessed using wireless telemetry EEG recordings, pentylenetetrazol (PTZ) seizure induction, and immunohistochemistry. Metabolic perturbations were measured within the liver, serum, and brain using mass spectrometry and magnetic resonance spectroscopy. To test disease mechanisms, mice were subjected to disease pathway stressors and then survival, body weight gain, and epilepsy were assessed. Mice containing KI/KI or KI/KO alleles were viable with normal development and survival, and the presence of KI and KO alleles resulted in a significant reduction in ECHS1 protein. ECHS1D mice displayed reduced exercise capacity and pain sensation. EEG analysis revealed increased slow wave power that was associated with perturbations in sleep. ECHS1D mice had significantly increased epileptiform EEG discharges, and were sensitive to seizure induction, which resulted in death of 60% of ECHS1D mice. Under basal conditions, brain structure was grossly normal, although histological analysis revealed increased microglial activation in aged ECHS1D mice. Increased dietary valine only affected ECHS1D mice, which significantly exacerbated seizure susceptibility and resulted in death. Lastly, acute inflammatory challenge drove regression and early lethality in ECHS1D mice. In conclusion, we developed a novel model of ECHS1D that may be used to further knowledge on disease mechanisms and to develop therapeutics. Our data suggests altered metabolic signaling and inflammation may contribute to epilepsy in ECHS1D, and these alterations may be attributed to impaired valine metabolism.

Detection of short-lasting and ictal spike-and-wave discharges in around-the-ears EEG recordings in children with absence epilepsy

PurposeLong-term ambulatory EEG recordings can improve the monitoring of absence epilepsy in children, but signal quality and increased review workload are a concern. We evaluated the feasibility of around-the-ears EEG arrays (cEEGrids) to capture 3-Hz short-lasting and ictal spike-and-wave discharges and assessed the performance of automated detection software in cEEGrids data. We compared patterns of bilateral synchronisation between short-lasting and ictal spike-and-wave discharges. MethodsWe recruited children with suspected generalised epilepsy undergoing routine video-EEG monitoring and performed simultaneous cEEGrids recordings. We used ASSYST software to detect short-lasting 3-Hz spike-and-wave discharges (1–3 s) and ictal spike-and-wave discharges in the cEEGrids data. We assessed data quality and sensitivity of cEEGrids for spike-and-wave discharges in routine EEG. We determined the sensitivity and false detection rate for automated spike-and-wave discharge detection in cEEGrids data. We compared bihemispheric synchrony across the onset of short-lasting and ictal spike-and-wave discharges using the mean phase coherence in the 2–4 Hz frequency band. ResultsWe included nine children with absence epilepsy (median age = 11 y, range 8–15 y, nine females) and recorded 4 h and 27 min of cEEGrids data. The recordings from seven participants were suitable for quantitative analysis, containing 82 spike-and-wave discharges. The cEEGrids captured 58 % of all spike-and-wave discharges (median individual sensitivity: 100 %, range: 47–100 %). ASSYST detected 82 % of all spike-and-wave discharges (median: 100 %, range: 41–100 %) with a false detection rate of 48/h (median: 6/h, range: 0–154/h). The mean phase coherence significantly increased during short-lasting and ictal spike-and-wave discharges in the 500-ms pre-onset to 1-s post-onset interval. ConclusionscEEGrids are of variable quality for monitoring spike-and-wave discharges in children with absence epilepsy. ASSYST could facilitate the detection of short-lasting and ictal spike-and-wave discharges with clear periodic structures but with low specificity. A similar course of bihemispheric synchrony between short-lasting and ictal spike-and-wave discharges indicates that cortico-thalamic driving may be relevant for both types of spike-and-wave discharges.

