Epileptic EEG Activity Research Articles

Role of Central and Peripheral Physiological Markers in Understanding and Monitoring the Clinical Illness in Dementia

Patients with Alzheimer's dementia are known to have electrophysiological abnormalities such as increased slow wave power of resting electroencephalography (EEG), cortical excitability as detected using EEG epileptiform and epileptic activity, and deficits in cortical plasticity detected using brain stimulation combined with EEG. Understanding these neurophysiological abnormalities is important to improve our understanding of the mechanisms leading to brain dysfunction thus leading to the development of novel treatment interventions. Further, EEG is a non-invasive, low-cost, and portable technique that is widely available and can become an important tool in monitoring illness and response to treatment. To further improve objective measures to detect and monitor clinical symptoms of dementia, recently, there has been an increased interest in the development of peripheral physiological markers such as motor activity, skin conductance and temperature, and heart rate variability. These markers can be recorded using wearable devices and have shown usefulness in monitoring neuropsychiatric symptoms of dementia. Further development of these markers can improve clinical care by improving objective assessment of clinical profiles of persons with dementia living in the community or those admitted to hospitals and can help individualize care. In this session, we will first review novel findings from studies using EEG to assess central neurophysiological markers, and then discuss the role of peripheral physiological markers in the detection and monitoring of clinical symptoms of dementia in community and dementia care units.These talks will be followed by a discussion about the relevance of the central and peripheral physiological markers (biometrics) in dementia.

Automatic Detection and Classification of Epileptic Seizures from EEG Data: Finding Optimal Acquisition Settings and Testing Interpretable Machine Learning Approach.

Deep learning (DL) is emerging as a successful technique for automatic detection and differentiation of spontaneous seizures that may otherwise be missed or misclassified. Herein, we propose a system architecture based on top-performing DL models for binary and multigroup classifications with the non-overlapping window technique, which we tested on the TUSZ dataset. The system accurately detects seizure episodes (87.7% Sn, 91.16% Sp) and carefully distinguishes eight seizure types (95-100% Acc). An increase in EEG sampling rate from 50 to 250 Hz boosted model performance: the precision of seizure detection rose by 5%, and seizure differentiation by 7%. A low sampling rate is a reasonable solution for training reliable models with EEG data. Decreasing the number of EEG electrodes from 21 to 8 did not affect seizure detection but worsened seizure differentiation significantly: 98.24 ± 0.17 vs. 85.14 ± 3.14% recall. In detecting epileptic episodes, all electrodes provided equally informative input, but in seizure differentiation, their informative value varied. We improved model explainability with interpretable ML. Activation maximization highlighted the presence of EEG patterns specific to eight seizure types. Cortical projection of epileptic sources depicted differences between generalized and focal seizures. Interpretable ML techniques confirmed that our system recognizes biologically meaningful features as indicators of epileptic activity in EEG.

Increased propensity for infantile spasms and altered neocortical excitation-inhibition balance in a mouse model of down syndrome carrying human chromosome 21

Children with Down syndrome (DS, trisomy of chromosome 21) have an increased risk of infantile spasms (IS). As an epileptic encephalopathy, IS may further impair cognitive function and exacerbate neurodevelopmental delays already present in children with DS. To investigate the pathophysiology of IS in DS, we induced IS-like epileptic spasms in a genetic mouse model of DS that carries human chromosome 21q, TcMAC21, the animal model most closely representing gene dosage imbalance in DS. Repetitive extensor/flexor spasms were induced by the GABAB receptor agonist γ-butyrolactone (GBL) and occurred predominantly in young TcMAC21 mice (85%) but also in some euploid mice (25%). During GBL application, background electroencephalographic (EEG) amplitude was reduced, and rhythmic, sharp-and-slow wave activity or high-amplitude burst (epileptiform) events emerged in both TcMAC21 and euploid mice. Spasms occurred only during EEG bursts, but not every burst was accompanied by a spasm. Electrophysiological experiments revealed that basic membrane properties (resting membrane potential, input resistance, action-potential threshold and amplitude, rheobase, input-output relationship) of layer V pyramidal neurons were not different between TcMAC21 mice and euploid controls. However, excitatory postsynaptic currents (EPSCs) evoked at various intensities were significantly larger in TcMAC21 mice than euploid controls, while inhibitory postsynaptic currents (IPSCs) were similar between the two groups, resulting in an increased excitation-inhibition (E-I) ratio. These data show that behavioral spasms with epileptic EEG activity can be induced in young TcMAC21 DS mice, providing proof-of-concept evidence for increased IS susceptibility in these DS mice. Our findings also show that basic membrane properties are similar in TcMAC21 and euploid mice, while the neocortical E-I balance is altered to favor increased excitation in TcMAC21 mice, which may predispose to IS generation.

