Revealing a Brain Network Endophenotype in Families with Idiopathic Generalised Epilepsy

Idiopathic generalised epilepsy (IGE) has a genetic basis. The mechanism of seizure expression is not fully known, but is assumed to involve large-scale brain networks. We hypothesised that abnormal brain network properties would be detected using EEG in patients with IGE, and would be manifest as a familial endophenotype in their unaffected first-degree relatives. We studied 117 participants: 35 patients with IGE, 42 unaffected first-degree relatives, and 40 normal controls, using scalp EEG. Graph theory was used to describe brain network topology in five frequency bands for each subject. Frequency bands were chosen based on a published Spectral Factor Analysis study which demonstrated these bands to be optimally robust and independent. Groups were compared, using Bonferroni correction to account for nonindependent measures and multiple groups. Degree distribution variance was greater in patients and relatives than controls in the 6–9 Hz band (p = 0.0005, p = 0.0009 respectively). Mean degree was greater in patients than healthy controls in the 6–9 Hz band (p = 0.0064). Clustering coefficient was higher in patients and relatives than controls in the 6–9 Hz band (p = 0.0025, p = 0.0013). Characteristic path length did not differ between groups. No differences were found between patients and unaffected relatives. These findings suggest brain network topology differs between patients with IGE and normal controls, and that some of these network measures show similar deviations in patients and in unaffected relatives who do not have epilepsy. This suggests brain network topology may be an inherited endophenotype of IGE, present in unaffected relatives who do not have epilepsy, as well as in affected patients. We propose that abnormal brain network topology may be an endophenotype of IGE, though not in itself sufficient to cause epilepsy.     

Predicting Surgery Targets in Temporal Lobe Epilepsy through Structural Connectome Based Simulations

Temporal lobe epilepsy (TLE) is a prevalent neurological disorder resulting in disruptive seizures. In the case of drug resistant epilepsy resective surgery is often considered. This is a procedure hampered by unpredictable success rates, with many patients continuing to have seizures even after surgery. In this study we apply a computational model of epilepsy to patient specific structural connectivity derived from diffusion tensor imaging (DTI) of 22 individuals with left TLE and 39 healthy controls. We validate the model by examining patient-control differences in simulated seizure onset time and network location. We then investigate the potential of the model for surgery prediction by performing in silico surgical resections, removing nodes from patient networks and comparing seizure likelihood post-surgery to pre-surgery simulations. We find that, first, patients tend to transit from non-epileptic to epileptic states more often than controls in the model. Second, regions in the left hemisphere (particularly within temporal and subcortical regions) that are known to be involved in TLE are the most frequent starting points for seizures in patients in the model. In addition, our analysis also implicates regions in the contralateral and frontal locations which may play a role in seizure spreading or surgery resistance. Finally, the model predicts that patient-specific surgery (resection areas chosen on an individual, model-prompted, basis and not following a predefined procedure) may lead to better outcomes than the currently used routine clinical procedure. Taken together this work provides a first step towards patient specific computational modelling of epilepsy surgery in order to inform treatment strategies in individuals.     

Widespread EEG Changes Precede Focal Seizures

The process by which the brain transitions into an epileptic seizure is unknown. In this study, we investigated whether the transition to seizure is associated with changes in brain dynamics detectable in the wideband EEG, and whether differences exist across underlying pathologies. Depth electrode ictal EEG recordings from 40 consecutive patients with pharmacoresistant lesional focal epilepsy were low-pass filtered at 500 Hz and sampled at 2,000 Hz. Predefined EEG sections were selected immediately before (immediate preictal), and 30 seconds before the earliest EEG sign suggestive of seizure activity (baseline). Spectral analysis, visual inspection and discrete wavelet transform were used to detect standard (delta, theta, alpha, beta and gamma) and high-frequency bands (ripples and fast ripples). At the group level, each EEG frequency band activity increased significantly from baseline to the immediate preictal section, mostly in a progressive manner and independently of any modification in the state of vigilance. Preictal increases in each frequency band activity were widespread, being observed in the seizure-onset zone and lesional tissue, as well as in remote regions. These changes occurred in all the investigated pathologies (mesial temporal atrophy/sclerosis, local/regional cortical atrophy, and malformations of cortical development), but were more pronounced in mesial temporal atrophy/sclerosis. Our findings indicate that a brain state change with distinctive features, in the form of unidirectional changes across the entire EEG bandwidth, occurs immediately prior to seizure onset. We postulate that these changes might reflect a facilitating state of the brain which enables a susceptible region to generate seizures.     

