Incidence of seizures and EEG abnormalities among offspring of epileptic patients

Summary The marriage rate of epileptic patients was 62% in males und 78% in females. Compared with the rates in the general population, the male patients had a 15% lower rate, but there was no difference in females. There were 263 patients with at least one offspring selected for the study. There were 243 sons and 272 daughters (506 total, 1.9 per patient). Distribution by types of seizure was awakening grand mal, absence or myoclonic petit mal in 24%, grand mal with no aura in 21%, grand mal during sleep in 23%, diffuse grand mal in 7%, grand mal with aura in 13%, psychomotor seizure in 9%, and focal seizure in 3%. The probands were composed of 79% idiopathic and 21% symptomatic in pathogenetic classification. An epileptic EEG abnormality was demonstrated in 22% of male and 44% of female probands.The incidence of seizures among offspring was 2.4% (4.2% age-corrected) in a narrow sense (epilepsy) and 9.1% in a broad sense including febrile convulsions. The latter morbidity was 11.0% for the idiopathic and 3.2% for the symptomatic group; 11.0% for female and 6.9% for male probands; 10.2% for sons and 8.1% for daughters. The figure was higher for the probands with the age range at onset of seizure of 0–4 years (20.6%) and 20–29 years (12.6%) than for those with other age ranges; higher for those with awakening grand mal, absence, myoclonic petit mal, or grand mal with no aura than for those with other types of seizure; and higher for those with family history of epilepsy than those without it.Possible correlation of types of seizure between probands and offspring was demonstrated. Thirty-seven percent of offspring exhibited epileptic EEG abnormalities, and the ratio of epileptic EEG abnormalities to clinical manifestation is about 4:1.Possible existence of familial aggregation of EEG abnormalities and of two kinds of families with large or small epileptic predisposition was indicated.The importance of the role of hereditary and environmental factors in epileptic pathogenesis is proved, and the results of an investigation of congenital malformation among offspring of epileptic mothers are presented. These results were considered to be useful for genetic counseling of epileptic patients.     

Behavioral management of epileptic seizures following EEG biofeedback training of the sensorimotor rhythm

Eight severely epileptic patients, four males and four females, ranging in age from 10 to 29 years, were trained to increase 12–14 Hz EEG activity from the regions overlying the Rolandic area. This activity, the sensorimotor rhythm(SMR), has been hypothesized to be related to motor inhibitory processes(Sterman, 1974). The patients represented a crosssection of several different types of epilepsy, including grand mal, myoclonic, akinetic, focal, and psychomotor types. Three of them had varying degrees of mental retardation. SMR was detected by a combination of an analog filtering system and digital processing. Feedback, both auditory and/or visual, was provided whenever one-half second of 12–14-Hz activity was detected in the EEG. Patients were provided with additional feedback keyed by the output of a 4–7-Hz filter which indicated the presence of epileptiform spike activity, slow waves, or movement. Feedback for SMR was inhibited whenever slow-wave activity spikes or movement was also present. During the treatment period most of the patients showed varying degrees of improvement. Two of the patients who had been severely epileptic, having multiple seizures per week, have been seizure free for periods of up to 1 month. Other patients have developed the ability to block many of their seizures. Seizure intensity and duration have also decreased. Furthermore, the successful patients demonstrated an increase in the amount of SMR and an increase in amplitude of SMR during the training period. Spectral analyses for the EEGs were performed periodically. The effectiveness of SMR conditioning for the control of epileptic seizures is evaluated in terms of patient characteristics and type of seizures.     

The methods of automatic analysis of epileptic EEG

The methods of automatic evaluation of epileptic EEG are reviewed. The aims of the computer analysis of seizure activity and different approaches to this problem are presented.     

Application of a dissimilarity index of EEG and its sub-bands on prediction of induced epileptic seizures from rat's EEG signals

