Normal EEG Activity Research Articles

Artifacts Deceive: The Electroretinogram in the Electroencephalogram of a teenager with cerebral anoxia.

Artifacts on an electroencephalogram (EEG) - whether physiologic or non-physiologic - can be common and are important to recognize to prevent errors in interpretation. One such EEG artifact is an electroretinogram (ERG) artifact which occurs during photic stimulation. Typically, of a low amplitude, its presence is usually obscured by normal EEG activity over the frontopolar channels but it can appear prominent in very suppressed or EEG recordings showing electrocerebral inactivity. Overall, rarely reported in the literature, the purpose of this case report is to highlight the presence of an ERG artifact in a teenage boy where EEG was obtained after a cerebral anoxic event. It is important that EEG readers identify this to be a non-cerebral waveform in order to provide an accurate assessment of neurologic prognosis.

AWAreness during REsuscitation - II: A multi-center study of consciousness and awareness in cardiac arrest

IntroductionCognitive activity and awareness during cardiac arrest (CA) are reported but ill understood. This first of a kind study examined consciousness and its underlying electrocortical biomarkers during cardiopulmonary resuscitation (CPR). MethodsIn a prospective 25-site in-hospital study, we incorporated a) independent audiovisual testing of awareness, including explicit and implicit learning using a computer and headphones, with b) continuous real-time electroencephalography(EEG) and cerebral oxygenation(rSO2) monitoring into CPR during in-hospital CA (IHCA). Survivors underwent interviews to examine for recall of awareness and cognitive experiences. A complementary cross-sectional community CA study provided added insights regarding survivors’ experiences. ResultsOf 567 IHCA, 53(9.3%) survived, 28 of these (52.8%) completed interviews, and 11(39.3%) reported CA memories/perceptions suggestive of consciousness. Four categories of experiences emerged: 1) emergence from coma during CPR (CPR-induced consciousness [CPRIC]) 2/28(7.1%), or 2) in the post-resuscitation period 2/28(7.1%), 3) dream-like experiences 3/28(10.7%), 4) transcendent recalled experience of death (RED) 6/28(21.4%). In the cross-sectional arm, 126 community CA survivors’ experiences reinforced these categories and identified another: delusions (misattribution of medical events). Low survival limited the ability to examine for implicit learning. Nobody identified the visual image, 1/28(3.5%) identified the auditory stimulus. Despite marked cerebral ischemia (Mean rSO2 = 43%) normal EEG activity (delta, theta and alpha) consistent with consciousness emerged as long as 35–60 minutes into CPR. ConclusionsConsciousness. awareness and cognitive processes may occur during CA. The emergence of normal EEG may reflect a resumption of a network-level of cognitive activity, and a biomarker of consciousness, lucidity and RED (authentic “near-death” experiences).

EPILEPTIC EEG IDENTIFICATION BASED ON HYBRID FEATURE EXTRACTION

Electroencephalogram (EEG) signals are widely used as an effective method for epilepsy analysis and diagnosis. For the establishment of an accurate and efficient epilepsy EEG identification system, it is very important to properly extract the features of EEG signals and select appropriate combination features. This paper proposes an automatic epileptic EEG identification method based on hybrid feature extraction. It uses temporal and frequency domain analysis, nonlinear analysis and one-dimensional local pattern recognition method to extract epileptic EEG features. Gradient energy operator and local speed pattern are proposed to better reflect typical feature in the active EEG signals measured during seizure-free intervals. The genetic algorithm is used to select the obtained hybrid features; then the AdaBoost classifier is used to classify epileptic EEG under various classification conditions. Classification results on the dataset developed by University of Bonn show that the proposed method can be used to classify normal EEG, interictal EEG and seizure activity with only a few features. Compared with related researches using the same dataset, the proposed method can obtain an equally satisfactory classification accuracy while the feature amount is reduced by 61–95%. In particular, the classification accuracy of the interictal and normal EEG can reach 99%.