Interictal Electrical Source Imaging.

Interictal electrical source imaging (ESI) determines the neuronal generators of epileptic activity in EEG occurring outside of seizures. It uses computational models to take anatomic and neuronal characteristics of the individual patient into account. The presented article provides an overview of application and clinical value of interictal ESI in patients with pharmacoresistant focal epilepsies undergoing evaluation for surgery. Neurophysiological constraints of interictal data are discussed and technical considerations are summarized. Typical indications are covered as well as issues of integration into clinical routine. Finally, an outlook on novel markers of epilepsy for interictal source analysis is presented. Interictal ESI provides diagnostic performance on par with other established methods, such as MRI, PET, or SPECT. Although its accuracy benefits from high-density recordings, it provides valuable information already when applied to EEG with only a limited number of electrodes with complete coverage. Novel oscillatory markers and the integration of frequency coupling and connectivity may further improve accuracy and efficiency.

Spike-wave seizures, slow-wave sleep EEG and morphology of substantia nigra pars compacta in WAG/Rij rats with genetic predisposition to absence epilepsy

Spike-wave discharges (SWDs) are EEG hallmarks of absence epilepsy, and they spontaneously appear in adult WAG/Rij rats. SWDs are known to be vigilance-dependent and are modulated by monoaminergic mechanisms. It is also known that loss of neurons in the center of the nigrostriatal dopamine system, substantia nigra pars compacta (SNc), is associated with a variety of sleep disorders. We hypothesized that a disorder of the nigrostriatal dopamine system described for WAG/Rij rats might facilitate generation of SWDs through changes in vigilance state and the quality of sleep. Our study was conducted in ‘epileptic’ and ‘non-epileptic’ phenotype (less than 1 SWDs per h). Analysis included (1) EEG examination, i.e., analysis of SWDs, rudimentary SWDs and slow wave sleep EEG and (2) microstructural examination of SNc, i.e., measuring its size and the number of neurons and glial cells. No differences in size and cellular content of SNc were found between ‘epileptic’ and ‘non-epileptic’ phenotypes. Meanwhile in ‘epileptic’ subjects, the number of SWDs correlated with the number of neurons in SNc (SWDs more frequently occurred in subjects with fewer neurons in SNc). Rudimentary SWDs were found in both phenotypes. No differences in number and duration of rudimentary SWDs were found between ‘epileptic’ and ‘non-epileptic’ phenotypes. Spike-wave EEG activity showed strong association with the number of neurons in SNc: subjects with fewer neurons in SNc were characterized by higher number of SWDs and longer rudimentary SWDs. In sum, our data suggested that intense epileptic EEG activity (in the form of SWDs and rudimentary SWDs) might lead to sleep disruption. However, the lack of direct correlations between sleep parameters and SWDs number indicated that the link between sleep features, SNc cellularity and spike-wave EEG activity could be more complex than we had expected.

