Increase trend of correlation and phase synchrony of microwire iEEG before macroseizure onset

Micro/macrowire intracranial EEG (iEEG) signals recorded from implanted micro/macroelectrodes in epileptic patients have received great attention and are considered to include much information of neuron activities in seizure transition compared to scalp EEG from cortical electrodes. Microelectrode is contacted more close to neurons than macroelectrode and it is more sensitive to neuron activity changes than macroelectrode. Microwire iEEG recordings are inevitably advantageous over macrowire iEEG recordings to reveal neuronal mechanisms contributing to the generation of seizures. In this study, we investigate the seizure generation from microwire iEEG recordings and discuss synchronization of microwire iEEGs in four frequency bands: alpha (1−30 Hz), gamma (30−80 Hz), ripple (80–250 Hz), and fast ripple (>250 Hz) via two measures: correlation and phase synchrony. We find that an increase trend of correlation or phase synchrony exists before the macroseizure onset mostly in gamma and ripple bands where the duration of the preictal states varied in different seizures ranging up to a few seconds (minutes). This finding is contrast to the well-known result that a decrease of synchronization in macro domains exists before the macroseizure onset. The finding demonstrates that it is only when the seizure has recruited enough surrounding brain tissue does the signal become strong enough to be observed on the clinical macroelectrode and as a result support the hypothesis of progressive coalescence of microseizure domains. The potential ramifications of such an early detection of microscale seizure activity may open a new window on treatment by making possible disruption of seizure activity before it becomes fully established.     

Analysis of Epileptic Discharges from Implanted Subdural Electrodes in Patients with Sturge-Weber Syndrome

ObjectiveAlmost two-thirds of patients with Sturge-Weber syndrome (SWS) have epilepsy, and half of them require surgery for it. However, it is well known that scalp electroencephalography (EEG) does not demonstrate unequivocal epileptic discharges in patients with SWS. Therefore, we analyzed interictal and ictal discharges from intracranial subdural EEG recordings in patients treated surgically for SWS to elucidate epileptogenicity in this disorder.MethodsFive intractable epileptic patients with SWS who were implanted with subdural electrodes for presurgical evaluation were enrolled in this study. We examined the following seizure parameters: seizure onset zone (SOZ), propagation speed of seizure discharges, and seizure duration by visual inspection. Additionally, power spectrogram analysis on some frequency bands at SOZ was performed from 60 s before the visually detected seizure onset using the EEG Complex Demodulation Method (CDM).ResultsWe obtained 21 seizures from five patients for evaluation, and all seizures initiated from the cortex under the leptomeningeal angioma. Most of the patients presented with motionless staring and respiratory distress as seizure symptoms. The average seizure propagation speed and duration were 3.1 ± 3.6 cm/min and 19.4 ± 33.6 min, respectively. Significant power spectrogram changes at the SOZ were detected at 10–30 Hz from 15 s before seizure onset, and at 30–80 Hz from 5 s before seizure onset.SignificanceIn patients with SWS, seizures initiate from the cortex under the leptomeningeal angioma, and seizure propagation is slow and persists for a longer period. CDM indicated beta to low gamma-ranged seizure discharges starting from shortly before the visually detected seizure onset. Our ECoG findings indicate that ischemia is a principal mechanism underlying ictogenesis and epileptogenesis in SWS.     

Forecasting Seizures in Dogs with Naturally Occurring Epilepsy

Seizure forecasting has the potential to create new therapeutic strategies for epilepsy, such as providing patient warnings and delivering preemptive therapy. Progress on seizure forecasting, however, has been hindered by lack of sufficient data to rigorously evaluate the hypothesis that seizures are preceded by physiological changes, and are not simply random events. We investigated seizure forecasting in three dogs with naturally occurring focal epilepsy implanted with a device recording continuous intracranial EEG (iEEG). The iEEG spectral power in six frequency bands: delta (0.1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), low-gamma (30–70 Hz), and high-gamma (70–180 Hz), were used as features. Logistic regression classifiers were trained to discriminate labeled pre-ictal and inter-ictal data segments using combinations of the band spectral power features. Performance was assessed on separate test data sets via 10-fold cross-validation. A total of 125 spontaneous seizures were detected in continuous iEEG recordings spanning 6.5 to 15 months from 3 dogs. When considering all seizures, the seizure forecasting algorithm performed significantly better than a Poisson-model chance predictor constrained to have the same time in warning for all 3 dogs over a range of total warning times. Seizure clusters were observed in all 3 dogs, and when the effect of seizure clusters was decreased by considering the subset of seizures separated by at least 4 hours, the forecasting performance remained better than chance for a subset of algorithm parameters. These results demonstrate that seizures in canine epilepsy are not randomly occurring events, and highlight the feasibility of long-term seizure forecasting using iEEG monitoring.     