ObjectiveEpileptic seizures are defined as manifest of excessive and hyper-synchronous activity of neurons in the cerebral cortex that cause frequent malfunction of the human central nervous system. Therefore, finding precursors and predictors of epileptic seizure is of utmost clinical relevance to reduce the epileptic seizure induced nervous system malfunction consequences. Researchers for this purpose may even guide us to a deep understanding of the seizure generating mechanisms. The goal of this paper is to predict epileptic seizures in epileptic rats.MethodsSeizures were induced in rats using pentylenetetrazole (PTZ) model. EEG signals in interictal, preictal, ictal and postictal periods were then recorded and analyzed to predict epileptic seizures. Epileptic seizures were predicted by calculating an index in consecutive windows of EEG signal and comparing the index with a threshold. In this work, a newly proposed dissimilarity index called Bhattacharyya Based Dissimilarity Index (BBDI), dynamical similarity index and fuzzy similarity index were investigated.ResultsBBDI, dynamical similarity index and fuzzy similarity index were examined on case and control groups and compared to each other. The results show that BBDI outperforms dynamical and fuzzy similarity indices. In order to improve the results, EEG sub-bands were also analyzed. The best result achieved when the proposed dissimilarity index was applied on Delta sub-band that predicts epileptic seizures in all rats with a mean of 299.5 s.ConclusionThe dissimilarity of neural network activity between reference window and present window of EEG signal has a significant increase prior to an epileptic seizure and the proposed dissimilarity index (BBDI) can reveal this variation to predict epileptic seizures. In addition, analyzing EEG sub-bands results in more accurate information about constituent neuronal activities underlying the EEG since certain changes in EEG signal may be amplified when each sub-band is analyzed separately.SignificanceThis paper presents application of a dissimilarity index (BBDI) on EEG signals and its sub-bands to predict PTZ-induced epileptic seizures in rats. Based on the results of this work, BBDI will predict epileptic seizures more accurately and more reliably compared to current indices that increases epileptic patient comfort and improves patient outcomes.     

Identifying an increased risk of epileptic seizures using a multi-feature EEG–ECG classification

Epilepsy, a neurological disorder in which patients suffer from recurring seizures, affects approximately 1% of the world population. In spite of available drug and surgical treatment options, more than 25% of individuals with epilepsy have seizures that are uncontrollable. For these patients with intractable epilepsy, the unpredictability of seizure occurrence underlies an enhanced risk of sudden unexpected death or morbidity. A system that could warn the patient of the impending event or trigger an antiepileptic device would dramatically increase the quality of life for those patients. Here, we proposed a patient-specific algorithm for possible seizure warning using machine learning classification of 34 algorithmic features derived from EEG–ECG recordings. We evaluated our algorithm on unselected and continuous recordings of 12 patients (total of 108 seizures and 3178-h). Good out-of-sample performances were observed around 25% of the patients with an average preictal period around 30 min and independently of the EEG type (scalp or intracranial). Inspection of the most discriminative EEG–ECG features revealed that good classification rates reflected specific physiological precursors, particularly related to certain stages of sleep. From these observations, we conclude that our algorithmic strategy enables a quantitative way to identify “pro-ictal” states with a high risk of seizure generation.     

Proton magnetic resonance spectroscopy in patients with solitary and sporadic temporal lobe epileptic seizures

Proton magnetic resonance spectroscopy (¹H MRS) is an optional diagnostic method for potential epilepsy surgery candidates. The aim of this study was to determine the credibility of ¹H MRS examination in a group of patients suffering from solitary and sporadic epileptic seizures generated in temporal lobe. We recorded a 100% sensitivity of ¹H MRS in a group of ten patients in terms of detection of a pathological process in the temporal lobe. ¹H MRS also enabled determination of lateralization of the pathological process in three patients with bilateral epileptiform abnormalities on electroencephalography. Based on these results we suggest new perspectives on ¹H MRS as a part of standard diagnostic algorithm for solitary and sporadic temporal lobe epileptic seizures, particularly in cases with normal electroencephalography and magnetic resonance imaging findings.     

Association of refractory complex partial seizures with a polymorphism of ApoE genotype

Apolipoprotein E (ApoE) is a constituent of many types of lipoproteins that play a role in metabolism of cholesterol and lipids in the body as well as in the brain. ApoE is synthesised in astrocytes and microglia and enter to neurons through LDL, LRP and VLDL receptors. Recently it was shown that ApoE is also produced in neurons. ApoE has a role in modulating learning and memory, structural plasticity, mobilization of cholesterol in repair, growth and maintenance of myelin and neuronal membranes during development and aging, and cell death after ischemic, convulsive, or other type of brain injury. The aim of this research was to investigate the possible association of ApoE gene polymorphism with the development of resistance to pharmacological therapy in patients with partial complex seizures with or without secondary generalization. In this prospective matched-pair controlled study, 60 patients with cryptogenic epilepsy with complex partial seizures, with or without secondary generalization, who have been suffering for five or more years, were studied. The first group comprised 30 patients refractory to the current therapy, while the second group consisted of patients with well-controlled seizures. The refractory and non-refractory groups of patients differed significantly in their phenotypes. Phenotype E3/4 was six times more frequent in refractory group than among non-refractory group. The lack of response was shown to be significantly associated with the presence of epsilon4 allele. This study provided evidence that the presence of epsilon4 allele is more often associated with a lack of response to current antiepileptic drugs as compared to epsilon2 and epsilon3 alleles.     