Semiology of epileptic seizures: Assiut University Hospital-based study

BackgroundEpilepsy diagnosis is mainly clinical, as it depends on the detailed analysis of the seizure semiology. This study reviews the systematic way to describe and classify seizure semiology with the help of using electro-clinical methods for better diagnosis and to choose the most effective medical treatment.Patients and methodsThis study was conducted on 60 epileptic patients throughout the period from 1st of October 2016 to 31st of March 2017 in Assiut University Hospital. We excluded patients who lacked eye witness and who had seizures owing to metabolic causes. All patients were subjected to complete general and neurological examination, epilepsy sheet with detailed seizure semiology analysis, and electroencephalogram (EEG).ResultsProdroma was found in 26 (43.3%) cases, and aura was recorded in 34 (56.7%) cases. Forty (66.7%) cases had automatism more in the form of picking cloths and unresponsiveness. Most cases (63.3%) reported loss of contact with surroundings and 28.3% lost their consciousness. Ipsiversive movement was recorded in 13.3% of cases, whole-body myoclonus was presented in 10% of cases, unilateral nonmarching sensory seizure in 3.3%, 23.3% presented with tonic seizure, and 16.7% with tonic–clonic seizure. Postictal amnesia was seen in 60% of cases, postictal confusion in 46.7%, and postictal Todd's paralysis in 6.7%. Distribution of epileptic activity in EEG was mostly in left fronto-temporal area (20%).ConclusionClinical semiology is the starting point of understanding seizure disorder and making the diagnosis of epilepsy. The correlation between analysis of the development and sequence of semiologic features and EEG findings can identify the seizure initiation and propagation.

Automatic sleep stage classification based on subcutaneous EEG in patients with epilepsy

Background The interplay between sleep structure and seizure probability has previously been studied using electroencephalography (EEG). Combining sleep assessment and detection of epileptic activity in ultralong-term EEG could potentially optimize seizure treatment and sleep quality of patients with epilepsy. However, the current gold standard polysomnography (PSG) limits sleep recording to a few nights. A novel subcutaneous device was developed to record ultralong-term EEG, and has been shown to measure events of clinical relevance for patients with epilepsy. We investigated whether subcutaneous EEG recordings can also be used to automatically assess the sleep architecture of epilepsy patients.Method Four adult inpatients with probable or definite temporal lobe epilepsy were monitored simultaneously with long-term video scalp EEG (LTV EEG) and subcutaneous EEG. In total, 11 nights with concurrent recordings were obtained. The sleep EEG in the two modalities was scored independently by a trained expert according to the American Academy of Sleep Medicine (AASM) rules. By using the sleep stage labels from the LTV EEG as ground truth, an automatic sleep stage classifier based on 30 descriptive features computed from the subcutaneous EEG was trained and tested.Results An average Cohen’s kappa of kappa = 0.78pm 0.02 was achieved using patient specific leave-one-night-out cross validation. When merging all sleep stages into a single class and thereby evaluating an awake–sleep classifier, we achieved a sensitivity of 94.8% and a specificity of 96.6%. Compared to manually labeled video-EEG, the model underestimated total sleep time and sleep efficiency by 8.6 and 1.8 min, respectively, and overestimated wakefulness after sleep onset by 13.6 min.Conclusion This proof-of-concept study shows that it is possible to automatically sleep score patients with epilepsy based on two-channel subcutaneous EEG. The results are comparable with the methods currently used in clinical practice. In contrast to comparable studies with wearable EEG devices, several nights were recorded per patient, allowing for the training of patient specific algorithms that can account for the individual brain dynamics of each patient. Clinical trial registered at ClinicalTrial.gov on 19 October 2016 (ID:NCT02946151).