Complexity of Multi-Channel Electroencephalogram Signal Analysis in Childhood Absence Epilepsy

Absence epilepsy is an important epileptic syndrome in children. Multiscale entropy (MSE), an entropy-based method to measure dynamic complexity at multiple temporal scales, is helpful to disclose the information of brain connectivity. This study investigated the complexity of electroencephalogram (EEG) signals using MSE in children with absence epilepsy. In this research, EEG signals from 19 channels of the entire brain in 21 children aged 5-12 years with absence epilepsy were analyzed. The EEG signals of pre-ictal (before seizure) and ictal states (during seizure) were analyzed by sample entropy (SamEn) and MSE methods. Variations of complexity index (CI), which was calculated from MSE, from the pre-ictal to the ictal states were also analyzed. The entropy values in the pre-ictal state were significantly higher than those in the ictal state. The MSE revealed more differences in analysis compared to the SamEn. The occurrence of absence seizures decreased the CI in all channels. Changes in CI were also significantly greater in the frontal and central parts of the brain, indicating fronto-central cortical involvement of “cortico-thalamo-cortical network” in the occurrence of generalized spike and wave discharges during absence seizures. Moreover, higher sampling frequency was more sensitive in detecting functional changes in the ictal state. There was significantly higher correlation in ictal states in the same patient in different seizures but there were great differences in CI among different patients, indicating that CI changes were consistent in different absence seizures in the same patient but not from patient to patient. This implies that the brain stays in a homogeneous activation state during the absence seizures. In conclusion, MSE analysis is better than SamEn analysis to analyze complexity of EEG, and CI can be used to investigate the functional brain changes during absence seizures.     

Dynamic Imaging of Coherent Sources Reveals Different Network Connectivity Underlying the Generation and Perpetuation of Epileptic Seizures

The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone) and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS), an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity) between coherent sources was investigated using the renormalized partial directed coherence (RPDC) method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis.     

Towards a large-scale model of patient-specific epileptic spike-wave discharges

Clinical electroencephalographic (EEG) recordings of the transition into generalised epileptic seizures show a sudden onset of spike-wave dynamics from a low-amplitude irregular background. In addition, non-trivial and variable spatio-temporal dynamics are widely reported in combined EEG/fMRI studies on the scale of the whole cortex. It is unknown whether these characteristics can be accounted for in a large-scale mathematical model with fixed heterogeneous long-range connectivities. Here, we develop a modelling framework with which to investigate such EEG features. We show that a neural field model composed of a few coupled compartments can serve as a low-dimensional prototype for the transition between irregular background dynamics and spike-wave activity. This prototype then serves as a node in a large-scale network with long-range connectivities derived from human diffusion-tensor imaging data. We examine multivariate properties in 42 clinical EEG seizure recordings from 10 patients diagnosed with typical absence epilepsy and 50 simulated seizures from the large-scale model using 10 DTI connectivity sets from humans. The model can reproduce the clinical feature of stereotypy where seizures are more similar within a patient than between patients, essentially creating a patient-specific fingerprint. We propose the approach as a feasible technique for the investigation of patient-specific large-scale epileptic features in space and time.     

