Mouse model of focal cortical dysplasia type II generates a wide spectrum of high-frequency activities.

High-frequency oscillations (HFOs) represent an electrographic biomarker of endogenous epileptogenicity and seizure-generating tissue that proved clinically useful in presurgical planning and delineating the resection area. In the neocortex, the clinical observations on HFOs are not sufficiently supported by experimental studies stemming from a lack of realistic neocortical epilepsy models that could provide an explanation of the pathophysiological substrates of neocortical HFOs. In this study, we explored pathological epileptiform network phenomena, particularly HFOs, in a highly realistic murine model of neocortical epilepsy due to focal cortical dysplasia (FCD) type II. FCD was induced in mice by the expression of the human pathogenic mTOR gene mutation during embryonic stages of brain development. Electrographic recordings from multiple cortical regions in freely moving animals with FCD and epilepsy demonstrated that the FCD lesion generates HFOs from all frequency ranges, i.e., gamma, ripples, and fast ripples up to 800 Hz. Gamma-ripples were recorded almost exclusively in FCD animals, while fast ripples occurred in controls as well, although at a lower rate. Gamma-ripple activity is particularly valuable for localizing the FCD lesion, surpassing the utility of fast ripples that were also observed in control animals, although at significantly lower rates. Propagating HFOs occurred outside the FCD, and the contralateral cortex also generated HFOs independently of the FCD, pointing to a wider FCD network dysfunction. Optogenetic activation of neurons carrying mTOR mutation and expressing Channelrhodopsin-2 evoked fast ripple oscillations that displayed spectral and morphological profiles analogous to spontaneous oscillations. This study brings experimental evidence that FCD type II generates pathological HFOs across all frequency bands and provides information about the spatiotemporal properties of each HFO subtype in FCD. The study shows that mutated neurons represent a functionally interconnected and active component of the FCD network, as they can induce interictal epileptiform phenomena and HFOs.

An update on the seizures beget seizures theory.

Seizures beget seizures is a longstanding theory that proposed that seizure activity can impact the structural and functional properties of the brain circuits in ways that contribute to epilepsy progression and the future occurrence of seizures. Originally proposed by Gowers, this theory continues to be quoted in the pathophysiology of epilepsy. We critically review the existing data and observations on the consequences of recurrent seizures on brain networks and highlight a range of factors that speak for and against the theory. The existing literature demonstrates clearly that ictal activity, especially if recurrent, induces molecular, structural, and functional changes including cell loss, connectivity reorganization, changes in neuronal behavior, and metabolic alterations. These changes have the potential to modify the seizure threshold, contribute to disease progression, and recruit wider areas of the epileptic network into epileptic activity. Repeated seizure activity may, thus, act as a pathological positive-feedback mechanism that increases seizure likelihood. On the other hand, the time course of self-limited epilepsies and the presence of seizure remission in two thirds of epilepsy cases and various chronic epilepsy models oppose the theory. Experimental work showed that seizures could induce neural changes that increase the seizure threshold and decrease the risk of a subsequent seizure. Due to the complex nature of epilepsies, it is wrong to consider only seizures as the key factor responsible for disease progression. Epilepsy worsening can be attributed to the various forms of interictal epileptiform activity or underlying disease mechanisms. Although seizure activity can negatively impact brain structure and function, the "seizures beget seizures" theory should not be used dogmatically but with extreme caution.

Personalized dynamic network models of the human brain as a future tool for planning and optimizing epilepsy therapy.

Epilepsy is a common neurological disorder, with one third of patients not responding to currently available antiepileptic drugs. The proportion of pharmacoresistant epilepsies has remained unchanged for many decades. To cure epilepsy and control seizures requires a paradigm shift in the development of new approaches to epilepsy diagnosis and treatment. Contemporary medicine has benefited from the exponential growth of computational modeling, and the application of network dynamics theory to understanding and treating human brain disorders. In epilepsy, the introduction of these approaches has led to personalized epileptic network modeling that can explore the patient's seizure genesis and predict the functional impact of resection on its individual network's propensity to seize. The application of the dynamic systems approach to neurostimulation therapy of epilepsy allows designing stimulation strategies that consider the patient's seizure dynamics and long-term fluctuations in the stability of their epileptic networks. In this article, we review, in a nontechnical fashion suitable for a broad neuroscientific audience, recent progress in personalized dynamic brain network modeling that is shaping the future approach to the diagnosis and treatment of epilepsy.

Long-term seizure dynamics are determined by the nature of seizures and the mutual interactions between them.

The seemingly random and unpredictable nature of seizures is a major debilitating factor for people with epilepsy. An increasing body of evidence demonstrates that the epileptic brain exhibits long-term fluctuations in seizure susceptibility, and seizure emergence seems to be a consequence of processes operating over multiple temporal scales. A deeper insight into the mechanisms responsible for long-term seizure fluctuations may provide important information for understanding the complex nature of seizure genesis. In this study, we explored the long-term dynamics of seizures in the tetanus toxin model of temporal lobe epilepsy. The results demonstrate the existence of long-term fluctuations in seizure probability, where seizures form clusters in time and are then followed by seizure-free periods. Within each cluster, seizure distribution is non-Poissonian, as demonstrated by the progressively increasing inter-seizure interval (ISI), which marks the approaching cluster termination. The lengthening of ISIs is paralleled by: increasing behavioral seizure severity, the occurrence of convulsive seizures, recruitment of extra-hippocampal structures and the spread of electrographic epileptiform activity outside of the limbic system. The results suggest that repeated non-convulsive seizures obey the 'seizures-beget-seizures' principle, leading to the occurrence of convulsive seizures, which decrease the probability of a subsequent seizure and, thus, increase the following ISI. The cumulative effect of repeated convulsive seizures leads to cluster termination, followed by a long inter-cluster period. We propose that seizures themselves are an endogenous factor that contributes to long-term fluctuations in seizure susceptibility and their mutual interaction determines the future evolution of disease activity.