EP.111Identification of novel biallelic mutations in SPTBN4 in a child with NEDHND featuring a spinal muscular atrophy phenotype

Neurodevelopmental disorder with hypotonia, neuropathy, and deafness (NEDHND, OMIM: #617519) is an autosomal recessive disorder caused by homozygous or compound heterozygous mutations in the SPTBN4. Mutations in SPTBN4 disrupt cytoskeletal machinery that control proper localization of ion channels and function of axonal domains, generating severe neurological dysfunction. Recently, recessive mutations in human SPTBN4 have been described in 7 patients manifesting with severe hypotonia, developmental delay and mixed neuropathic and myopathic features, with central deafness and severe epilepsy in some cases. Here we report a six-year-old Chilean patient with a phenotype characterized by severe early-onset hypotonia, areflexia, proximal and distal weakness with an axonal motor neuropathy and evidence of acute denervation by EMG. At first evaluation at ten months of age, she presented as a spinal muscular atrophy phenotype and negative result for SMN1 deletion. Subsequently, a muscle biopsy showed neurogenic type grouping. The clinical evolution was characterized by global developmental delay, absent speech, deafness, progressive swallowing and respiratory difficulties. A tracheostomy and gastrostomy were indicated. Later in her evolution, appearance of severe generalized EEG epileptic abnormalities and absence of manifest clinical seizures were noted. A specific motor neuron diseases panel failed to find any mutation, and trio whole exome sequencing identified an apparent homozygous single base pair duplication in the SPTBN4 in the proband; this variant was also detected as heterozygous in the patient's father but was not detected in the patient's mother. However, a deletion involving multiple exons of the SPTBN4, which overlaps this variant, was identified in the proband and in the patient's mother, indicating that the two variants are in trans in the proband. This is the first multi-exon deletion that has been reported in the SPTBN4 to date. Additionally, this case highlights the early predominant motor axonal involvement in this patient manifesting as severe hypotonia and areflexia similar to others non-5q SMA patients, and the consecutive appearance of another feature in the clinical evolution as the auditory neuropathy and epileptic activity in EEG as key elements to suspect SPTBN4 mutation.

The Role of EEG-fMRI in Studying Cognitive Network Alterations in Epilepsy.

Brain functions do not arise from isolated brain regions, but from interactions in widespread networks necessary for both normal and pathological conditions. These Intrinsic Connectivity Networks (ICNs) support cognitive processes such as language, memory, or executive functions, but can be disrupted by epileptic activity. Simultaneous EEG-fMRI can help explore the hemodynamic changes associated with focal or generalized epileptic discharges, thus providing information about both transient and non-transient impairment of cognitive networks related to spatio-temporal overlap with epileptic activity. In the following review, we discuss the importance of interictal discharges and their impact on cognition in different epilepsy syndromes. We explore the cognitive impact of interictal activity in both animal models and human connectivity networks in order to confirm that this effect could have a possible clinical impact for prescribing medication and characterizing post-surgical outcome. Future work is needed to further investigate electrophysiological changes, such as amplitude/latency of single evoked responses or spontaneous epileptic activity in either scalp or intracranial EEG and determine its relative change in hemodynamic response with subsequent network modifications.

Diagnostic principles of immature epileptic (proepileptic) EEG activity in rats with genetic predisposition to absence epilepsy

Introduction:Absence epilepsy is a specific neurological disorder characterized by brief episodes of loss of consciousness (absence) accompanied by high-amplitude “spike-wave” discharges in the electroencephalogram (EEG). WAG/Rij rats with a genetic predisposition to absence epilepsy are used as a reliable model of this disease. This model is beneficial for investigating basic mechanisms of absence epilepsy, including the development of spike-wave seizures.Purpose:Establishing diagnostic principles for immature forms of spikewave activity in EEG (so-called proepileptic activity) of WAG/Rij rats.Results:Diagnostic criteria are proposed for proepileptic EEG activity in rats, based on time-frequency analysis with the continuous wavelet transform and skeletons of wavelet surfaces. The algorithm was tested in “epileptic” and “asymptomatic” individuals. Rats with the “epileptic” phenotype demonstrated a decrease in number of proepileptic patterns between 5 and 7 months of age in parallel to an increase in the number of epileptic discharges that might relate to the transformation of proepileptic activity to epileptic. In rats with the “asymptomatic” phenotype, the age-related decline in the number of proepileptic patterns was not accompanied by the occurrence of spike-wave discharges. A decrease in the instantaneous frequency was found in a larger number of proepileptic patterns in “epileptic” WAG/Rij rats as compared to “asymptomatic” individuals.Practical relevance:A similar approach can be used for early diagnosis of absence epilepsy at the preclinical stage in patients with genetic predisposition.