Long-term prognosis of patients with photosensitive idiopathic generalized epilepsy

ObjectiveThe long-term prognosis of photosensitive idiopathic generalized epilepsy (p-IGE) is generally considered favorable; however, its specific characteristics remain unclear. Our objective was to investigate the extended prognosis of p-IGE. MethodsWe analyzed the demographics, clinical, and electroencephalographic (EEG) data of consecutive patients who were diagnosed as having p-IGE, who were under follow-up for a minimum of 10 years and exhibited a photoparoxysmal response (PPR) in their EEGs. Prognostic data, epilepsy course types, and electroclinical variables were compared using appropriate statistical methods. ResultsThe mean follow-up duration for 108 consecutive patients with p-IGE (74.1 % female) was 16.8 ± 6.5 years. The main syndromes within this cohort included juvenile myoclonic epilepsy (37 %), juvenile absence epilepsy (15.7 %), and epilepsy with eyelid myoclonia (EEM) (14.8 %). In terms of epilepsy course types, 27.8 % were in the relapse-remission group, and 13.9 % had never experienced remission. A low early remission rate (5.6 %) was evident, with the remaining half of the cohort categorized as the late remission group. Several significant poor prognostic factors were identified including self-induction, clinical symptoms accompanying PPR, asynchrony and focal findings in EEG discharges, a wide frequency range of PPR, the coexistence of three seizure types, the presence of accompanying focal seizure features, and a history of convulsive status epilepticus. ConclusionsOur long-term follow-up study, conducted within a substantial p-IGE group, unveiled newly proposed course types within this epilepsy category and highlighted significant poor prognostic factors related to photosensitivity. These findings furnish valuable insights for precise prognosis counselling and effective management strategies for patients with p-IGE.

Classification of self-limited epilepsy with centrotemporal spikes by classical machine learning and deep learning based on electroencephalogram data

Electroencephalogram (EEG) has been widely utilized as a valuable assessment tool for diagnosing epilepsy in hospital settings. However, clinical diagnosis of patients with self-limited epilepsy with centrotemporal spikes (SeLECTS) is challenging due to the presence of similar abnormal discharges in EEG displays compared to other types of epilepsy (non-SeLECTS) patients. To assist the diagnostic process of epilepsy, a comprehensive classification study utilizing machine learning or deep learning techniques is proposed. In this study, clinical EEG was collected from 33 patients diagnosed with either SeLECTS or non-SeLECTS, aged between 3 and 11 years. In the realm of classical machine learning, sharp wave features (including upslope, downslope, and width at half maximum) were extracted from the EEG data. These features were then combined with the random forest (RF) and extreme random forest (ERF) classifiers to differentiate between SeLECTS and non-SeLECTS. Additionally, deep learning was employed by directly inputting the EEG data into a deep residual network (ResNet) for classification. The classification results were evaluated based on accuracy, F1-score, area under the curve (AUC), and area under the precision-recall curve (AUPRC). Following a 10-fold cross-validation, the ERF classifier achieved an accuracy of 73.15 % when utilizing sharp wave feature extraction for classification. The F1-score obtained was 0.72, while the AUC and AUPRC values were 0.75 and 0.63, respectively. On the other hand, the ResNet model achieved a classification accuracy of 90.49 %, with an F1-score of 0.90. The AUC and AUPRC values for ResNet were found to be 0.96 and 0.92, respectively. These results highlighted the significant potential of deep learning methods in SeLECTS classification research, owing to their high accuracy. Moreover, feature extraction-based methods demonstrated good reliability and could assist in identifying relevant biological features of SeLECTS within EEG data.

Risk factors of electrical status epilepticus during sleep in children with benign childhood epilepsy with centro-temporal spikes.

To explore risk factors of electrical status epilepticus during sleep in children with benign childhood epilepsy with centro-temporal spikes (BECT). This is a clinical comparative study. The subjects of study were 67 children with BECT from the Outpatient Department of Pediatric Neurology in Xingtai People's Hospital from January 2019 to January 2022. According to the occurrence of ESES, the enrolled children were divided into control group which included BECT children without ESES and the observation group which included BECT children with ESES. Compared differences of the two groups in the age of first seizure, the frequency of seizures before treatment, the classification of treatment drugs, cranial MRI, and discharge side of electroencephalogram (EEG). There was no statistical difference between the two groups in the frequency of seizures before treatment, the classification of treatment drugs, cranial MRI, and the distribution of EEG discharges in the left and right cerebral areas(P>0.05). Statistical differences were observed in the age of the first seizure, whether the seizures occurred after treatment, and EEG discharges in unilateral/bilateral cerebral areas (P<0.05). Furthermore, the collinearity test and Logistic regression analysis showed that the age of the first seizure, the frequency of seizures before treatment, and whether the seizures occurred after treatment were independent risk factors for the occurrence of ESES in BECT (P<0.05). Clinically, the occurrence of ESES in children with BECT may be related to the younger age of the first seizure, higher frequency of seizures before treatment, and the occurrence of seizures after treatment.