Human Intracranial High Frequency Oscillations (HFOs) Detected by Automatic Time-Frequency Analysis

Objectives

High frequency oscillations (HFOs) have been proposed as a new biomarker for epileptogenic tissue. The exact characteristics of clinically relevant HFOs and their detection are still to be defined.

Methods

We propose a new method for HFO detection, which we have applied to six patient iEEGs. In a first stage, events of interest (EoIs) in the iEEG were defined by thresholds of energy and duration. To recognize HFOs among the EoIs, in a second stage the iEEG was Stockwell-transformed into the time-frequency domain, and the instantaneous power spectrum was parameterized. The parameters were optimized for HFO detection in patient 1 and tested in patients 2–5. Channels were ranked by HFO rate and those with rate above half maximum constituted the HFO area. The seizure onset zone (SOZ) served as gold standard.

Results

The detector distinguished HFOs from artifacts and other EEG activity such as interictal epileptiform spikes. Computation took few minutes. We found HFOs with relevant power at frequencies also below the 80–500 Hz band, which is conventionally associated with HFOs. The HFO area overlapped with the SOZ with good specificity > 90% for five patients and one patient was re-operated. The performance of the detector was compared to two well-known detectors.

Conclusions

Compared to methods detecting energy changes in filtered signals, our second stage - analysis in the time-frequency domain - discards spurious detections caused by artifacts or sharp epileptic activity and improves the detection of HFOs. The fast computation and reasonable accuracy hold promise for the diagnostic value of the detector.     

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.     

Forecasting Seizures Using Intracranial EEG Measures and SVM in Naturally Occurring Canine Epilepsy

Management of drug resistant focal epilepsy would be greatly assisted by a reliable warning system capable of alerting patients prior to seizures to allow the patient to adjust activities or medication. Such a system requires successful identification of a preictal, or seizure-prone state. Identification of preictal states in continuous long- duration intracranial electroencephalographic (iEEG) recordings of dogs with naturally occurring epilepsy was investigated using a support vector machine (SVM) algorithm. The dogs studied were implanted with a 16-channel ambulatory iEEG recording device with average channel reference for a mean (st. dev.) of 380.4 (+87.5) days producing 220.2 (+104.1) days of intracranial EEG recorded at 400 Hz for analysis. The iEEG records had 51.6 (+52.8) seizures identified, of which 35.8 (+30.4) seizures were preceded by more than 4 hours of seizure-free data. Recorded iEEG data were stratified into 11 contiguous, non-overlapping frequency bands and binned into one-minute synchrony features for analysis. Performance of the SVM classifier was assessed using a 5-fold cross validation approach, where preictal training data were taken from 90 minute windows with a 5 minute pre-seizure offset. Analysis of the optimal preictal training time was performed by repeating the cross validation over a range of preictal windows and comparing results. We show that the optimization of feature selection varies for each subject, i.e. algorithms are subject specific, but achieve prediction performance significantly better than a time-matched Poisson random predictor (p<0.05) in 5/5 dogs analyzed.     

Neuronal septal activity during hippocampal seizure discharges generation in acute model of epilepsy

The activity of the neurones of the medial septal region (MS) and the hippocampal EEG in control and during the appearance of seizure discharges provoked by electrical stimulation of the perforant path were investigated in the awake rabbit. During afterdischarge generation in the hippocampus the dense neuronal bursts separated by periods of inhibition were recorded in the MS. In one group of neurons the bursts of spikes coincided with the discharges in the hippocampus, in other group-occured during inhibitory periods. When the afterdischarge stopped, in the septal neurons with theta activity the disruption of theta pattern was recorded, which have been correlated with the occurrence of low amplitude high frequency (20-25 Hz) waves in the hippocampal EEG. As a rule, the neuronal activivity of the MS recovered much quickly than EEG of the hippocampus; in some cases the increasing of the theta regularity was observed. The definite accordance of the electrical activity of the hippocampus and MS during seizure discharges suggests that the septohippocampal system operate as integral nervous circuit in these conditions. Diverse in the temporal interrelations between the discharges of MS neurones and ictal discharges in the hippocampus in the different cells possible indicate that various groups of the septal nervous elements have different participation in the seizure development. Appearance of the high frequency bursts in the MS is a possible "precursor" of the seizure onsets.     