Effects of Levetiracetam on EEG Activity and Regularity of the Menstrual Cycle in Women Suffering from Epilepsy

Epilepsy itself and its treatment with anticonvulsants noticeably affect the reproductive function in women suffering from this disease. Levetiracetam (LEV) was shown to be highly effective for the reduction of clinical seizures and EEG epileptic activity. At the same time, its impact on the reproductive/endocrine functions is still unclear. The aim of our study was to evaluate the influence of LEV on the frequency of seizures and epilepsy-related EEG discharges, and also on the regularity of menstrual cycles (MCs) among women with epilepsy (WE) in Georgia. Seizures entirely disappeared in all examined WE with focal and bilateral tonico-clonic seizures (BTCSs), as well as in all cases with juvenile myoclonic epilepsy (JME) (P = 0.008). Six months after starting LEV monotherapy, a reduction in single and burst EEG epileptic discharges was observed in all eight women with JME (P = 0.031); weakening of burst discharges was also revealed in all patients with focal epilepsy (P = 0.046). Among examined WE with regular MCs, oligomenorrhea was observed in two cases from eight patients with focal epilepsy and in one case from seven women with JME treated with LEV. In general, LEV effectively suppresses paroxysmal EEG discharges and also improves clinical seizure control. There was no significant influence of LEV on the MC disturbances, while oligomenorrhea was found in some cases; thus, the respective effects on the MC were at least relatively moderate. More data are needed to establish the level of association between LEV therapy and reproductive endocrine disorders in WE.

Schmidtea mediterranea as an alternative model to predict carcinogenicity via its stem cell responses

To study the association between global hemodynamics, blood gases, epileptiform EEG activity and survival after out-of-hospital CA (0HCA).We retrospectively analyzed 195 comatose post-CA patients. At least one EEG recording per patient was evaluated to diagnose epileptiform EEG activity. Refractory epileptiform EEG activity was defined as persisting epileptic activity on EEG despite the use of 2 or more anti-epileptics. The time weighted average mean arterial pressure 48 h (TWA-MAP48), the percentage of time with a MAP below 65 and above 85 mmHg and the percentage of time with normoxia, hypoxia (<70 mmHg), hyperoxia (>150 mmHg), normocapnia, hypocapnia (<35 mmHg) and hypercapnia (>45 mmHg) were calculated.We observed epileptiform EEG activity in 57 patients (29%). A shockable rhythm was associated with a decreased likelihood of epileptic activity on the EEG (OR: 0.41, 95%CI 0.22–0.79). We did not identify an association between the TWA-MAP48, the percentage of time with MAP below 65 mmHg or above 85 mmHg, blood gas variables and the risk of post-CA epileptiform EEG activity. The presence of epileptiform activity decreased the likelihood of survival independently (OR: 0.10, 95% CI: 0.04–0.24). Interestingly, survival rates of patients in whom the epileptiform EEG resolved (n = 20), were similar compared to patients without epileptiform activity on EEG (60% vs 67%,p = 0.617). Other independent predictors of survival were presence of basic life support (BLS) (OR:5.08, 95% CI 1.98–13.98), presence of a shockable rhythm (OR: 7.03, 95% CI: 3.18–16.55), average PaO2 (OR = 0.93, CI 95% 0.90–0.96) and% time MAP < 65 mmHg (OR: 0.96, CI 95% 0.94–0.98).Epileptiform EEG activity in post-CA patients is independently and inversely associated with survival and this effect is mainly driven by patients in whom this pattern is refractory over time despite treatment with anti-epileptic drugs. We did not identify an association between hemodynamic factors, blood gas variables and epileptiform EEG activity after CA, although both hypotension, hypoxia and epileptic EEG activity were predictors of survival.