A novel approach based on wavelet analysis and arithmetic coding for automated detection and diagnosis of epileptic seizure in EEG signals using machine learning techniques

Epilepsy, a common neurological disorder, is generally detected by electroencephalogram (EEG) signals. Visual inspection and interpretation of EEGs is a slow, time consuming process that is vulnerable to error and subjective variability. Consequently, several efforts to develop automatic epileptic seizure detection and classification methods have been made. The present study proposes a novel computer aided diagnostic technique (CAD) based on the discrete wavelet transform (DWT) and arithmetic coding to differentiate epileptic seizure signals from normal (seizure-free) signals. The proposed CAD technique comprises three steps. The first step decomposes EEG signals into approximations and detail coefficients using DWT while discarding non-significant coefficients in view of threshold criteria; thus, limiting the number of significant wavelet coefficients. The second step converts significant wavelet coefficients to bit streams using arithmetic coding to compute the compression ratio. In the final step, the compression feature set is standardized, whereupon machine-learning classifiers detect seizure activity from seizure-free signals. We employed the widely used benchmark database from Bonn University to compare and validate the technique with results from prior approaches. The proposed method achieved a perfect classification performance (100% accuracy) for the detection of epileptic seizure activity from EEG data, using both linear and non-liner machine-learning classifiers. This CAD technique can thus be considered robust with an extraordinary detection capability that discriminates epileptic seizure activity from seizure-free and normal EEG activity with simple linear classifiers. The method has the potential for efficient application as an adjunct for the clinical diagnosis of epilepsy.

Electroencephalographic assessment of pneumatically powered penetrating and non-penetrating captive-bolt stunning of bulls

The electroencephalographic (EEG) responses of 31 bulls (zebu crossbred cattle) stunned with either pneumatically powered Jarvis penetrating (PCB) or non-penetrating captive bolt (NPCB) was examined. Animals were organized into two treatment groups: PCB (n = 20); and NPCB (n = 11) stunning, both using airline pressures of 220 psi (1517 kPa). All bulls shot with PCB (n = 20/20) had patterns of EEG activity that were inconsistent with consciousness. Of the cattle shot with NPCB 82% (n = 9/11) showed waveforms suggesting complete unconsciousness. After stunning two NPCB bulls had periods of normal EEG activity and maintenance (Ptot, delta, theta, beta) or increased (alpha) spectral power compared to pre-treatment values, indicating incomplete concussion. The study showed that pneumatic PCB stunning was effective in rendering all bulls unconscious, while NPCB was less effective. This highlights the potential animal welfare risks associated with NPCB compared to PCB stunning of mature bulls in commercial abattoirs.

Chapter 1 - Generalized epilepsies

Idiopathic generalized epilepsies (IGE) are characterized by normal background EEG activity and generalized interictal spike-and-wave discharges in the absence of any evidence of brain lesion. Absence epilepsies are the prototypes of IGEs. In childhood and juvenile absence epilepsies, by definition, all patients manifest absence seizures associated with an EEG pattern of generalized spike-wave (GSW) discharges. In juvenile myoclonic epilepsy, myoclonic jerks, usually affecting shoulders and arms bilaterally and appearing upon awakening, are the most characteristic clinical feature. Myoclonic jerks are accompanied on the EEG by generalized spike/polyspike-and-wave (GSW, GPWS) complexes at 3.5-6Hz. Idiopathic generalized epilepsy with generalized tonic-clonic seizures only is a broad and nonspecific category including all patients with generalized tonic-clonic seizures and an interictal EEG pattern of GSW discharges. Despite the strong heritability and the recent advances in genetic technology, the genetic basis of IGEs remains largely elusive and only in a small minority of patients with classic IGE phenotypes is a monogenic cause identified. Early myoclonic encephalopathy (EME), early infantile encephalopathy with suppression bursts, West syndrome, and Lennox-Gastaut syndrome, once classified among the generalized epilepsies, are now considered to be epileptic encephalopathies. Among them, only Lennox-Gastaut syndrome is characterized by prominent generalized clinical and EEG features.

