Pattern- and age-dependency of the antiepileptic effects induced by valproic acid in the rat hippocampus.

The effects induced by the antiepileptic drug valproic acid were studied in the CA3 subfield of in vitro hippocampal slices obtained from young (16- to 27-day-old) and adult (over 60-day-old) rats. Spontaneous epileptiform discharges were induced by the addition of the convulsant 4-aminopyridine to the medium. Valproic acid (0.5 mM) selectively blocked the ictal epileptiform discharges in slices obtained from young rats. Interictal epileptiform discharges disappeared during perfusion with higher doses of valproic acid (2 mM). This blockade of interictal epileptiform activity was not observed when valproic acid (0.5-5 mM) was tested in hippocampal slices from adult rats. Thus, in the hippocampus of young rats, 4-aminopyridine-induced ictal activity is more sensitive to valproic acid than are interictal discharges. Moreover, valproic acid is effective in controlling interictal discharges in the young, but not in the adult rat hippocampus.     

In vivo optical mapping of epileptic foci and surround inhibition in ferret cerebral cortex

The population of neurons participating in an epileptiform event varies from moment to moment. Most techniques currently used to localize epileptiform events in vivo have spatial and/or temporal sampling limitations. Here we show in an animal model that optical imaging based on intrinsic signals is an excellent method for in vivo mapping of clinically relevant epileptiform events, such as interictal spikes, ictal onsets, ictal spread and secondary homotopic foci. In addition, a decrease in the optical signal correlates spatially with a decrease in neuronal activity recorded from cortex surrounding an epileptic focus. Optical mapping of epilepsy might be a useful adjunct in the surgical treatment of neocortical epilepsy, which critically depends on the precise localization of intrinsically epileptogenic neurons.     

ICA Extracts Epileptic Sources from fMRI in EEG-Negative Patients: A Retrospective Validation Study

Simultaneous EEG-fMRI has proven to be useful in localizing interictal epileptic activity. However, the applicability of traditional GLM-based analysis is limited as interictal spikes are often not seen on the EEG inside the scanner. Therefore, we aim at extracting epileptic activity purely from the fMRI time series using independent component analysis (ICA). To our knowledge, we show for the first time that ICA can find sources related to epileptic activity in patients where no interictal spikes were recorded in the EEG. The epileptic components were identified retrospectively based on the known localization of the ictal onset zone (IOZ). We demonstrate that the selected components truly correspond to epileptic activity, as sources extracted from patients resemble significantly better the IOZ than sources found in healthy controls. Furthermore, we show that the epileptic components in patients with and without spikes recorded inside the scanner resemble the IOZ in the same degree. We conclude that ICA of fMRI has the potential to extend the applicability of EEG-fMRI for presurgical evaluation in epilepsy.     

Cardiac neural discharge and epileptogenic activity in the cat: An animal model for unexplained death

This study developed an animal model to explore the hypothesis that altered automatic function may be one cause for unexplained sudden epileptic deaths. After α-chloralose anesthesia, 9 cats received a tracheostomy and a thoracotomy. Intravenous gallamine was used to paralyze the cats. Blood pressure, arterial blood gases, electrocardiogram, and rectal temperature were monitored. Simultaneous monitoring of the neural discharge in postganglionic cardiac sympathetic branches and the vagus nerve was combined with a bilateral craniectomy and electrocorticography. Pentylenetetrazol was given intravenously at 10 min intervals in 10, 20, 50, 100, 200, and 2000 mg/kg doses. Epileptiform discharges were categorized as a prolonged ictal (duration of 10 sec or more), brief ictal (duration of less than 10 sec mixed with suppression), and interictal spike activity. The two types of ictal activity were quantified by duration in seconds for the 10 min interval after each dose of pentylenetetrazol; the number of interictal spikes/min was determined for each minute of the entire experiment. This study developed a model which quantified the degree of epileptiform activity and correlated it with changes in cardiovascular function and autonomic cardiac neural discharge. An imbalance within and between sympathetic and parasympathetic cardiac neural discharges was found, as was a significant disruption of the physiological relationships between heart rate and blood pressure. Frequent and varied electrocardiogram abnormalities occurred. All of the above changes occurred during minimal (interictal) subconvulsant as well as during maximal (ictal) convulsant epileptogenic activity.     