Prevalence, Semiology, and Risk Factors of Epilepsy in Alzheimer's Disease: An Ambulatory EEG Study.

Alzheimer's disease (AD) is the primary cause of cognitive decline. A growing body of evidence suggests that AD patients have a higher risk to develop epileptic seizures; however, results are contradictory due to different methodological approaches of previous studies. We aimed to identify the prevalence, semiology, and risk factors of epilepsy in AD using long-term EEG. We selected forty-two AD patients and examined them using 24-hour ambulatory EEG. Neurological and epileptological data were collected with retro- and prospective methods. We analyzed the semiology of the identified seizures and the possible risk factors using logistic regression analysis. We identified seizures confirmed by EEG in 24%. The majority of the seizures were aware focal (72%) without any motor activity (55%). We found epileptiform discharges without seizures in 28%. Patients with seizures and only with epileptic EEG activity showed similar clinical and demographical features. Higher education (OR:1.8) and lower Addenbrooke Examination Score (OR: 0.9) were identified as risk factors of epilepsy. Increase of 0.1 point in the Verbal-Language/Orientation-Memory ratio (VLOM) was associated with higher epilepsy risk as well (OR:2.9). Epilepsy is a frequent comorbidity of AD. Since most of the seizures are aware non-motor focal seizures, sensitive EEG techniques are required for precise diagnosis of epilepsy. Long-term ambulatory EEG is a safe and well-tolerated option. Epileptiform EEG in AD signals the presence of concomitant epilepsy. Clinicians have to pay attention to comorbid epilepsy in dementia patients with high education, with high VLOM ratio and severe stage.

The impact of global hemodynamics, oxygen and carbon dioxide on epileptiform EEG activity in comatose survivors of out-of-hospital cardiac arrest

AimTo study the association between global hemodynamics, blood gases, epileptiform EEG activity and survival after out-of-hospital CA (0HCA). MethodsWe retrospectively analyzed 195 comatose post-CA patients. At least one EEG recording per patient was evaluated to diagnose epileptiform EEG activity. Refractory epileptiform EEG activity was defined as persisting epileptic activity on EEG despite the use of 2 or more anti-epileptics. The time weighted average mean arterial pressure 48h (TWA-MAP48), the percentage of time with a MAP below 65 and above 85mmHg and the percentage of time with normoxia, hypoxia (<70mmHg), hyperoxia (>150mmHg), normocapnia, hypocapnia (<35mmHg) and hypercapnia (>45mmHg) were calculated. ResultsWe observed epileptiform EEG activity in 57 patients (29%). A shockable rhythm was associated with a decreased likelihood of epileptic activity on the EEG (OR: 0.41, 95%CI 0.22–0.79). We did not identify an association between the TWA-MAP48, the percentage of time with MAP below 65mmHg or above 85mmHg, blood gas variables and the risk of post-CA epileptiform EEG activity. The presence of epileptiform activity decreased the likelihood of survival independently (OR: 0.10, 95% CI: 0.04–0.24). Interestingly, survival rates of patients in whom the epileptiform EEG resolved (n=20), were similar compared to patients without epileptiform activity on EEG (60% vs 67%,p=0.617). Other independent predictors of survival were presence of basic life support (BLS) (OR:5.08, 95% CI 1.98–13.98), presence of a shockable rhythm (OR: 7.03, 95% CI: 3.18–16.55), average PaO2 (OR=0.93, CI 95% 0.90–0.96) and% time MAP<65mmHg (OR: 0.96, CI 95% 0.94–0.98). ConclusionEpileptiform EEG activity in post-CA patients is independently and inversely associated with survival and this effect is mainly driven by patients in whom this pattern is refractory over time despite treatment with anti-epileptic drugs. We did not identify an association between hemodynamic factors, blood gas variables and epileptiform EEG activity after CA, although both hypotension, hypoxia and epileptic EEG activity were predictors of survival.