Electrographic spikes are common in wildtype mice

High-voltage rhythmic electroencephalographic (EEG) spikes have been recorded in wildtype (WT) rats during periods of light slow-wave sleep and passive wakefulness. The source of this activity is unclear but has been attributed to either an inherent form of absence epilepsy or a normal feature of rodent sleep EEG. In contrast, little is known about epileptiform spikes in WT mice. We thus characterize and quantify epileptiform discharges in WT mice for the first time. Thirty-six male WT C57 mice with 24-h wireless telemetry video-EEG recordings were manually scored by blinded reviewers to mark individual spikes and spike trains. Epileptiform spikes were detected in 100% of the recorded WT mice, and spike trains of at least three spikes were recorded in 90% of mice. The spikes were more frequent during the day than at night and were inversely correlated to each animal's locomotor activity. However, the discharges were not absent during active nighttime periods. These discharges may indicate a baseline tendency toward epileptic seizures or perhaps are benign variants of normal rodent background EEG. Nevertheless, a better understanding of baseline WT EEG activity will aid in differentiating pathological and normal EEG activity in mouse epilepsy models.

Atlas of the normal intracranial electroencephalogram: neurophysiological awake activity in different cortical areas.

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Reevaluation of CNS Oxygen Toxicity Seizures in Male Sprague‐Dawley Rats

Prolonged breathing of hyperbaric oxygen (HBO2) results in central nervous system O2 toxicity (CNS‐OT; i.e., seizures, Sz's). The threat of CNS‐OT is what limits the use of HBO2 in hyperbaric, diving and submarine medicine. Past studies have identified CNS‐OT as the onset of visibly detectable tonic‐clonic Sz's preceded by increased cortical EEG activity. It has been our experience, however, that onset of 1st Sz in Sprague‐Dawley (SD) rats is variable between animals and, in some cases, difficult to confirm in real time. This is problematic because the latency time to seizures (LSz) is how the risk of CNS‐OT is evaluated in hyperbaric research. Consequently, we have begun using longer exposures to HBO2 to capture recurring changes in EEG activity and behaviors that can be analyzed offline to redefine the criteria for 1st Sz. We also wanted to know if subsequent Sz's increased in intensity. Accordingly, cortical EEGs were recorded in 27 adult male SD rats that were implanted with a DSI 4‐ET radio transmitter. At least 1 week following surgery, each rat was placed in a hyperbaric chamber and “dived” to 5 ATA O2. 71 Sz's were identified in 27 rats based on quantified changes in cortical EEG activity (NeuroScore 2.1) and our modified Racine scale of six Sz‐related behaviors. A cortical seizure (CSz) was defined as a series of EEG polyspikes that crossed a threshold of 200μV, lasted ≥15 seconds, and contained an increase in theta wave activity coupled with at least one of the Sz‐related behaviors (65% of the Sz were classified as CSz). Two other Sz types were also recorded: neurological seizures (NSz) that included only the EEG profile described above, but without any detectable behavior changes (14%); and behavioral seizure (BSz) that included one or more of the behavioral components without any detectable changes in cortical EEG activity (21%). LSz was calculated from the moment the chamber pressure reached 5 ATA O2 until the onset of CSz, NSz or BSz. The LSz to 1st seizure was 7.2 ± 5.3 min (n= 27), while the 2nd and 3rd Sz's occurred at 26.2 ± 29.88 min (n=25) and 40 ± 40.86 min (n=13), respectively. Remarkably, in between bouts of Sz's, animals exhibited normal behaviors (grooming, exploring, chewing, etc.) and normal EEG activity in 5 ATA O2. There was also a shift in the type of Sz between the 1st and 2nd Sz such that the fraction of BSz + NSz significantly increased from 22% to 44%. Moreover, intensity of the Sz increased progressively with each successive Sz based on our modified Racine score. We conclude that the majority of HBO2 Sz's in SD rats can be readily identified using a combination of defined EEG and behavioral criteria. However, not all Sz's during HBO2 fit both criteria. The occurrence of BSz suggests that neurological Sz's originate outside the cerebral cortex. The occurrence of NSz indicate that some Sz's will be missed in studies that do not measure EEG activity. The fact that 1st Sz is often underwhelming compared to subsequent Sz's suggests the LSz may be overestimated in some animals. To better understand the SD rat model of CNS‐OT, we recommend that future studies need to 1) implant telemetric leads into multiple cortical and subcortical areas to localize the site of Sz‐genesis; and 2) determine the degree of performance impairment during 1st, 2nd & 3rd Sz's.Support or Funding InformationONR N000141310405 & N000141612537