Dynamics on Networks: The Role of Local Dynamics and Global Networks on the Emergence of Hypersynchronous Neural Activity

Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3–6 Hz) and low-alpha (6–9 Hz) bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80 predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic stratification of people with epilepsy leading to improved diagnostics and therapeutics.     

Inducible brain COX-2 facilitates the recurrence of hippocampal seizures in mouse rapid kindling

Brain cyclooxygenase-2 (COX-2), the rate-limiting enzyme in prostaglandin synthesis, is rapidly and transiently induced by convulsions in hippocampal and cortical neurons. Therefore, we examined the effects of COX-2 on the 'rapid kindling' development in COX-2 knockout mice and in mice treated with nimesulide, a COX-2-selective inhibitor. Rapid kindling development was examined based on the incidence of hippocampal EEG seizures and behavioral seizures following repetitive electrical stimulation of the perforant path at an interval of 40 s, and on the total afterdischarge (AD) duration induced by 50 stimulations. In addition, we measured COX-2 mRNA expression by in situ hybridization and PGE2 concentration using enzyme immunoassay following rapid kindling stimulation. The results suggested that brain COX-2 mRNA levels were markedly increased in the hippocampal neurons and the concentration of PGE2 was elevated significantly, and that the incidence of AD and seizure behavior induction and the total AD duration were significantly decreased under conditions of COX-2 deficiency. Therefore, we concluded that inducible COX-2 facilitates the recurrence of hippocampal seizures.     

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Electroencephalogram (EEG) has been traditionally used to determine which brain regions are the most likely candidates for resection in patients with focal epilepsy. This methodology relies on the assumption that seizures originate from the same regions of the brain from which interictal epileptiform discharges (IEDs) emerge. Preclinical models are very useful to find correlates between IED locations and the actual regions underlying seizure initiation in focal epilepsy. Rats have been commonly used in preclinical studies of epilepsy¹; hence, there exist a large variety of models for focal epilepsy in this particular species. However, it is challenging to record multichannel EEG and to perform brain source imaging in such a small animal. To overcome this issue, we combine a patented-technology to obtain 32-channel EEG recordings from rodents² and an MRI probabilistic atlas for brain anatomical structures in Wistar rats to perform brain source imaging. In this video, we introduce the procedures to acquire multichannel EEG from Wistar rats with focal cortical dysplasia, and describe the steps both to define the volume conductor model from the MRI atlas and to uniquely determine the IEDs. Finally, we validate the whole methodology by obtaining brain source images of IEDs and compare them with those obtained at different time frames during the seizure onset.     

Altered Resting State Brain Dynamics in Temporal Lobe Epilepsy Can Be Observed in Spectral Power,Functional Connectivity and Graph Theory Metrics

Despite a wealth of EEG epilepsy data that accumulated for over half a century, our ability to understand brain dynamics associated with epilepsy remains limited. Using EEG data from 15 controls and 9 left temporal lobe epilepsy (LTLE) patients, in this study we characterize how the dynamics of the healthy brain differ from the “dynamically balanced” state of the brain of epilepsy patients treated with anti-epileptic drugs in the context of resting state. We show that such differences can be observed in band power, synchronization and network measures, as well as deviations from the small world network (SWN) architecture of the healthy brain. The θ (4–7 Hz) and high α (10–13 Hz) bands showed the biggest deviations from healthy controls across various measures. In particular, patients demonstrated significantly higher power and synchronization than controls in the θ band, but lower synchronization and power in the high α band. Furthermore, differences between controls and patients in graph theory metrics revealed deviations from a SWN architecture. In the θ band epilepsy patients showed deviations toward an orderly network, while in the high α band they deviated toward a random network. These findings show that, despite the focal nature of LTLE, the epileptic brain differs in its global network characteristics from the healthy brain. To our knowledge, this is the only study to encompass power, connectivity and graph theory metrics to investigate the reorganization of resting state functional networks in LTLE patients.     