O81 High frequency EEG activity is associated with preserved cerebral function in critical illness

Objectives To assess the value of continuous electroencephalography (cEEG) in detecting delirium in a medical intensive care unit (ICU), applying a visual, qualitative analysis in accordance with The American Clinical Neurophysiology Society’s Standardized Critical Care Terminology. Methods Single-center prospective observational study including 102 patients with sepsis or septic shock. Full scalp cEEG was recorded continuously after admission.Delirium screening was applied six times daily using the Confusion Assessment Method for the ICU (CAM-ICU). Results Sixty-six patients (65%) had at least one episode of delirium during their ICU stay; thirty (29%) remained delirium-free; six patients (6%) remained comatose and unassessable. In total, 6723 h of EEG-recordings were visually analyzed. Preserved beta activity (>13 Hz) was independently associated with staying delirium-free ( p 10 - 7 ) along with preserved EEG reactivity ( p 0.001 ). Reduced beta activity emerged as the stronger predictor for delirium, eliminating theta and delta electrographic band power. Time-dependent Cox regression associated burst suppression with reduced mortality. Sporadic periodic discharges occurred in fifteen patients of whom 87% were delirious. Treatment-requiring epileptic or non-convulsive EEG activity was not observed. Discussion Neuronal desynchronization expressed as loss of high frequency EEG activity could be a potential biomarker for delirium. Whether this is superior to bedside clinical screening with validated tests such as the CAM-ICU remains to be further examined. Conclusions Beta activity was the strongest predictor of preserved cerebral function in septic patients and superior to the previously described association between delirium and low frequency delta activity. Non-convulsive activity was not observed. Significance Early detection of cerebral deterioration by cEEG may provide a window for intervention to improve outcome.

Corpus callosum agenesis and interhemispheric cysts: Epileptic evaluation and long-term outcome in 9 children

Objective: To describe perinatal history, clinical phenotype, MR features, neurological outcome, and EEG patterns of pediatric patients with Corpus Callosum Agenesis (CCAg) and Interhemispheric Cysts. Methods: We selected 9 patients (8 males, mean age 7,3 +/−5,7) with CCAg (partial or complete) and interemipheric cysts from our imaging database of 378 patients with midline brain anomalies scanned at Gaslini Children Hospital from Jan 2005 to Jan 2017. Interemispheric cysts were grouped according to the 2001 Barkovich classification. Presence and location of gray matter anomalies such as polymichrogyria (PMG) or nodular heterotopia (NH) were recorded. Perinatal, clinical, genetic testing (when available), EEG pattern, age of onset of seizure (if present) with drug responsivity were reported. Results: Complete CCAg was present in 6 individuals, while the remaining cases had partial CCAg. Type1 cysts were present in 1 patient (subtype1a). Type 2 cysts were 8 (2 subtype2a, 2 subtype2b, 1 subtype2c and 1 subtype2d). Of interest, 2 patients had an MRI pattern overlapping between subtype2b and 2c (transmanterllar NH, diffuse PMG, macrocephaly, developmental delay). EEG epileptic activity was present in all but epilepsy onset was observed in 3/9 cases, with drug response in all. Major neurological defects were excluded. Developmental delay was observed in all cases but cognitive outcome, registered for 6/9 patients, was milder: 3/6 normal IQ, 2/6 bordeline and 1 with mild Intellectual Disability. Psychiatric data were recorded for 7/9 patients: hyperactivity and anxiety were frequent comorbidities (5/7). Conclusions: CCAg associated with Intehemispheric Cysts may be associated with a good neurological outcome with borderline or normal cognition and no major neurological signs in the majority of patients. Despite the presence of EEG anomalies, the occurrence of epilepsy in these cases is rare and usually responsive to antiepileptic drugs.

EEG responses to direct electrical stimulation and correlations to post-stimulus parameters in electroconvulsive therapy (ECT).