A possibility of machine learning as a learning tool to evaluate paroxysmal discharge in interictal EEG of childhood focal epilepsy

A possibility of machine learning as a learning tool to evaluate paroxysmal discharge in interictal EEG of childhood focal epilepsy

Clinical phenotype and genetic characteristics of SZT2 related diseases: A case report and literature review

PurposeSeizure threshold 2 protein homolog gene (SZT2, MIM: 615463) related diseases are extremely rare autosomal recessive disorders with a wide spectrum of clinical phenotypes ranging from mild intellectual impairment to severe developmental epileptic encephalopathy (DEE). Most SZT2 related diseases are accompanied by craniofacial malformation and corpus callosum malformation. This study attempts to analyze and summarize the clinical phenotype and genetic characteristics of SZT2 related diseases, providing a basis for early diagnosis, treatment, and prognosis. MethodWe analyzed the clinical characteristics of a Chinese child with pathogenic variants of SZT2. We also performed whole-exome sequencing (WES) on the patient. In addition, we conducted a literature review of previously reported patients with pathogenic mutations in the SZT2 gene. ResultThe proband was a boy aged 1 year and 9 months with severe global developmental delay, transient drug-controlled focal epilepsy, cluster epilepsy, autism spectrum disorder, craniofacial deformity, hypotonia, focal EEG discharge, corpus callosum malformation, and persistent cavum septum pellucidum. WES revealed that the patient carried the SZT2 gene c.7584dupA and c.6302A>C complex heterozygous variants; the former being Likely Pathogenic (LP) and the latter Uncertain Significance (VUS) according to ACMG classification guidelines. According to our literature review, 43 cases of SZT2 related diseases have been reported so far; these include 15 cases with homozygous variations and 28 cases with complex heterozygous variations. A total of 57 types of variation were found, including 47 genetic variants, 2 de novo variants, and 8 unknown genetic modes. In addition, 2 high-frequency variants were found (c.5949_5951delTGT and c.6553C>T). The main clinical manifestations of the 40 patients were global developmental delay (GDD) of varying degrees (38/40, 95.00%), seizures (36/40, 90.00%), cranial deformity (27/40, 67.50%), facial deformity (22/40, 55.00%), hypotonia (22/40, 55.00%), abnormal interseizure EEG discharge (26/40, 65.00%), slow background activity (20/40, 50.00%), corpus callosum deformity (18/40, 45.00%). There was also one case of sudden unexpected death in epilepsy (SUDEP) and 3 cases of death from infection. In addition, three fetuses with the same variant had hydrocephalus and encephalocele. ConclusionThe compound heterozygous mutation of c.7584dupA and c.6302A>C in the SZT2 gene is the genetic etiology of this patient, expanding the mutation spectrum of SZT2 related diseases. Early genetic testing is the best choice for clear diagnosis, treatment, and prognosis.

A case of reversible isolated cognition impairment in meningoencephalitis without abnormal MRI findings