Epileptic seizures may begin hours in advance of clinical onset: a report of five patients

Mechanisms underlying seizure generation are traditionally thought to act over seconds to minutes before clinical seizure onset. We analyzed continuous 3- to 14-day intracranial EEG recordings from five patients with mesial temporal lobe epilepsy obtained during evaluation for epilepsy surgery. We found localized quantitative EEG changes identifying prolonged bursts of complex epileptiform discharges that became more prevalent 7 hr before seizures and highly localized subclinical seizure-like activity that became more frequent 2 hr prior to seizure onset. Accumulated energy increased in the 50 min before seizure onset, compared to baseline. These observations, from a small number of patients, suggest that epileptic seizures may begin as a cascade of electrophysiological events that evolve over hours and that quantitative measures of preseizure electrical activity could possibly be used to predict seizures far in advance of clinical onset.     

Characterization of PTZ-induced seizure susceptibility in a down syndrome mouse model that overexpresses CSTB

Down syndrome (DS) is a complex genetic syndrome characterized by intellectual disability, dysmorphism and variable additional physiological traits. Current research progress has begun to decipher the neural mechanisms underlying cognitive impairment, leading to new therapeutic perspectives. Pentylenetetrazol (PTZ) has recently been found to have positive effects on learning and memory capacities of a DS mouse model and is foreseen to treat DS patients. But PTZ is also known to be a convulsant drug at higher dose and DS persons are more prone to epileptic seizures than the general population. This raises concerns over what long-term effects of treatment might be in the DS population. The cause of increased propensity for epilepsy in the DS population and which Hsa21 gene(s) are implicated remain unknown. Among Hsa21 candidate genes in epilepsy, CSTB, coding for the cystein protease inhibitor cystatin B, is involved in progressive myoclonus epilepsy and ataxia in both mice and human. Thus we aim to evaluate the effect of an increase in Cstb gene dosage on spontaneous epileptic activity and susceptibility to PTZ-induced seizure. To this end we generated a new mouse model trisomic for Cstb by homologous recombination. We verified that increasing copy number of Cstb from Trisomy (Ts) to Tetrasomy (Tt) was driving overexpression of the gene in the brain, we checked transgenic animals for presence of locomotor activity and electroencephalogram (EEG) abnormalities characteristic of myoclonic epilepsy and we tested if those animals were prone to PTZ-induced seizure. Overall, the results of the analysis shows that an increase in Cstb does not induce any spontaneous epileptic activity and neither increase or decrease the propensity of Ts and Tt mice to myoclonic seizures suggesting that Ctsb dosage should not interfere with PTZ-treatment.     

Scalp EEG for the diagnosis of epilepsy and photosensitivity in the baboon

Spontaneous seizures have been observed in several baboon species housed at the Southwest National Primate Research Center (SNPRC), including Papio hamadryas anubis and cynocephalus/anubis, hamadryas/anubis, and papio/anubis hybrids. The goal of this study was to establish a noninvasive, reliable electroencephalographic technique to characterize epilepsy phenotypes and assess photosensitivity in these subspecies. Thirty baboons with witnessed seizures, and 15 asymptomatic baboons underwent scalp electroencephalograms (EEGs) with photic stimulation (PS). The sensitivity and specificity of surface EEG for identifying interictal epileptic discharges (IEDs) in baboons with witnessed seizures were examined. The morphology of IEDs, electroclinical features of seizures and responses to PS, reproducibility of EEG findings, and intrarater reliability were also evaluated. Twenty-three seizure baboons (77%) demonstrated IEDs, predominantly with frequencies of 4-6 Hz in 18 baboons and 2-3 Hz in six baboons. Two seizure animals had a mixture of 2-3-Hz and 4-6-Hz IEDs. All animals with 2-3-Hz IEDs were 3 years old or younger. Myoclonic seizures (MS) and generalized tonic-clonic seizures (GTCS) were recorded in 13 baboons (43%). PS activated IEDs in 15 baboons (50%) and seizures in nine baboons. The presence of IEDs or seizures was not associated with a particular gender or species (Fisher exact test, alpha=0.05). Seizures were more common in animals >3 years old, while PS-induced IEDs and seizures were more prevalent in P.h. anubis/cynocephalus crosses compared to P.h. anubis. In the asymptomatic controls, IEDs were recorded in five baboons (33%), and photoparoxysmal responses were observed in two (13%). Surface EEG is a sensitive and reliable instrument for characterizing the epilepsy encountered in Papio species. Electroclinically, the seizure animals had generalized epilepsy with photosensitivity. The variation in IED morphology may be age-related or it may reflect different epileptic phenotypes. Ketamine provoked IEDs and seizures in most seizure animals and only in a few asymptomatic baboons; therefore, it may enhance the sensitivity of surface EEG for detecting a predisposition to epilepsy.     

