High-frequency activity in experimental and clinical epileptic foci

HFA analysis using scalp electroencephalograms in two cases of Rasmussen's syndrome

OBJECTIVE

In recent years, wide-band EEGs have been used to assess brain activity, and their effectiveness in the pathological analysis of epilepsy has been demonstrated. This report describes two cases of Rasmussen's syndrome (RS) in which high-frequency scalp EEGs were retrospectively analyzed to assess the pathological condition of epilepsy in RS.

METHODS

The two RS cases were divided into three periods: incipient, stable, and frequent seizure periods. Using the EEG record of each period, interictal epileptiform discharges (IEDs) were visually extracted. Subsequently, a time-frequency analysis was performed to calculate the rate of high-frequency activities (HFAs) (IED-HFA rate). Finally, differences between the three periods were examined.

RESULTS

IED-HFA rates significantly increased in the frequent seizure period compared with the stable period in both cases(P < 0.05).

CONCLUSION

there was a significant increase in HFAs superimposed over IEDs during the frequent seizure period compared to the stable period. HFAs are thought to be associated with epileptogenicity. Similarly, HFAs could be a useful biomarker for the pathological condition of epilepsy in RS.

Epileptogenic high-frequency oscillations present larger amplitude both in mesial temporal and neocortical regions

High-frequency oscillations (HFO) are a promising biomarker for the identification of epileptogenic tissue. While HFO rates have been shown to predict seizure outcome, it is not yet clear whether their morphological features might improve this prediction. We validated HFO rates against seizure outcome and delineated the distribution of HFO morphological features. We collected stereo-EEG recordings from 20 patients (231 electrodes; 1,943 contacts). We computed HFO rates (the co-occurrence of ripples and fast ripples) through a validated automated detector during non-rapid eye movement sleep. Applying machine learning, we delineated HFO morphological features within and outside epileptogenic tissue across mesial temporal lobe (MTL) and Neocortex. HFO rates predicted seizure outcome with 85% accuracy, 79% specificity, 100% sensitivity, 100% negative predictive value, and 67% positive predictive value. The analysis of HFO features showed larger amplitude in the epileptogenic tissue, similar morphology for epileptogenic HFO in MTL and Neocortex, and larger amplitude for physiological HFO in MTL. We confirmed HFO rates as a reliable biomarker for epilepsy surgery and characterized the potential clinical relevance of HFO morphological features. Our results support the prospective use of HFO in epilepsy surgery and contribute to the anatomical mapping of HFO morphology.

The Relationship Between the Rhythmic Components of the Brain Electrical Activity During the Development of Status Epilepticus: An Operational Model of Brain Rhythms Generation

Background/Introduction: Despite the fact that brain rhythms are widely studied and officially classified, there is no consensus on their relationship, which can shed light on the genesis of rhythmic activity, its synchronization, functional role, and the formation of pathological reactions. Using the experimental status epilepticus (SE) as a model of brain in a hypersynchronized state with well-defined rhythms, we aimed to study the relationship between the rhythmic components of the brain electrical activity. Materials and Methods: Local field potentials (LFPs) were recorded simultaneously from the hippocampus, entorhinal cortex, medial septum, and amygdala during normal conditions and after kainic acid (KA) administration in waking guinea pigs. The dynamical spectral LFP properties were analyzed with the aid of Fast Fourier transform. Results: KA induces prominent SE with periodic combination of epileptiform discharge complexes and relatively quiet interdischarge intervals in the electrical activity of the brain. We have shown that new components appeared in the LFP spectra during the development of SE, representing a sequential doubling of the frequency, which had initially been dominating in the background records. Discussion: The phenomenon of frequency doubling can be interpreted as the octave principle of the LFP spectrum rhythmic carcass structure. The spectra of discharge complexes represent an alternation of harmonic spectra, where fundamental frequency coincides with one of the doubled frequencies dominating in the interdischarge activity. Using a nonlinear recurrent operation of rhythm multiplication and the obtained data we propose an operational model of the generation of rhythms and pathological discharges in the brain based on the octave principle. Impact statement In this study, we examined the relationship between the rhythmic components of the electrical activity of the limbic structures during the experimental status epilepticus and propose an operational model of brain rhythms generation based on the octave principle. Our study demonstrates that using fundamental principles (nonlinearity and the presence of recurrence), it is possible to explain the genesis and phenomenology of the electrical activity of brain structures in normal and pathological conditions.