Preventive and Abortive Strategies for Stimulation Based Control of Epilepsy: A Computational Model Study

Epilepsy is a condition in which periods of ongoing normal EEG activity alternate with periods of oscillatory behavior characteristic of epileptic seizures. The dynamics of the transitions between the two states are still unclear. Computational models provide a powerful tool to explore the underlying mechanisms of such transitions, with the purpose of eventually finding therapeutic interventions for this debilitating condition. In this study, the possibility to postpone seizures elicited by a decrease of inhibition is investigated by using external stimulation in a realistic bistable neuronal model consisting of two interconnected neuronal populations representing pyramidal cells and interneurons. In the simulations, seizures are induced by slowly decreasing the conductivity of GABA[Formula: see text] synaptic channels over time. Since the model is bistable, the system will change state from the initial steady state (SS) to the limit cycle (LS) state because of internal noise, when the inhibition falls below a certain threshold. Several state-independent stimulations paradigms are simulated. Their effectiveness is analyzed for various stimulation frequencies and intensities in combination with periodic and random stimulation sequences. The distributions of the time to first seizure in the presence of stimulation are compared with the situation without stimulation. In addition, stimulation protocols targeted to specific subsystems are applied with the objective of counteracting the baseline shift due to decreased inhibition in the system. Furthermore, an analytical model is used to investigate the effects of random noise. The relation between the strength of random noise stimulation, the control parameter of the system and the transitions between steady state and limit cycle are investigated. The study shows that it is possible to postpone epileptic activity by targeted stimulation in a realistic neuronal model featuring bistability and that it is possible to stop seizures by random noise in an analytical model.

A new method to detect event-related potentials based on Pearson's correlation.

Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience. Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise. The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N, where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP’s waveform, these waveforms being time- and phase-locked. In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson’s correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase—in consonance with the stimuli—in EEG signal correlation over all channels. This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs. These hidden components seem to be caused by variations (between each successive stimulus) of the ERP’s inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology. The method we are proposing can be directly used in the form of a process written in the well-known Matlab programming language and can be easily and quickly written in any other software language.Electronic supplementary materialThe online version of this article (doi:10.1186/s13637-016-0043-z) contains supplementary material, which is available to authorized users.

V11 Poster location 011 Seizures in infants with pyridoxine-dependent epilepsy and pyridoxine phosphate oxidase deficiency