Modulation of spontaneous seizures in the mongolian gerbil: effects of beta-endorphin

Intraventricular injection of beta-endorphin (0.1-3 micrograms) into gerbils from the UCLA seizure sensitive strain reduced the incidence and severity of spontaneous epileptiform seizures, both the motor manifestations and the preceding high voltage focal spiking and accompanying seizure activity in the cortical EEG. This "'anticonvulsant" effect of beta-endorphin was prevented by prior administration of naloxone (1 mg . kg-1 IP). These findings suggest that the endogenous opioid peptide may be involved in the normal suppression of the epileptic diathesis in these animals during the interictal periods.     

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.     

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     

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.     

Human gamma oscillations during slow wave sleep

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.     

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.     

Altered Rolandic Gamma-Band Activation Associated with Motor Impairment and Ictal Network Desynchronization in Childhood Epilepsy

Epilepsy is associated with an abnormal expression of neural oscillations and their synchronization across brain regions. Oscillatory brain activation and synchronization also play an important role in cognition, perception and motor control. Childhood epilepsy is associated with a variety of cognitive and motor deficits, but the relationship between altered functional brain responses in various frequency ranges and functional impairment in these children remains poorly understood. We investigated functional magnetoencephalographic (MEG) responses from motor cortex in multiple functionally relevant frequency bands following median nerve stimulation in twelve children with epilepsy, including four children with motor impairments. We demonstrated that children with motor impairments exhibit an excessive gamma-band response from Rolandic cortex, and that the magnitude of this Rolandic gamma response is negatively associated with motor function. Abnormal responses from motor cortex were also associated with ictal desynchronization of oscillations within Rolandic cortex measured using intracranial EEG (iEEG). These results provide the evidence that ictal disruption of motor networks is associated with an altered functional response from motor cortex, which is in turn associated with motor impairment.     

2 types of chronic epileptogenesis in rabbits during kindling stimulation of the hippocampus

The development of convulsant readiness in rabbits during kindling electrical stimulation of the hippocamp was studied as was the dependence of the motor seizure pattern on the degree of epileptiform activity generalization in the CNS. The kindling electrical stimulation of the hippocamp gave rise to the formation in different rabbits of the two main types of afterdischarges. One of them was characterized by high-frequency and high-amplitude spikes (total duration 8-30 s) and the other one by continuous, rather long (50-100 s) hypersynchronous paroxysms. In the interictal period, the animals with the first type demonstrated the occurrence of spontaneous spikes (in all the brain structures under study) that sometimes progressed to a more or less prolonged seizure discharges. At the same time in the animals with the second type of afterdischarges the EEG in the interictal period was slightly different from normal. Despite this fact the seizures induced by electrical stimulation ran a milder course (short-term clonic seizures) in animals with the first type of afterdischarges as compared to those with the second type (long-term clonicotonic seizures). It is assumed that the severity of the motor seizure does not depend on the degree of epileptic activity generalization in the CNS.     

Early Postnatal EEG Features of Perinatal Arterial Ischaemic Stroke with Seizures

Background

Stroke is the second most common cause of seizures in term neonates and is associated with abnormal long-term neurodevelopmental outcome in some cases.

Objective

To aid diagnosis earlier in the postnatal period, our aim was to describe the characteristic EEG patterns in term neonates with perinatal arterial ischaemic stroke (PAIS) seizures.

Design

Retrospective observational study.

Patients

Neonates >37 weeks born between 2003 and 2011 in two hospitals.

Method

Continuous multichannel video-EEG was used to analyze the background patterns and characteristics of seizures. Each EEG was assessed for continuity, symmetry, characteristic features and sleep cycling; morphology of electrographic seizures was also examined. Each seizure was categorized as electrographic-only or electroclinical; the percentage of seizure events for each seizure type was also summarized.

Results

Nine neonates with PAIS seizures and EEG monitoring were identified. While EEG continuity was present in all cases, the background pattern showed suppression over the infarcted side; this was quite marked (>50% amplitude reduction) when the lesion was large. Characteristic unilateral bursts of theta activity with sharp or spike waves intermixed were seen in all cases. Sleep cycling was generally present but was more disturbed over the infarcted side. Seizures demonstrated a characteristic pattern; focal sharp waves/spike-polyspikes were seen at frequency of 1–2 Hz and phase reversal over the central region was common. Electrographic-only seizure events were more frequent compared to electroclinical seizure events (78 vs 22%).