The role of interictal discharges in ictogenesis - A dynamical perspective

Interictal epileptiform discharge (IED) is a traditional hallmark of epileptic tissue that is generated by the synchronous activity of a population of neurons. Interictal epileptiform discharges represent a heterogeneous group of pathological activities that differ in shape, duration, spatiotemporal distribution, underlying cellular and network mechanisms, and their relationship to seizure genesis. The exact role of IEDs in epilepsy is still not well understood, and there remains a persistent dichotomy about the impact on IEDs on seizures. Proseizure, antiseizure, and no impact on ictogenesis have all been described in previous studies. In this article, we review the existing knowledge on the role of interictal discharges in seizure genesis, and we discuss how dynamical approaches to ictogenesis can explain the existing dichotomy about the multifaceted role of IEDs in ictogenesis. This article is part of the Special Issue "NEWroscience 2018".

High frequency oscillations in epileptic and non-epileptic human hippocampus during a cognitive task

Hippocampal high-frequency electrographic activity (HFOs) represents one of the major discoveries not only in epilepsy research but also in cognitive science over the past few decades. A fundamental challenge, however, has been the fact that physiological HFOs associated with normal brain function overlap in frequency with pathological HFOs. We investigated the impact of a cognitive task on HFOs with the aim of improving differentiation between epileptic and non-epileptic hippocampi in humans. Hippocampal activity was recorded with depth electrodes in 15 patients with focal epilepsy during a resting period and subsequently during a cognitive task. HFOs in ripple and fast ripple frequency ranges were evaluated in both conditions, and their rate, spectral entropy, relative amplitude and duration were compared in epileptic and non-epileptic hippocampi. The similarity of HFOs properties recorded at rest in epileptic and non-epileptic hippocampi suggests that they cannot be used alone to distinguish between hippocampi. However, both ripples and fast ripples were observed with higher rates, higher relative amplitudes and longer durations at rest as well as during a cognitive task in epileptic compared with non-epileptic hippocampi. Moreover, during a cognitive task, significant reductions of HFOs rates were found in epileptic hippocampi. These reductions were not observed in non-epileptic hippocampi. Our results indicate that although both hippocampi generate HFOs with similar features that probably reflect non-pathological phenomena, it is possible to differentiate between epileptic and non-epileptic hippocampi using a simple odd-ball task.

Docosanoids and elovanoids from omega-3 fatty acids are pro-homeostatic modulators of inflammatory responses, cell damage and neuroprotection

The functional significance of the selective enrichment of the omega-3 essential fatty acid docosahexaenoic acid (DHA; 22C and 6 double bonds) in cellular membrane phospholipids of the nervous system is being clarified by defining its specific roles on membrane protein function and by the uncovering of the bioactive mediators, docosanoids and elovanoids (ELVs). Here, we describe the preferential uptake and DHA metabolism in photoreceptors and brain as well as the significance of the Adiponectin receptor 1 in DHA retention and photoreceptor cell (PRC) survival. We now know that this integral membrane protein is engaged in DHA retention as a necessary event for the function of PRCs and retinal pigment epithelial (RPE) cells. We present an overview of how a) NPD1 selectively mediates preconditioning rescue of RPE and PR cells; b) NPD1 restores aberrant neuronal networks in experimental epileptogenesis; c) the decreased ability to biosynthesize NPD1 in memory hippocampal areas of early stages of Alzheimer's disease takes place; d) NPD1 protection of dopaminergic circuits in an in vitro model using neurotoxins; and e) bioactivity elicited by DHA and NPD1 activate a neuroprotective gene-expression program that includes the expression of Bcl-2 family members affected by Aβ42, DHA, or NPD1. In addition, we highlight ELOVL4 (ELOngation of Very Long chain fatty acids-4), specifically the neurological and ophthalmological consequences of its mutations, and their role in providing precursors for the biosynthesis of ELVs. Then we outline evidence of ELVs ability to protect RPE cells, which sustain PRC integrity. In the last section, we present a summary of the protective bioactivity of docosanoids and ELVs in experimental ischemic stroke. The identification of early mechanisms of neural cell survival mediated by DHA-synthesized ELVs and docosanoids contributes to the understanding of cell function, pro-homeostatic cellular modulation, inflammatory responses, and innate immunity, opening avenues for prevention and therapeutic applications in neurotrauma, stroke and neurodegenerative diseases.