AbstractBackgroundWe report a case of meningoencephalitis with reversible isolated cognition impairment without abnormal MRI findings.MethodA 75‐year‐old man presented with confusion including bizarre behavior 2 days ago. Before visiting the hospital, his son found the patient naked and under the blanket saying it was cold. Fever didn’t occur. Mental status was alert without awareness. On neurologic examination, mutism was found. Muscle power on both upper and lower limbs was normal. Routine laboratory test showed that leukocytes count was normal but eosinophils were increased to 14.0%. Initial brain MRI including DWI and contrast enhanced image revealed no enhanced structural lesions. Initial K‐MMSE score was 4 points while the previous K‐MMSE score 3‐months‐ago was 25 points. There was no epileptic form discharge in EEG. CSF study demonstrated that WBC count was 18/L. protein was 42.6mg/dL, and glucose was 103mg/dL. CSF opening pressure was 5cmH2O. Culture study including gram stain, AFB stain, PAS stain showed no growth of aerobe, anaerobe, fungus and hyphae. Mycobacterium tuberculosis PCR and HSV PCR were negative. ADA was under 3 IU/I. Serum paraneoplastic antibodies were all negative.ResultThe patient showed only isolated cognition impairment without fever and there was no evidence of meningoencephalitis on the contrast enhanced MRI. Although the patient revealed CNS infection with unknown cause in CSF profile, it has some possibilities; 1) Aseptic meningoencephalitis with viral infection, 2) Bacterial meningoencephalitis with early stage, 3) Parasitic meningoencephalitis, 4) Autoimmune meningoencephalitis. Because of the negative findings in autoimmune antibody test, autoimmune meningoencephalitis was less likely. After treatment with acyclovir 0.6g for 7days, ceftriaxone 4g, vancomycin 2.5g and Ampicillin 8g for 10 days, confusion and mutism were improved with K‐MMSE 18 points.ConclusionMany reports have been published on meningoencephalitis accompanied by fever, altered mentality, seizure, muscle weakness and abnormal MRI findings respectively. However there have been few cases of meningoencephalitis with isolated cognition impairment and normal MRI simultaneously. If it is a change of consciousness and cognition impairment caused by meningoencephalitis, it can be reversible with proper treatment. Therefore, if only sudden onset isolated CNS symptom with normal brain MR finding, it is essential to check CSF profile.

Characteristics of neonatal hypoxic-ischemic encephalopathy at high altitude and early results of therapeutic hypothermia

BackgroundAltitude hypoxia and limited socioeconomic conditions may result in distinctive features of neonatal hypoxic-ischemic encephalopathy (HIE). Therapeutic hypothermia (TH) has not been used at altitude. We examined characteristics of HIE and early outcomes of TH in 3 centers at two high altitudes, 2 at 2,261 m and 1 at 3,650 m.MethodsThe incidence of HIE at NICUs was noted. TH was conducted when personnel and devices were available in 2019~2020. Standard inclusion criteria were used, with the addition of admission age >6 hours and mild HIE. Demographic and clinical data included gestational age, gender, weight, Apgar score, ethnics, age on admission, age at TH and clinical degree of HIE. EEG was monitored for 96 hours during hypothermia and rewarming. MRI was performed before discharge.ResultsThere was significant difference in ethnics, HIE degree, age at TH across 3 centers. The overall NICU incidence of HIE was 4.0%. Among 566 HIE patients, 114 (20.1%) received TH. 63 (55.3%) patients had moderate/severe HIE. Age at TH >6 hours occurred in 34 (29.8%) patients. EEG discharges showed seizures in 7~11% of patients, whereas spikes/sharp waves in 94~100%, delta brushes in 50~100%. After TH, MRI showed moderate to severe brain injury in 77% of patients, and correlated with center, demographic and clinical variables (Ps≤0.0003). Mortality was 5% during hospitalization and 11% after discharge until 1 year.ConclusionsAt altitude, the incidence of HIE was high and brain injury was severe. TH was limited and often late >6 hours. EEG showed distinct patterns attributable to altitude hypoxia. TH was relatively safe.Trial registrationThe study was registered on February 23, 2019 in Chinese Clinical Trial Register (ChiCTR1900021481).

Candidate Genes Associated with the Course of Epilepsy in Cerebral Palsy: Remission or Refractoriness

Epilepsy often accompanies congenital cerebral palsy (CP). Canalopathies can be the cause of congenital epilepsy. The aim of the study is to determine the influence of various determinants on the course of epilepsy. Materials and methods: The results of clinical and genetic analysis of 136 cases of cerebral palsy (CP) with epilepsy are presented. The patients were divided into groups according to the syndromes according to the classification of CP (Panteliadis and R. Korinthenberg, 2005). Epileptic syndromes were divided into three groups: focal childhood epilepsy with structural brain changes and benign epileptiform discharges (BEDC) in EEG - 41 children (30.1%), structural focal epilepsy - 37 children (27.2%), epileptic encephalopathies 58 children (42.7%). Pathogenic variants in genes were confirmed by next generation sequencing (NGS) Sanger methods of venous blood. Results. Remission was more difficult to achieve in patients with determinants of regulation of general aspects of cellular metabolism, mitochondrial function, cytoskeleton formation and function, and transport across the outer membrane. The need for polypharmacy was in the groups that regulate the function of mitochondria, the formation and functioning of the cytoskeleton, and the regulation of membrane excitability. Conclusion. Determinant analysis provides a better understanding of the mechanisms of patient responsiveness to anticonvulsant therapy. The determinant of mitochondrial function most significantly affects its effectiveness. Probably, the violation of energy metabolism in the cell neutralizes the stabilization of the neuronal membrane under the influence of anticonvulsants. The determinant of the formation and functioning of the cytoskeleton, according to our preliminary data, is associated with the formation of malformations of the brain. In this case, the refractoriness of epilepsy can be secondary and determined by the severity of structural changes in the brain.