Effects of ketamine on neuronal epileptiform responses in the cat neocortex

The effects of ketamine, an antagonist of NMDA receptors, on the neuronal epileptiform responses evoked by applications of strychnine, penicillin, or bicuculline to the suprasylvian gyrus were studied in cats. Ketamine either exerted no effect, or slightly decreased interictal high-amplitude depolarizing shifts of the membrane potential and depolarizing afterpotentials, which appeared spontaneously or were evoked by intracortical stimulation. Repetitive electrical stimulation of the epileptogenic cortical regions resulted in the appearance of autogenerated ictal activity lasting up to several tens of seconds; this activity was produced against the background of a depolarization of neuronal membranes. After ketamine injections, such stimulations evoked no ictal activity in the neurons, or the discharges became much shorter. The results of our study show that the NMDA-dependent postsynaptic components play a more important role in the development of neocortical ictal activity compared with the interictal activity.Neirofiziologiya/Neurophysiology, Vol. 27, No. 1, pp. 32–35, January–February, 1995.     

Effects of interleukin-10 on the epileptiform activity development in the hippocampus induced by brief hypoxia, bicuculline and electrical kindling

The comparative effects of antiinflammatory cytokine interleukin-10 on the epileptiform activity development in CA1 hippocampal neurons were studied in different functional models of epileptogenesis that are not accompanied the visible morphological disturbances in the brain cells: --in vitro hypoxic model in the rat hippocampal slices; 2--in vitro disinhibitory model with using GABAA antagonist, bicuculline, in the rat hippocampal slices; 3--partial hippocampal kindling model in freely moving rats. Interleukin-10 (1 ng/ml) depressed the posthypoxic hyperexcitability in CA1 pyramidal neurons of the rat hippocampal slices through a decrease of the effectiveness of hypoxia to depresses the functional neuronal activity in the rat hippocampal slices during hypoxic episode. On the other hand, interleukin-10 (1 ng/ml) did not affect an initiation of epileptiform activity in CA1 pyramidal neurons of the rat hippocampal slices induced by bicuculline. Interleukin-10 (1 ng/5 microl) applied to the dorsal hippocampus in awake rats depressed an initiation of focal seizures ("ictal"-like components of afterdischarges) induced by hippocampal kindling during the first six hours after an application. However, this cytokine did not affect neither the duration of "interictal"-like component of afterdischarges nor motor seizure development. Thus, our findings showed that antiinflammatory cytokine interleukin-10, in addition to its antihypoxic action, exert the neuroprotective effect on the initiation of "ictal"-like, but not "interictal"-like, epileptiform discharges.     

Interictal functional connectivity of human epileptic networks assessed by intracerebral EEG and BOLD signal fluctuations

In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal derived from resting state functional magnetic resonance imaging (fMRI) reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG) and resting-state functional MRI (fMRI) in 5 patients suffering from intractable temporal lobe epilepsy (TLE). Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions) during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband) and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal). This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional connectivity measured by iEEG and BOLD signals give complementary but sometimes inconsistent information in TLE.     

Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals

In the field of epilepsy, the analysis of stereoelectroencephalographic (SEEG, intra-cerebral recording) signals with signal processing methods can help to better identify the epileptogenic zone, the area of the brain responsible for triggering seizures, and to better understand its organization. In order to evaluate these methods and to physiologically interpret the results they provide, we developed a model able to produce EEG signals from “organized” networks of neural populations. Starting from a neurophysiologically relevant model initially proposed by Lopes Da Silva et al. [Lopes da Silva FH, Hoek A, Smith H, Zetterberg LH (1974) Kybernetic 15: 27–37] and recently re-designed by Jansen et al. [Jansen BH, Zouridakis G, Brandt ME (1993) Biol Cybern 68: 275–283] the present study demonstrates that this model can be extended to generate spontaneous EEG signals from multiple coupled neural populations. Model parameters related to excitation, inhibition and coupling are then altered to produce epileptiform EEG signals. Results show that the qualitative behavior of the model is realistic; simulated signals resemble those recorded from different brain structures for both interictal and ictal activities. Possible exploitation of simulations in signal processing is illustrated through one example; statistical couplings between both simulated signals and real SEEG signals are estimated using nonlinear regression. Results are compared and show that, through the model, real SEEG signals can be interpreted with the aid of signal processing methods. Received: 3 January 2000 / Accepted: 24 March 2000     

Topographic analysis of dimension estimates of EEG and filtered rhythms in epileptic patients with complex partial seizures

Nonlinear dynamic properties were analyzed on the EEG and filtered rhythms recorded from healthy subjects and epileptic patients with complex partial seizures. Estimates of correlation dimensions of control EEG, interictal EEG and ictal EEG were calculated. The values were demonstrated on topograms. The delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz) and gamma (30–40 Hz) components were obtained and considered as signals from the cortex. Corresponding surrogate data was produced. Firstly, the influence of sampling parameters on the calculation was tested. The dimension estimates of the signals from the frontal, temporal, parietal and occipital regions were computed and compared with the results of surrogate data. In the control subjects, the estimates between the EEG and surrogate data did not differ (P > 0.05). The interictal EEG from the frontal region and occipital region, as well as its theta component from the frontal region, and temporal region, showed obviously low dimensions (P < 0.01). The ictal EEG exhibited significantly low-dimension estimates across the scalp. All filtered rhythms from the temporal region yielded lower results than those of the surrogate data (P < 0.01). The dimension estimates of the EEG and filtered components markedly changed when the neurological state varied. For each neurological state, the dimension estimates were not uniform among the EEG and frequency components. The signal with a different frequency range and in a different neurological state showed a different dimension estimate. Furthermore, the theta and alpha components demonstrated the same estimates not only within each neurological state, but also among the different states. These results indicate that the theta and alpha components may be caused by similar dynamic processes. We conclude that the brain function underlying the ictal EEG has a simple mechanism. Several heterogeneous dynamic systems play important roles in the generation of EEG. Received: 10 December 1999 / Accepted in revised form: 8 May 2000     

Fractal dimension of electroencephalographic time series and underlying brain processes

 Fractal dimension has been proposed as a useful measure for the characterization of electrophysiological time series. This paper investigates what the pointwise dimension of electroencephalographic (EEG) time series can reveal about underlying neuronal generators. The following theoretical assumptions concerning brain function were made (i) within the cortex, strongly coupled neural assemblies exist which oscillate at certain frequencies when they are active, (ii) several such assemblies can oscillate at a time, and (iii) activity flow between assemblies is minimal. If these assumptions are made, cortical activity can be considered as the weighted sum of a finite number of oscillations (plus noise). It is shown that the correlation dimension of finite time series generated by multiple oscillators increases monotonically with the number of oscillators. Furthermore, it is shown that a reliable estimate of the pointwise dimension of the raw EEG signal can be calculated from a time series as short as a few seconds. These results indicate that (i) The pointwise dimension of the EEG allows conclusions regarding the number of independently oscillating networks in the cortex, and (ii) a reliable estimate of the pointwise dimension of the EEG is possible on the basis of short raw signals. Received: 1 September 1994/Accepted in revised form: 16 May 1995     

Elevated S100B and Neuron Specific Enolase Levels in Patients with Migraine-without Aura: Evidence for Neurodegeneration?