Hippocampal sharp wave-ripple: A cognitive biomarker for episodic memory and planning

Sharp wave ripples (SPW-Rs) represent the most synchronous population pattern in the mammalian brain. Their excitatory output affects a wide area of the cortex and several subcortical nuclei. SPW-Rs occur during "off-line" states of the brain, associated with consummatory behaviors and non-REM sleep, and are influenced by numerous neurotransmitters and neuromodulators. They arise from the excitatory recurrent system of the CA3 region and the SPW-induced excitation brings about a fast network oscillation (ripple) in CA1. The spike content of SPW-Rs is temporally and spatially coordinated by a consortium of interneurons to replay fragments of waking neuronal sequences in a compressed format. SPW-Rs assist in transferring this compressed hippocampal representation to distributed circuits to support memory consolidation; selective disruption of SPW-Rs interferes with memory. Recently acquired and pre-existing information are combined during SPW-R replay to influence decisions, plan actions and, potentially, allow for creative thoughts. In addition to the widely studied contribution to memory, SPW-Rs may also affect endocrine function via activation of hypothalamic circuits. Alteration of the physiological mechanisms supporting SPW-Rs leads to their pathological conversion, "p-ripples," which are a marker of epileptogenic tissue and can be observed in rodent models of schizophrenia and Alzheimer's Disease. Mechanisms for SPW-R genesis and function are discussed in this review.

Safe direct current stimulator 2: concept and design

Essentially all neuroprostheses use alternating biphasic current pulses to stimulate neural tissue. While this method can effectively excite neurons, it is not very effective for inhibiting them. In contrast, direct current (DC) can excite, inhibit, and modulate sensitivity of neurons. However, DC stimulation is biologically unsafe because it violates safe charge injection criteria. We have previously described the concept of a safe direct current stimulator (SDCS) that overcomes this constraint. The SDCS drives DC ionic current into the tissue by switching fluid valves in phase with biphasic current pulses delivered to the metal electrodes within the device. The original prototype of this device, SDCS1, could both suppress and excite the vestibular nerve with DC stimulation delivered by the device. In the process of building the SDCS1 we identified several problems that must be addressed to further develop this technology. Consequently, we designed the SDCS2, which eliminates periodic interruptions in stimulation current flow observed in the original SDCS1 design and is small enough for head-mounted use in chronic animal studies.

A study of the dynamics of seizure propagation across micro domains in the vicinity of the seizure onset zone

OBJECTIVE

The use of micro-electrode arrays to measure electrical activity from the surface of the brain is increasingly being investigated as a means to improve seizure onset zone (SOZ) localization. In this work, we used a multivariate autoregressive model to determine the evolution of seizure dynamics in the [Formula: see text] Hz high frequency band across micro-domains sampled by such micro-electrode arrays. We showed that a directed transfer function (DTF) can be used to estimate the flow of seizure activity in a set of simulated micro-electrode data with known propagation pattern.

APPROACH

We used seven complex partial seizures recorded from four patients undergoing intracranial monitoring for surgical evaluation to reconstruct the seizure propagation pattern over sliding windows using a DTF measure.

MAIN RESULTS

We showed that a DTF can be used to estimate the flow of seizure activity in a set of simulated micro-electrode data with a known propagation pattern. In general, depending on the location of the micro-electrode grid with respect to the clinical SOZ and the time from seizure onset, ictal propagation changed in directional characteristics over a 2-10 s time scale, with gross directionality limited to spatial dimensions of approximately [Formula: see text]. It was also seen that the strongest seizure patterns in the high frequency band and their sources over such micro-domains are more stable over time and across seizures bordering the clinically determined SOZ than inside.

SIGNIFICANCE

This type of propagation analysis might in future provide an additional tool to epileptologists for characterizing epileptogenic tissue. This will potentially help narrowing down resection zones without compromising essential brain functions as well as provide important information about targeting anti-epileptic stimulation devices.

Ictal propagation of high frequency activity is recapitulated in interictal recordings: effective connectivity of epileptogenic networks recorded with intracranial EEG

Seizures are increasingly understood to arise from epileptogenic networks across which ictal activity is propagated and sustained. In patients undergoing invasive monitoring for epilepsy surgery, high frequency oscillations have been observed within the seizure onset zone during both ictal and interictal intervals. We hypothesized that the patterns by which high frequency activity is propagated would help elucidate epileptogenic networks and thereby identify network nodes relevant for surgical planning. Intracranial EEG recordings were analyzed with a multivariate autoregressive modeling technique (short-time direct directed transfer function--SdDTF), based on the concept of Granger causality, to estimate the directionality and intensity of propagation of high frequency activity (70-175 Hz) during ictal and interictal recordings. These analyses revealed prominent divergence and convergence of high frequency activity propagation at sites identified by epileptologists as part of the ictal onset zone. In contrast, relatively little propagation of this activity was observed among the other analyzed sites. This pattern was observed in both subdural and depth electrode recordings of patients with focal ictal onset, but not in patients with a widely distributed ictal onset. In patients with focal ictal onsets, the patterns of propagation recorded during pre-ictal (up to 5 min immediately preceding ictal onset) and interictal (more than 24h before and after seizures) intervals were very similar to those recorded during seizures. The ability to characterize epileptogenic networks from interictal recordings could have important clinical implications for epilepsy surgery planning by reducing the need for prolonged invasive monitoring to record spontaneous seizures.