Multiscale Entropy of Electroencephalogram as a Potential Predictor for the Prognosis of Neonatal Seizures

Objective

Increasing animal studies supported the harmful effects of prolonged or frequent neonatal seizures in developing brain, including increased risk of later epilepsy. Various nonlinear analytic measures had been applied to investigate the change of brain complexity with age. This study focuses on clarifying the relationship between later epilepsy and the changes of electroencephalogram (EEG) complexity in neonatal seizures.

Methods

EEG signals from 19 channels of the whole brain from 32 neonates below 2 months old were acquired. The neonates were classified into 3 groups: 9 were normal controls, 9 were neonatal seizures without later epilepsy, and 14 were neonatal seizures with later epilepsy. Sample entropy (SamEn), multiscale entropy (MSE) and complexity index (CI) were analyzed.

Results

Although there was no significant change in SamEn, the CI values showed significantly decreased over Channels C3, C4, and Cz in patients with neonatal seizures and later epilepsy compared with control group. More multifocal epileptiform discharges in EEG, more abnormal neuroimaging findings, and higher incidence of future developmental delay were noted in the group with later epilepsy.

Conclusions

Decreased MSE and CI values in patients with neonatal seizures and later epilepsy may reflect the mixed effects of acute insults, underlying brain immaturity, and prolonged seizures-related injuries. The analysis of MSE and CI can therefore provide a quantifiable and accurate way to decrypt the mystery of neonatal seizures, and could be a promising predictor.     

Network analysis of intrinsic functional brain connectivity in Alzheimer's disease

Functional brain networks detected in task-free (“resting-state”) functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.     

颅内电极在感觉运动区皮质发育不良癫痫手术中的应用

目的：探讨长程颅内电极监测及电刺激方法,在感觉运动区皮质发育不良的难治性癫痫外科手术评估中的意义。方法：筛选MRI提示的皮质发育不良区域与重要功能区-感觉运动区位置关系密切的11例难治性癫痫患者,且头皮长程视频脑电监测及PET检查也初步提示癫痫发作与皮质发育不良所在脑区有关,在可疑脑区放置颅内电极,然后进行颅内电极长程视频脑电监测及电刺激检测,对癫痫起源位置及功能区定位,明确癫痫发作起源区域与感觉运动功能区的解剖学关系,在定位结果指导下进行切除术。结果：11例中3例位于左侧半球,8例位于右侧半球,11例感觉运动功能区皮质分布均存在不同程度变异,7例癫痫发作起源区域与感觉运动功能区一定范围重叠,其中5例与感觉区重叠,该5例切除了起源区域与发作有关的部分感觉区,2例部分致痫灶与运动区重叠,该2例仅切除了除与发作有关的运动区以外的癫痫起源区域,4例癫痫发作起源区域与感觉运动功能区相对独立,该4例完全切除癫痫发作起源区域;手术后6例患者发作消失,2例患者发作频率减少90%以上,1例癫痫发作控制无效,2例患者发生部分感觉缺失,但对生活无明显影响。结论：在皮质发育不良的癫痫患者中,有较高比例的病人伴有功能区皮层分布的变异,长程颅内电极监测及电刺激能够实现癫痫起源区域及功能区精确定位,明确功能区变异情况,对于指导病灶切除,避免损伤功能区皮质,减少术后并发症具有重要意义。     