Although migraine has mainly been considered as a benign disease, there is cumulative evidence of silent changes in the brain, brainstem, or cerebellum and subtle subclinical cerebellar dysfunction. In this study, in order to investigate a possible neuronal and/or glial damage at the cellular level in migraine, we measured and compared serum levels of S100B which is a protein marker of glial damage or activation, and neuron specific enolase (NSE) which is a marker of neuronal damage, in migraine patients and control subjects. Serum levels of S100B and NSE were measured in blood samples from 41 patients with migraine-without aura taken during a migraine attack (ictal) and in the attack-free period between migraine attacks (interictal) and 35 age- and sex-matched controls. Patients with migraine-without aura had significantly higher ictal serum levels of S100B and NSE (P < 0.05, for both) than control subjects; whereas in the interictal phase, there was a significant increment only in S100B levels (P < 0.05) compared to controls. On the other hand, serum levels of S100B and NSE in ictal and interictal blood samples did not differ significantly. The findings of increased ictal serum S100B and NSE levels together with increased interictal levels of S100B suggested that migraine might be associated with glial and/or neuronal damage in the brain and a prolonged disruption of blood–brain barrier. Increased interictal serum levels of S100B might point out to an insidious and slow damaging process in migraine patients.     

An autoregressive method for the measurement of synchronization of interictal and ictal EEG signals

We propose a new measure of synchronization of multichannel ictal and interictal EEG signals. The measure is based on the residual covariance matrix of a multichannel autoregressive model. A major advantage of this measure is its ability to be interpreted both in the framework of stochastic and deterministic models. A preliminary analysis of EEG data from three patients using this measure documents the expected increased synchronization during ictal periods but also reveals that increased synchrony persists for prolonged periods (up to 2 h or more) in the postictal period. Received: 20 July 1997 / Accepted in revised form: 26 January 1999     

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.     

Computational models of epileptiform activity in single neurons

A series of original computational models written in NEURON of increasing physiological and morphological complexity were developed to determine the dominant causes of epileptiform behavior. Current injections to a model hippocampal pyramidal neuron consisting of three compartments produced the sustained depolarizations (SD) and simple paroxysmal depolarizing shifts (PDS) characteristic of ictal and interictal behavior in a cell, respectively. Our results indicate that SDs are the result of the semi-saturation of Na+, Ca2+ and K+ active channels, particularly the CaN, with regular Na+/K+ spikes riding atop a saturated depolarization; PDS rides on a similar semi-saturated depolarization whose shape depends more heavily on interactions between low-threshold voltage-gated Ca2+ channels (CaT) and Ca(2+)-dependent K+ channels. Our results reflect and predict recent physiological data, and we report here a cellular basis of epilepsy whose mechanisms reside mainly in the membrane channels, and not in specific morphology or network interactions, advancing a possible resolution to the cellular/network debate over the etiology of epileptiform activity.     

Neuromagnetic Abnormality of Motor Cortical Activation and Phases of Headache Attacks in Childhood Migraine

The cerebral cortex serves a primary role in the pathogenesis of migraine. This aberrant brain activation in migraine can be noninvasively detected with magnetoencephalography (MEG). The objective of this study was to investigate the differences in motor cortical activation between attacks (ictal) and pain free intervals (interictal) in children and adolescents with migraine using both low- and high-frequency neuromagnetic signals. Thirty subjects with an acute migraine and 30 subjects with a history of migraine, while pain free, were compared to age- and gender-matched controls using MEG. Motor cortical activation was elicited by a standardized, validated finger-tapping task. Low-frequency brain activation (1∼50 Hz) was analyzed with waveform measurements and high-frequency oscillations (65–150 Hz) were analyzed with wavelet-based beamforming. MEG waveforms showed that the ictal latency of low-frequency brain activation was significantly delayed as compared with controls, while the interictal latency of brain activation was similar to that of controls. The ictal amplitude of low-frequency brain activation was significantly increased as compared with controls, while the interictal amplitude of brain activation was similar to that of controls. The ictal source power of high-frequency oscillations was significantly stronger than that of the controls, while the interictal source power of high-frequency oscillations was significantly weaker than that of controls. The results suggest that aberrant low-frequency brain activation in migraine during a headache attack returned to normal interictally. However, high-frequency oscillations changed from ictal hyper-activation to interictal hypo-activation. Noninvasive assessment of cortical abnormality in migraine with MEG opens a new window for developing novel therapeutic strategies for childhood migraine by maintaining a balanced cortical excitability.     