Introduction: We report on seizure symptoms and EEGfindings in 4 infants with pyridoxine-dependent epilepsy (PDE) and in one with pyridoxine phosphate oxidase deficiency (PNPO). Methods: Seizure videos and EEG were analysed and compared with seizure videos from our neonatal archive. PDE and PNPO was proven by response to pyridoxine or pyridoxal 5′-phosphate and by relapse after withdrawal. Mutations in the antiquitin gene were found in 3 patients and in the PNPO gene in 1 child. Results: Prolonged erratic multifocal or generalised myoclonic jerks were observed in all infants as well as abnormal eye movements, grimacing, focal or generalised tonic symptoms, crying and irritability. Symptoms often occurred intermixed and with variable intensity. None of >100 archived neonatal seizures of different aetiologies showed a comparable mix of seizure symptoms. In 2 older infants irritability, inconsolable crying and frightful facial expression was the prominent symptom during withdrawal. Divers visual symptoms occurred in a 4 year old child with PNPO (probably because of underdosing) and were suspected in a 14 month old child with PDE during withdrawal. Ictal EEG was very variable. Beside continuous spike wave discharges or suppression burst pattern we registered multifocal sharp waves, intermittent prolonged periods of suppression or even normal EEG activity during the seizures. Conclusion: PDE or PNPO should be considered in infants with prolonged seizures with mixed multifocal myoclonic tonic symptoms, often associated with grimacing and abnormal eye movements.

Analyzing large data sets acquired through telemetry from rats exposed to organophosphorous compounds: An EEG study

The organophosphorous compound soman is an acetylcholinesterase inhibitor that causes damage to the brain. Exposure to soman causes neuropathology as a result of prolonged and recurrent seizures. In the present study, long-term recordings of cortical EEG were used to develop an unbiased means to quantify measures of seizure activity in a large data set while excluding other signal types. Rats were implanted with telemetry transmitters and exposed to soman followed by treatment with therapeutics similar to those administered in the field after nerve agent exposure. EEG, activity and temperature were recorded continuously for a minimum of 2 days pre-exposure and 15 days post-exposure. A set of automatic MATLAB algorithms have been developed to remove artifacts and measure the characteristics of long-term EEG recordings. The algorithms use short-time Fourier transforms to compute the power spectrum of the signal for 2-s intervals. The spectrum is then divided into the delta, theta, alpha, and beta frequency bands. A linear fit to the power spectrum is used to distinguish normal EEG activity from artifacts and high amplitude spike wave activity. Changes in time spent in seizure over a prolonged period are a powerful indicator of the effects of novel therapeutics against seizures. A graphical user interface has been created that simultaneously plots the raw EEG in the time domain, the power spectrum, and the wavelet transform. Motor activity and temperature are associated with EEG changes. The accuracy of this algorithm is also verified against visual inspection of video recordings up to 3 days after exposure.

Quantifying Cortical Activity During General Anesthesia Using Wavelet Analysis

This paper reports on a novel method for quantifying the cortical activity of a patient during general anesthesia as a surrogate measure of the patient's level of consciousness. The proposed technique is based on the analysis of a single-channel (frontal) electroencephalogram (EEG) signal using stationary wavelet transform (SWT). The wavelet coefficients calculated from the EEG are pooled into a statistical representation, which is then compared to two well-defined states: the awake state with normal EEG activity, and the isoelectric state with maximal cortical depression. The resulting index, referred to as the wavelet-based anesthetic value for central nervous system monitoring (WAV(CNS)), quantifies the depth of consciousness between these two extremes. To validate the proposed technique, we present a clinical study which explores the advantages of the WAV(CNS) in comparison with the BIS monitor (Aspect Medical Systems, MA), currently a reference in consciousness monitoring. Results show that the WAV(CNS) and BIS are well correlated (r = 0.969) during periods of steady-state despite fundamental algorithmic differences. However, in terms of dynamic behavior, the WAV(CNS) offers faster tracking of transitory changes at induction and emergence, with an average lead of 15-30 s. Furthermore, and conversely to the BIS, the WAV(CNS) regains its preinduction baseline value when patients are responding to verbal command after emergence from anesthesia. We conclude that the proposed analysis technique is an attractive alternative to BIS monitoring. In addition, we show that the WAV(CNS) dynamics can be modeled as a linear time invariant transfer function. This index is, therefore, well suited for use as a feedback sensor in advisory systems, closed-loop control schemes, and for the identification of the pharmacodynamic models of anesthetic drugs.