Gad1 knock-out rats exhibit abundant spike-wave discharges in EEG, exacerbated with valproate treatment.

To elucidate the functional role of gamma-aminobutyric acid (GABA)-ergic inhibition in suppressing epileptic brain activities such as spike-wave discharge (SWD), we recorded electroencephalogram (EEG) in knockout rats for Glutamate decarboxylase 1 (Gad1), which encodes one of the two GABA-synthesizing enzymes in mammals. We also examined how anti-epileptic drug valproate (VPA) acts on the SWDs present in Gad1 rats and affects GABA synthesis in the reticular thalamic nucleus (RTN), which is known to play an essential role in suppressing SWD. Chronic EEG recordings were performed in freely moving control rats and homozygous knockout Gad1 (-/-) rats. Buzzer tones (82 dB) were delivered to the rats during EEG monitoring to test whether acoustic stimulation could interrupt ongoing SWDs. VPA was administered orally to the rats, and the change in the number of SWDs was examined. The distribution of GABA in the RTN was examined immunohistochemically. SWDs were abundant in EEG from Gad1 (-/-) rats as young as 2 months old. Although SWDs were universally detected in older rats irrespective of their Gad1 genotype, SWD symptom was most severe in Gad1 (-/-) rats. Acoustic stimulation readily interrupted ongoing SWDs irrespective of the Gad1 genotype, whereas SWDs were more resistant to interruption in Gad1 (-/-) rats. VPA treatment alleviated SWD symptoms in control rats, however, counterintuitively exacerbated the symptoms in Gad1 (-/-) rats. The immunohistochemistry results indicated that GABA immunoreactivity was significantly reduced in the somata of RTN neurons in Gad1 (-/-) rats but not in their axons targeting the thalamus. VPA treatment greatly increased GABA immunoreactivity in the RTN neurons of Gad1 (-/-) rats, which is likely due to the intact GAD2, another GAD isozyme, in these neurons. Our results revealed two opposing roles of GABA in SWD generation: suppression and enhancement of SWD. To account for these contradictory roles, we propose a model in which GABA produced by GAD1 in the RTN neuronal somata is released extrasynaptically and mediates intra-RTN inhibition.

Graph neural networks in EEG spike detection

Objective:This study develops new machine learning architectures that are more adept at detecting interictal epileptiform discharges (IEDs) in scalp EEG. A comparison of results using the average precision (AP) metric is made with the proposed models on two datasets obtained from Baptist Hospital of Miami and Temple University Hospital. Methods:Applying graph neural networks (GNNs) on functional connectivity (FC) maps of different frequency sub-bands to yield a novel architecture we call FC-GNN. Attention mechanism is applied on a complete graph to let the neural network select its important edges, hence bypassing the extraction of features, a model we refer to as CA-GNN. Results:On the Baptist Hospital dataset, the results were as follows: Vanilla Self-Attention →0.9029±0.0431, Hierarchical Attention →0.8546±0.0587, Vanilla Visual Geometry Group (VGG) →0.92±0.0618, Satelight →0.9219±0.046, FC-GNN →0.9731±0.0187, and CA-GNN →0.9788±0.0125. In the same order, the results on the Temple University Hospital dataset are 0.9692, 0.9113, 0.97, 0.9575, 0.963, and 0.9879. Conclusion:Based on the good results they yield, GNNs prove to have a strong potential in detecting epileptogenic activity. Significance:This study opens the door for the discovery of the powerful role played by GNNs in capturing IEDs, which is an essential step for identifying the epileptogenic networks of the affected brain and hence improving the prospects for more accurate 3D source localization.