Localizational concepts in epilepsy: past, present and future

The clinical seizure pattern, particularly the initial phenomena, plus the EEG, when satisfactory recording of the seizure onset can be achieved, determine the primary localization of epileptic phenomena. The EEG has also demonstrated, by the presence of interictal epileptiform spike discharges, the presence of a second-order localization of epileptic phenomena, namely, the location and extent of cortex adjacent to the site of origin of the neuronal seizure discharge that is recruited into action in a clinical epileptic seizure. Experience with cortical resection in the treatment of focal epilepsy has demonstrated the importance of a third-order localization of epileptic phenomena, namely, how much of the potentially epileptogenic cortex must be excised in order to produce a satisfactory reduction of the seizure tendency.     

Changes in paroxysmal brainwave patterns of epileptics by weak-field magnetic stimulation

In order to assess the effects of weak-field magnetic stimulation on brain electrical activity in epileptics, three patients suffering from mesial temporal lobe epilepsy (MTLE) were exposed to DC magnetic fields of 0.9 and 1.8 millitesla (mT). The EEG activity was recorded simultaneously from intracranial electrodes inserted through the foramen ovale (FO) and scalp electrodes. Significant enhancement of interictal epileptiform activity was observed in two patients, while in one patient, magnetic stimulation resulted in the cessation of interictal spike/wave trains.     

Detecting effective connectivity in networks of coupled neuronal oscillators

The application of data-driven time series analysis techniques such as Granger causality, partial directed coherence and phase dynamics modeling to estimate effective connectivity in brain networks has recently gained significant prominence in the neuroscience community. While these techniques have been useful in determining causal interactions among different regions of brain networks, a thorough analysis of the comparative accuracy and robustness of these methods in identifying patterns of effective connectivity among brain networks is still lacking. In this paper, we systematically address this issue within the context of simple networks of coupled spiking neurons. Specifically, we develop a method to assess the ability of various effective connectivity measures to accurately determine the true effective connectivity of a given neuronal network. Our method is based on decision tree classifiers which are trained using several time series features that can be observed solely from experimentally recorded data. We show that the classifiers constructed in this work provide a general framework for determining whether a particular effective connectivity measure is likely to produce incorrect results when applied to a dataset.     

Aging-related changes of EEG synchronization during a visual working memory task

Differences of EEG synchronization between normal old and young people during a working memory (WM) task were investigated. The synchronization likelihood (SL) is a novel method to assessed synchronization in multivariate time series for non-stationary systems. To evaluate this method to study the mechanisms of WM, we calculated the SL values in brain electrical activity for both resting state and task state. EEG signals were recorded from 14 young adults and 12 old adults during two different states, respectively. SL was used to measure EEG synchronization between 19 electrodes in delta, theta, alpha1, alpha2 and beta frequency bands. Bad task performance and significantly decreased EEG synchronization were found in old group compared to young group in alpha1, alpha2 and beta frequency bands during the WM task. Moreover, significantly decreased EEG synchronization in beta band in the elder was also detected during the resting state. The findings suggested that reduced EEG synchronization may be one of causes for WM capacity decline along with healthy aging.     

Foramen ovale electrodes: a new technique enabling presurgical evaluation of patients with mesiobasal temporal lobe seizures

A recently developed technique to record from the mesiobasal aspect of the temporal lobes by subdural electrodes inserted through the foramen ovale is described. Experience with this technique in 13 candidates for surgical epilepsy therapy is presented. Our results indicate that interictal epileptiform potentials as well as ictal discharges are reliably picked up by the foramen ovale electrode whenever nucleus amygdallae, hippocampus and parahippocampal gyrus show synchronous epileptic activity. The advantages of this technique are discussed.