Clinical Neurophysiology: EEG–Video Monitoring

Clinical Neurophysiology: EEG–Video Monitoring

Fetal heart rate variability and brain stem injury after asphyxia in preterm fetal sheep.

This study was undertaken to determine the mechanisms mediating changes in fetal heart rate variability (FHRV) during and after exposure to asphyxia in the premature fetus. Preterm fetal sheep at 0.6 of gestation (91 +/- 1 days, term is 147 days) were exposed to either sham occlusion (n = 10) or to complete umbilical cord occlusion for either 20 (n = 7) or 30 min (n = 10). Cord occlusion led to a transient increase in FHRV with abrupt body movements that resolved after 5 min. In the 30 min group there was a marked increase in FHRV in the final 10 min of occlusion related to abnormal atrial activity. After reperfusion, FHRV in both study groups was initially suppressed and progressively increased to baseline levels over the first 4 h of recovery. In the 20 min group this improvement was associated with return of normal EEG activity and movements. In contrast, in the 30 min group the EEG was abnormal with epileptiform activity superimposed on a suppressed background, which was associated with abnormal fetal movements. As the epileptiform activity resolved, FHRV fell and became suppressed for the remainder of the study. Histological assessment after 72 h demonstrated severe brain stem injury in the 30 min group but not in the 20 min group. In conclusion, during early recovery from asphyxia, epileptiform activity and associated abnormal fetal movements related to evolving neural injury can cause a confounding transient increase in FHRV, which mimics the normal pattern of recovery. However, chronic suppression of FHRV was a strong predictor of severe brain stem injury.

Strain differences in hippocampal EEG are related to strain differences in behaviour in rats

To date, EEG studies towards strain differences have focussed on pharmacologically altered or pathological EEG activity, but only few studies have investigated strain differences and normal EEG activity. A strong relation between behaviour and EEG activity has been demonstrated, especially for hippocampal EEG activity. This relation is known to be similar across species and strains, but no direct comparisons between rat strains within one study have been made. This study compared two rat strains (Sprague–Dawley and Long–Evans) with regard to open-field behaviour and concurrent hippocampal EEG recordings. A detailed behavioural analysis was made and spectral power was calculated for corresponding EEG activity in eight frequency bands. The two strains differed in exploratory activity and in spectral power in the 9–10-Hz frequency band (high frequency rhythmical slow activity [RSA] 6–10 Hz). Long–Evans rats showed higher exploratory activity and higher 9–10 Hz spectral power for voluntary movement and sniffing behaviours. Our results demonstrated these behaviour-specific strain differences in RSA power, although the relation between EEG and behaviour within each strain was similar. The strain differences in EEG were interpreted in relation to strain differences in exploratory behaviour, attributing the differences to a main motor component but also to a smaller sensory component integrated in exploratory behaviour. This is in accordance with theories on the sensory–motor function of the hippocampus and hippocampal theta activity.