Conclusions

Focal electrographic and electroclinical seizures with ipsilateral suppression of the background activity and focal sharp waves are strong indicators of PAIS. Approximately 80% of seizure events were the result of clinically unsuspected seizures in neonates with PAIS. Prolonged and continuous multichannel video-EEG monitoring is advocated for adequate seizure surveillance.     

Converging Intracranial Markers of Conscious Access

We compared conscious and nonconscious processing of briefly flashed words using a visual masking procedure while recording intracranial electroencephalogram (iEEG) in ten patients. Nonconscious processing of masked words was observed in multiple cortical areas, mostly within an early time window (<300 ms), accompanied by induced gamma-band activity, but without coherent long-distance neural activity, suggesting a quickly dissipating feedforward wave. In contrast, conscious processing of unmasked words was characterized by the convergence of four distinct neurophysiological markers: sustained voltage changes, particularly in prefrontal cortex, large increases in spectral power in the gamma band, increases in long-distance phase synchrony in the beta range, and increases in long-range Granger causality. We argue that all of those measures provide distinct windows into the same distributed state of conscious processing. These results have a direct impact on current theoretical discussions concerning the neural correlates of conscious access.     

Functional Connectivity Estimated from Intracranial EEG Predicts Surgical Outcome in Intractable Temporal Lobe Epilepsy

This project aimed to determine if a correlation-based measure of functional connectivity can identify epileptogenic zones from intracranial EEG signals, as well as to investigate the prognostic significance of such a measure on seizure outcome following temporal lobe lobectomy. To this end, we retrospectively analyzed 23 adult patients with intractable temporal lobe epilepsy (TLE) who underwent an invasive stereo-EEG (SEEG) evaluation between January 2009 year and January 2012. A follow-up of at least one year was required. The primary outcome measure was complete seizure-freedom at last follow-up. Functional connectivity between two areas in the temporal lobe that were sampled by two SEEG electrode contacts was defined as Pearson’s correlation coefficient of interictal activity between those areas. SEEG signals were filtered between 5 and 50 Hz prior to computing this correlation. The mean and standard deviation of the off diagonal elements in the connectivity matrix were also calculated. Analysis of the mean and standard deviation of the functional connections for each patient reveals that 90% of the patients who had weak and homogenous connections were seizure free one year after temporal lobectomy, whereas 85% of the patients who had stronger and more heterogeneous connections within the temporal lobe had recurrence of seizures. This suggests that temporal lobectomy is ineffective in preventing seizure recurrence for patients in whom the temporal lobe is characterized by weakly connected, homogenous networks. This pilot study shows promising potential of a simple measure of functional brain connectivity to identify epileptogenicity and predict the outcome of epilepsy surgery.     

The hippocampus as the determinant structure generating epileptic activity during korazol kindling

It has been shown in chronic experiments on rats that two periods of EEG and behavioral alterations may be distinguished during korazol kindling. The bursts of slow waves and spike-wave activity appear on the EEG during the first period as response to subthreshold doses of korazol, which is accompanied behaviorally by standing and myoclonuses. The second period is characterized by the appearance of high-frequency polymorphous generalized seizure discharges on the EEG accompanied by clonicotonic seizures. Interictal and ictal epileptic discharges appear primarily in the hippocamp and then in other brain structures during the development of korazol kindling. The conclusion is made that the hippocamp plays the role of a pathological determinant structure in the development of chronic brain epileptization during korazol kindling.     

Transcranial electrical currents to probe EEG brain rhythms and memory consolidation during sleep in humans

Previously the application of a weak electric anodal current oscillating with a frequency of the sleep slow oscillation (～0.75 Hz) during non-rapid eye movement sleep (NonREM) sleep boosted endogenous slow oscillation activity and enhanced sleep-associated memory consolidation. The slow oscillations occurring during NonREM sleep and theta oscillations present during REM sleep have been considered of critical relevance for memory formation. Here transcranial direct current stimulation (tDCS) oscillating at 5 Hz, i.e., within the theta frequency range (theta-tDCS) is applied during NonREM and REM sleep. Theta-tDCS during NonREM sleep produced a global decrease in slow oscillatory activity conjoint with a local reduction of frontal slow EEG spindle power (8-12 Hz) and a decrement in consolidation of declarative memory, underlining the relevance of these cortical oscillations for sleep-dependent memory consolidation. In contrast, during REM sleep theta-tDCS appears to increase global gamma (25-45 Hz) activity, indicating a clear brain state-dependency of theta-tDCS. More generally, results demonstrate the suitability of oscillating-tDCS as a tool to analyze functions of endogenous EEG rhythms and underlying endogenous electric fields as well as the interactions between EEG rhythms of different frequencies.