Objective: To evaluate epileptic EEG activity induced by stimulation during electroconvulsive therapy (ECT) and correlation with post-stimulus parameters currently used to evaluate the efficacy of stimulation.

Compensatory Changes in the Brain Dopaminergic System of WAG/Rij Rats Genetically Predisposed to Absence Epilepsy.

Involvement of the brain dopaminergic system in the age-related dynamics of absence epilepsy in WAG/Rij rats was examined by histological, immunohistochemical, and electrophysiological (EEG) methods. We revealed reduced expression of dopamine receptors in various brain structures prior to first manifestations of the disease (at the age of 1-3 months), reduced density of neurons in the center of nigrostriatal system (substantia nigra pars compacta) in 10-month-old rats in comparison with 1-month-old rats, and positive correlation between neural density in the substantia nigra and intensity of epileptic activity in EEG. It is hypothesized that loss of dopaminergic neurons and reduced nigrostriatal dopaminergic innervation of the brain could prevent the development of absence epilepsy in WAG/Rij rats.

Inhibition of long-term potentiation in the schaffer-CA1 pathway by repetitive high-intensity sound stimulation

High-intensity sound can induce seizures in susceptible animals. After repeated acoustic stimuli changes in behavioural seizure repertoire and epileptic EEG activity might be seen in recruited limbic and forebrain structures, a phenomenon known as audiogenic kindling. It is postulated that audiogenic kindling can produce synaptic plasticity events leading to the spread of epileptogenic activity to the limbic system. In order to test this hypothesis, we investigated if long-term potentiation (LTP) of hippocampal Schaffer-CA1 synapses and spatial navigation memory are altered by a repeated high-intensity sound stimulation (HISS) protocol, consisting of one-minute 120dB broadband noise applied twice a day for 10days, in normal Wistar rats and in audiogenic seizure-prone rats (Wistar Audiogenic Rats – WARs). After HISS all WARs exhibited midbrain seizures and 50% of these animals developed limbic recruitment, while only 26% of Wistar rats presented midbrain seizures and none of them had limbic recruitment. In naïve animals, LTP in hippocampal CA1 neurons was induced by 50- or 100-Hz high-frequency stimulation of Schaffer fibres in slices from both Wistar and WAR animals similarly. Surprisingly, HISS suppressed LTP in CA1 neurons in slices from Wistar rats that did not present any seizure, and inhibited LTP in slices from Wistar rats with only midbrain seizures. However HISS had no effect on LTP in CA1 neurons from slices of WARs. Interestingly HISS did not alter spatial navigation and memory in both strains. These findings show that repeated high-intensity sound stimulation prevent LTP of Schaffer-CA1 synapses from Wistar rats, without affecting spatial memory. This effect was not seen in hippocampi from audiogenic seizure-prone WARs. In WARs the link between auditory stimulation and hippocampal LTP seems to be disrupted which could be relevant for the susceptibility to seizures in this strain.

MODERN CONCEPTS OF THE NATURE AND PATHOGENESIS OF COGNITIVE IMPAIRMENT IN PATIENTS WITH EPILEPSY. Review of literature

The analysis of modern aspects of nature and pathogenesis of cognitive disorders in epilepsy is presented. The cognitive disorders of different degree of severance are seen in 40–54% of patients with epilepsy. We detected 3 main causes of cognitive disorders: etiologic factors of epilepsy, epileptic seizure itself and the impact of anticonvulsants. The article presents the marks of epileptic seizures which can be predictors of cognitive deficit. The presumed mechanisms of impact on cognitive functions both seizures themselves and interictal epileptic activity in EEG are discussed. The article presents the mechanism of action of different anticonvulsants and emphasizes the drugs with negative impact on cognitive functions. Typical for epilepsy mnestic disorders, disturbance of attention, speech, ideation and executive functions are discussed. The basic hypotheses of cognitive disorders are disclosed.