The multipleparameter combinatory analysis of EEG rhythms in norm and at schizophrenia

On the base of EEG records of 38 healthy subjects and 17 schizophrenic patients the statistical structural analysis of 176 elementary characteristics in all 11 spectral ranges for each of 4 experimental conditions was carried out, employing "Kora-n" recognition algorithm, adopted for EEG analysis by Kaplan. The list of characteristics with a minimal error revealed statistically significant differences between spectral power of delta- and theta-ranges in healthy subjects and schizophrenic patients. Spectral power of these slow rhythms was always higher in the formers then in the latter. As a whole, in schizophrenic patients the decrease of delta-rhythm spectral power in the lower frontal area of right hemisphere and theta-rhythm - in the lower temporal area of left hemisphere most frequently is observed. These results are in agreement with hypofrontality and hypotemporality characteristic of schizophrenic patients and testify to the lack of "fundamental" brain base of cognitive functions. These facts are evidently connected with the significant neurochemical disturbances taking place in schizophrenia.     

Models of epileptic seizures in immature rats

Models of basic types of epileptic seizures are elaborated not only in adult but also in immature rodents. It is important because at least half of human epilepsies starts during infancy and childhood. This paper presents a review of chemically and electrically induced models of generalized convulsive and nonconvulsive (absence) seizures as well as models of partial simple (neocortical) and complex (limbic) seizures in immature rats. These models can also serve as a tool for study the development of central nervous system and motor abilities because the level of maturation is reflected in seizure semiology. Age-dependent models of epileptic seizures (absences and flexion seizures) are discussed. Models of seizures in immature animals should be used for testing of potential antiepileptic drugs.     

Role of oxidative stress in epileptic seizures

Oxidative stress resulting from excessive free-radical release is likely implicated in the initiation and progression of epilepsy. Therefore, antioxidant therapies aimed at reducing oxidative stress have received considerable attention in epilepsy treatment. However, much evidence suggests that oxidative stress does not always have the same pattern in all seizures models. Thus, this review provides an overview aimed at achieving a better understanding of this issue. We summarize work regarding seizure models (i.e., genetic rat models, kainic acid, pilocarpine, pentylenetetrazol, and trimethyltin), oxidative stress as an etiologic factor in epileptic seizures (i.e., impairment of antioxidant systems, mitochondrial dysfunction, involvement of redox-active metals, arachidonic acid pathway activation, and aging), and antioxidant strategies for seizure treatment. Combined, this review highlights pharmacological mechanisms associated with oxidative stress in epileptic seizures and the potential for neuroprotection in epilepsy that targets oxidative stress and is supported by effective antioxidant treatment.     

Excitatory aminoacids and epileptic seizures in immature brain

Data on convulsant and anticonvulsant action of drugs influencing excitatory amino acid receptors in developing rats are reviewed. Agonists of NMDA type of receptors NMDA and homocysteic acid, elicited an age-related seizure pattern--flexion, emprosthotonic seizures--in the first three postnatal weeks of rats. Generalized clonic-tonic seizures appeared only after a longer latency. Kainic acid administration resulted in epileptic automatisms and later in minimal, clonic seizures followed by generalized tonic-clonic seizures. A decrease of sensitivity to convulsant action with age is a general rule for all agonists tested. Different anticonvulsant action of NMDA and nonNMDA antagonists was demonstrated in a model of generalized tonic-clonic seizures induced by pentetrazol, whereas their action against epileptic afterdischarges elicited by electrical stimulation of cerebral cortex was similar. Again, higher efficacy in younger animals was a rule. As far as metabotropic glutamate receptors are concerned, agonists of groups II and III were shown to protect against convulsant action of homocysteic acid in immature rats and an antagonist of group I receptors MPEP suppressed the tonic phase of generalized tonic-clonic seizures induced by pentetrazol more efficiently in younger than in more mature rat pups. Unfortunately, a higher sensitivity to the action of antagonists of ionotropic glutamate receptors was demonstrated also for unwanted side effects (motor functions were compromized). In contrast, glutamate metabotropic receptor antagonist MPEP did not exhibit any serious side effects in rat pups.     