Time‐Course of Changes of SPECT, EEG, and Seizures in Temporal Lobe Epilepsy

Purpose: Rccent reports havc shown that diagnostic imaging by SPECT is uscfiil in the assessment of cpilcptogcnic foci in the brain. We investigated the relationship betwcen the time‐course of SPECT, EEG, and seizure changes over 3‐ to 6‐year periods. Changes wcre correlatcd with therapeutic effect assessments and predicted prognoses. In our study, SPECT and EEG data werc recorded on the same day.Subjects: Subjects comprised 27 outpaticnts with temporal lobe epiIcpsy, mean age and duration of disease of 39.2 years and 23.2 years, respectively. Seizure frequencies were weekly in 4 subjects, monthly in 7, yearly in 6, no seizure for I to 4 years in 6, and no seizure for 2 3 years in 4. Methods: The early phase SPECT images were taken 30 minutes after intravcnous administretion of 1231‐IMP. Resting EEG was sub‐scqucntly recorded. SPECT scanning was performed on horizontal and coronary sections. Regional cerebral blood flow findings were coin‐parcd by visual inspection. Results: In 9 of the 14 subjects whose seizure severity improved over time, focal spikes wcrc tiot observed i n either examination, or disappeared by second examination. I n contrast, only 5 of the 14 subjects had normal basic EEG activity by the second examination. SPECT usually did not improve. Only I ol the 14 subjects whose seizure scvcrity improved over time showed normalized SPECT findings. No subjects with scizure severity rating “unchanged” or “worsened” showed normalized SPECT findings. SPECT normalized i n only I of the 16 subjects i n whoin focal spikes wcrc not observed in either cxamination, or disappeared by second examination. Conclusions: In our present study, improvement of seizures with treatment or over tiinc wits likely to be correlated with improvement in focal spikes but not with SPECT findings. This agrees with the report of Michihiro et al. in that focal spike disappearance preceded SPECT finding normalization during treatment.

Acute soman poisoning in primates neither pretreated nor receiving immediate therapy: value of gacyclidine (GK-11) in delayed medical support.

Organophosphorus (OP) nerve agents are still used as warfare and terrorism compounds. Classical delayed treatment of victims of organophosphate poisoning includes combined i.v. administration of a cholinesterase reactivator (an oxime), a muscarinic cholinergic receptor antagonist (atropine) and a benzodiazepine anticonvulsant (diazepam). The objective of this study was to evaluate, in a realistic setting, the therapeutic benefit of administration of GK-11 (gacyclidine), an antiglutamatergic compound, as a complement to the above therapy against organophosphate poisoning. Gacyclidine was injected (i.v.) in combination with atropine/diazepam/pralidoxime at man-equivalent doses after a 45- or 30-min latency period to intoxicated primates (2 LD50). The effects of gacyclidine on the animals' survival, electroencephalographic (EEG) activity, signs of toxicity, recovery after challenge and central nervous system histology were examined. The present data demonstrated that atropine/diazepam/pralidoxime alone or combined with gacyclidine did not prevent signs of soman toxicity when treatment was delayed 45 min after poisoning. Atropine/diazepam/pralidoxime also did not control seizures or prevent neuropathology in primates exhibiting severe signs of poisoning when treatment was commenced 30 min after intoxication. However, in this latter case, EEG recordings revealed that additional treatment with gacyclidine was able to stop soman-induced seizures and restore normal EEG activity. This drug also totally prevented the neuropathology observed 5 weeks after soman exposure in animals treated with atropine/diazepam/pralidoxime alone. Overall, in the case of severe OP-poisoning, gacyclidine represents a promising adjuvant therapy to the currently available polymedication to ensure optimal management of organophosphate poisoning in man. This drug is presently being evaluated in a human clinical trial for a different neuroprotective indication. However, it should always be kept in mind that, in the case of severe OP-poisoning, medical intervention must be conducted as early as possible.

Human epileptic astrocytes exhibit increased gap junction coupling.

Fluorescence Recovery After Photobleach (FRAP) was used to quantify astrocyte gap junction coupling from tissues surgically resected from medically intractable epilepsy patients. Mesial temporal lobe cases provided hippocampus, surrounding hyperexcitable parahippocampus and normal cortex for culture. Cortical tumor cases yielded astrocytoma proper, cortex margins with normal EEG activity, and hyperexcitable cortex. Cells isolated from cortex surrounding astrocytomas and the parahippocampus surrounding the hippocampus showed an increase in glutamate-induced Ca2+ oscillations and intercellular Ca2+ waves. Gap-junction coupling was more pronounced in cells isolated from hyperexcitable tissue than from normal tissues as judged by their faster and more complete fluorescence recovery from laser bleach [FRAP]. This data suggests that intractable epilepsy may be associated with alterations in glial gap junction coupling.