Interictal infraslow activity in patients with epilepsy

OBJECTIVE

To evaluate if interictal infraslow activity (ISA), as obtained from a conventional EEG system, can contribute information about the epileptogenic process.

METHODS

The entire long-term intracranial monitoring sessions of 12 consecutive patients were evaluated on an XLTEK system for ISA. Three additional patients had long-term scalp recordings.

RESULTS

In intracranial as well as scalp recordings, the ISA background was consistently higher in the waking state than during sleep. From this background emerged intermittently focal changes, which could achieve in intracranial recordings millivolt amplitudes, while they remained in the microvolt range in scalp recordings. Although they were mainly contiguous between adjacent channels, this was not necessarily the case and intermittent build-up could be seen distant from the epileptogenic zone or radiographic lesion.

CONCLUSIONS

Interictal ISA can be detected in routine intracranial and scalp recordings, without the need for DC amplifiers, and can provide additional information.

SIGNIFICANCE

Since ISA is a separate element of the electromagnetic spectrum, apparently non-neuronal in origin, its assessment should be included not only in the pre-surgical evaluation of epilepsy patients but also in patients with other neurologic disorders and normal volunteers.

Safe direct current stimulation to expand capabilities of neural prostheses

While effective in treating some neurological disorders, neuroelectric prostheses are fundamentally limited because they must employ charge-balanced stimuli to avoid evolution of irreversible electrochemical reactions and their byproducts at the interface between metal electrodes and body fluids. Charge-balancing is typically achieved by using brief biphasic alternating current (AC) pulses, which typically excite nearby neural tissues but cannot efficiently inhibit them. In contrast, direct current (DC) applied via a metal electrode in contact with body fluids can excite, inhibit and modulate sensitivity of neurons; however, chronic DC stimulation is incompatible with biology because it violates charge injection limits that have long been considered unavoidable. In this paper, we describe the design and fabrication of a Safe DC Stimulator (SDCS) that overcomes this constraint. The SCDS drives DC ionic current into target tissue via salt-bridge micropipette electrodes by switching valves in phase with AC square waves applied to metal electrodes contained within the device. This approach achieves DC ionic flow through tissue while still adhering to charge-balancing constraints at each electrode-saline interface. We show the SDCS's ability to both inhibit and excite neural activity to achieve improved dynamic range during prosthetic stimulation of the vestibular part of the inner ear in chinchillas.

EEGgui: a program used to detect electroencephalogram anomalies after traumatic brain injury

Background

Identifying and quantifying pathological changes in brain electrical activity is important for investigations of brain injury and neurological disease. An example is the development of epilepsy, a secondary consequence of traumatic brain injury. While certain epileptiform events can be identified visually from electroencephalographic (EEG) or electrocorticographic (ECoG) records, quantification of these pathological events has proved to be more difficult. In this study we developed MATLAB-based software that would assist detection of pathological brain electrical activity following traumatic brain injury (TBI) and present our MATLAB code used for the analysis of the ECoG.

Methods

Software was developed using MATLAB(™) and features of the open access EEGLAB. EEGgui is a graphical user interface in the MATLAB programming platform that allows scientists who are not proficient in computer programming to perform a number of elaborate analyses on ECoG signals. The different analyses include Power Spectral Density (PSD), Short Time Fourier analysis and Spectral Entropy (SE). ECoG records used for demonstration of this software were derived from rats that had undergone traumatic brain injury one year earlier.

Results

The software provided in this report provides a graphical user interface for displaying ECoG activity and calculating normalized power density using fast fourier transform of the major brain wave frequencies (Delta, Theta, Alpha, Beta1, Beta2 and Gamma). The software further detects events in which power density for these frequency bands exceeds normal ECoG by more than 4 standard deviations. We found that epileptic events could be identified and distinguished from a variety of ECoG phenomena associated with normal changes in behavior. We further found that analysis of spectral entropy was less effective in distinguishing epileptic from normal changes in ECoG activity.

Conclusion

The software presented here was a successful modification of EEGLAB in the Matlab environment that allows detection of epileptiform ECoG signals in animals after TBI. The code allows import of large EEG or ECoG data records as standard text files and uses fast fourier transform as a basis for detection of abnormal events. The software can also be used to monitor injury-induced changes in spectral entropy if required. We hope that the software will be useful for other investigators in the field of traumatic brain injury and will stimulate future advances of quantitative analysis of brain electrical activity after neurological injury or disease.