Ultradian rhythms in the EEG and task performance

The purpose of this work was to investigate the presence of ultradian rhythms in: 1. levels of electroencephalographic activation; 2. interhemispheric correlation and 3. the performance of two cognitive tasks, and the correlation between these variables. Eight volunteers, aged 20 to 30, participated in the experiment. Two sessions were carried out: one from 0800 to 1400 on one day and the other from 1400 to 2000 another day. Samples of EEG activity were taken every 15 min at rest with eyes open in left and right temporal, central, parietal and occipital derivations referred to the ipsilateral earlobe the performance on two tasks, one logico-analytical (left hemisphere functions) and one spatial test (right hemisphere functions) was assessed. As control, body and environmental temperature were recorded. To test for the presence of ultradian rhythms, the data were subjected to a Fourier analysis. Different EEG variables showed rhythmicity throughout the sessions, principally with slow oscillation periods (3 and 6h); ultradian rhythms with 3h periods were also found in body temperature, while task performance showed no significant rhythmic patterns during sessions. Finally, no significant correlations were found between physiological variables evaluated and task performance.     

Travelling waves and EEG patterns during epileptic seizure: analysis with an integrate-and-fire neural network

Epilepsy is characterized by paradoxical patterns of neural activity. They may cause different types of electroencephalogram (EEG), which dynamically change in shape and frequency content during the temporal evolution of seizure. It is generally assumed that these epileptic patterns may originate in a network of strongly interconnected neurons, when excitation dominates over inhibition. The aim of this work is to use a neural network composed of 50 x 50 integrate-and-fire neurons to analyse which parameter alterations, at the level of synapse topology, may induce network instability and epileptic-like discharges, and to study the corresponding spatio-temporal characteristics of electrical activity in the network. We assume that a small group of central neurons is stimulated by a depolarizing current (epileptic focus) and that neurons are connected via a Mexican-hat topology of synapses. A signal representative of cortical EEG (ECoG) is simulated by summing the membrane potential changes of all neurons. A sensitivity analysis on the parameters describing the synapse topology shows that an increase in the strength and in spatial extension of excitatory vs. inhibitory synapses may cause the occurrence of travelling waves, which propagate along the network. These propagating waves may cause EEG patterns with different shape and frequency, depending on the particular parameter set used during the simulations. The resulting model EEG signals include irregular rhythms with large amplitude and a wide frequency content, low-amplitude high-frequency rapid discharges, isolated or repeated bursts, and low-frequency quasi-sinusoidal patterns. A slow progressive temporal variation in a single parameter may cause the transition from one pattern to another, thus generating a highly non-stationary signal which resembles that observed during ECoG measurements. These results may help to elucidate the mechanisms at the basis of some epileptic discharges, and to relate rapid changes in EEG patterns with the underlying alterations at the network level.     

Spectral analysis of EEG in normal rats and in rats genetically predisposed to seizures

Spectral and visual analyses were performed on the EEG of the motor and visual cortex, hippocampus, caudate nucleus, and intralaminary thalamic nuclei in two strains of rats; animals were maintained in a state of "awake immobility." It was found that KM rats, genetically predisposed to audiogenic fits, differed from the Wistar strain not subject to this genetic predisposition in that mean relative intensity of theta rhythm diminished and high amplitude slow irregular hippocampal activity intensified in the neocortex, as did generalized spindling. Susceptibility to seizure was reduced in KM rats as a result of protracted and graded increasing camphor administration to match the level of mean EEG spectral density changes characteristic of the Wistar strain. The part which brainstem reticular formation mechanisms may play in raising susceptibility to seizures is discussed, together with the EEG pattern characteristic of this condition.Institute of Higher Nervous Activity and Neurophysiology, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 19, No. 2, pp. 171–179, March–April, 1987.     

Scaling effects and spatio-temporal multilevel dynamics in epileptic seizures

Epileptic seizures are one of the most well-known dysfunctions of the nervous system. During a seizure, a highly synchronized behavior of neural activity is observed that can cause symptoms ranging from mild sensual malfunctions to the complete loss of body control. In this paper, we aim to contribute towards a better understanding of the dynamical systems phenomena that cause seizures. Based on data analysis and modelling, seizure dynamics can be identified to possess multiple spatial scales and on each spatial scale also multiple time scales. At each scale, we reach several novel insights. On the smallest spatial scale we consider single model neurons and investigate early-warning signs of spiking. This introduces the theory of critical transitions to excitable systems. For clusters of neurons (or neuronal regions) we use patient data and find oscillatory behavior and new scaling laws near the seizure onset. These scalings lead to substantiate the conjecture obtained from mean-field models that a Hopf bifurcation could be involved near seizure onset. On the largest spatial scale we introduce a measure based on phase-locking intervals and wavelets into seizure modelling. It is used to resolve synchronization between different regions in the brain and identifies time-shifted scaling laws at different wavelet scales. We also compare our wavelet-based multiscale approach with maximum linear cross-correlation and mean-phase coherence measures.