颅内电极在感觉运动区皮质发育不良癫痫手术中的应用

目的:探讨长程颅内电极监测及电刺激方法,在感觉运动区皮质发育不良的难治性癫痫外科手术评估中的意义。方法:筛选MRI提示的皮质发育不良区域与重要功能区-感觉运动区位置关系密切的11例难治性癫痫患者,且头皮长程视频脑电监测及PET检查也初步提示癫痫发作与皮质发育不良所在脑区有关,在可疑脑区放置颅内电极,然后进行颅内电极长程视频脑电监测及电刺激检测,对癫痫起源位置及功能区定位,明确癫痫发作起源区域与感觉运动功能区的解剖学关系,在定位结果指导下进行切除术。结果:11例中3例位于左侧半球,8例位于右侧半球,11例感觉运动功能区皮质分布均存在不同程度变异,7例癫痫发作起源区域与感觉运动功能区一定范围重叠,其中5例与感觉区重叠,该5例切除了起源区域与发作有关的部分感觉区,2例部分致痫灶与运动区重叠,该2例仅切除了除与发作有关的运动区以外的癫痫起源区域,4例癫痫发作起源区域与感觉运动功能区相对独立,该4例完全切除癫痫发作起源区域;手术后6例患者发作消失,2例患者发作频率减少90%以上,1例癫痫发作控制无效,2例患者发生部分感觉缺失,但对生活无明显影响。结论:在皮质发育不良的癫痫患者中,有较高比例的病人伴有功能区皮层分布的变异,长程颅内电极监测及电刺激能够实现癫痫起源区域及功能区精确定位,明确功能区变异情况,对于指导病灶切除,避免损伤功能区皮质,减少术后并发症具有重要意义。     

The piriform cortex and the cortical nucleus of the amygdala in epileptogenesis--the role of the rostrocaudal gradient

The seizure susceptibility of amygdaloid complex in rat was investigated. In piriform cortex and cortical nucleus of amygdaloid complex the structural and electrophysiological rostro-caudal differences were found (using relative spectral densities EEG, seizure thresholds, electrical kindling rate). The fundamental dependence of severity of motor seizures from structural (nuclear or cortical) organization of stimulating area was shown. There were more of limbic stages while stimulating anterior and posterior cortical nuclei, and there were more generalized stages while stimulating piriform and periamygdaloid cortex. Using the model of electrical kindling anticonvulsant effects of Sacricin were demonstrated. Sacricin is one of the compounds of polycarbonic acid. Sacricin has fully coped the process of secondary generalization of epileptic seizures.     

Neurosurgical management of epilepsy: a personal perspective in 1983

The therapeutic goal in the neurosurgical treatment of medically intractable epilepsy is complete seizure control, for both biologic and psychosocial reasons. Cortical resections are more likely to accomplish this than other surgical alternatives for epilepsy. Although abnormalities on new imaging techniques (CT, positron emission scanning) aid in identifying the epileptic focus, interictal epileptiform EEG changes remain the main indicator of focal origin of the seizures. Where this is equivocal, direct brain recording of spontaneous seizures with subdural electrodes is of value in identifying the side and lobe of seizure onset. The cortical resection is then tailored by the extent of the interictal electrocorticographic abnormalities and functional identification of essential areas such as those for language, using an electrical stimulation mapping technique, under local anesthesia. With this approach, half of the patients with temporal lobe foci are seizure-free since the time of operation, over two-thirds become so with time, and over three-quarters have at least very major reductions in seizure frequency.