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".

Chimera states in brain networks: Empirical neural vs. modular fractal connectivity.

Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

Update on the mechanisms and roles of high-frequency oscillations in seizures and epileptic disorders.

High-frequency oscillations (HFOs) are a type of brain activity that is recorded from brain regions capable of generating seizures. Because of the close association of HFOs with epileptogenic tissue and ictogenesis, understanding their cellular and network mechanisms could provide valuable information about the organization of epileptogenic networks and how seizures emerge from the abnormal activity of these networks. In this review, we summarize the most recent advances in the field of HFOs and provide a critical evaluation of new observations within the context of already established knowledge. Recent improvements in recording technology and the introduction of optogenetics into epilepsy research have intensified experimental work on HFOs. Using advanced computer models, new cellular substrates of epileptic HFOs were identified and the role of specific neuronal subtypes in HFO genesis was determined. Traditionally, the pathogenesis of HFOs was explored mainly in patients with temporal lobe epilepsy and in animal models mimicking this condition. HFOs have also been reported to occur in other epileptic disorders and models such as neocortical epilepsy, genetically determined epilepsies, and infantile spasms, which further support the significance of HFOs in the pathophysiology of epilepsy. It is increasingly recognized that HFOs are generated by multiple mechanisms at both the cellular and network levels. Future studies on HFOs combining novel high-resolution in vivo imaging techniques and precise control of neuronal behavior using optogenetics or chemogenetics will provide evidence about the causal role of HFOs in seizures and epileptogenesis. Detailed understanding of the pathophysiology of HFOs will propel better HFO classification and increase their information yield for clinical and diagnostic purposes.

Methodological standards for in vitro models of epilepsy and epileptic seizures. A TASK1-WG4 report of the AES/ILAE Translational Task Force of the ILAE.

In vitro preparations are a powerful tool to explore the mechanisms and processes underlying epileptogenesis and ictogenesis. In this review, we critically review the numerous in vitro methodologies utilized in epilepsy research. We provide support for the inclusion of detailed descriptions of techniques, including often ignored parameters with unpredictable yet significant effects on study reproducibility and outcomes. In addition, we explore how recent developments in brain slice preparation relate to their use as models of epileptic activity.

Detection of interictal epileptiform discharges using signal envelope distribution modelling: application to epileptic and non-epileptic intracranial recordings.

Interictal epileptiform discharges (spikes, IEDs) are electrographic markers of epileptic tissue and their quantification is utilized in planning of surgical resection. Visual analysis of long-term multi-channel intracranial recordings is extremely laborious and prone to bias. Development of new and reliable techniques of automatic spike detection represents a crucial step towards increasing the information yield of intracranial recordings and to improve surgical outcome. In this study, we designed a novel and robust detection algorithm that adaptively models statistical distributions of signal envelopes and enables discrimination of signals containing IEDs from signals with background activity. This detector demonstrates performance superior both to human readers and to an established detector. It is even capable of identifying low-amplitude IEDs which are often missed by experts and which may represent an important source of clinical information. Application of the detector to non-epileptic intracranial data from patients with intractable facial pain revealed the existence of sharp transients with waveforms reminiscent of interictal discharges that can represent biological sources of false positive detections. Identification of these transients enabled us to develop and propose secondary processing steps, which may exclude these transients, improving the detector's specificity and having important implications for future development of spike detectors in general.

Resection of individually identified high-rate high-frequency oscillations region is associated with favorable outcome in neocortical epilepsy.

OBJECTIVES: High-frequency oscillations (HFOs) represent a novel electrophysiologic marker of endogenous epileptogenicity. Clinically, this propensity can be utilized to more accurately delineate the resection margin before epilepsy surgery. Currently, prospective application of HFOs is limited because of a lack of an exact quantitative measure to reliably identify HFO-generating areas necessary to include in the resection. Here, we evaluated the potential of a patient-individualized approach of identifying high-rate HFO regions to plan the neocortical resection. METHODS: Fifteen patients with neocortical seizure-onset zones (SOZs) underwent intracranial electroencephalographic monitoring. To identify interictal HFOs, we applied an automated, hypersensitive HFO-detection algorithm followed by post hoc processing steps to reject false detections. The spatial relationship between HFO distribution and the SOZ was evaluated. To address high interpatient variability in HFO properties, we evaluated the high-rate HFO region, an unbiased statistical parameter, in each patient. The relationship between resection of the high-rate HFO region and postoperative outcome was examined. RESULTS: Grouped data demonstrated that the rate of ripple (60-200 Hz) and fast ripple (200-500 Hz) was increased in the SOZ (both p < 0.01). Intrapatient analysis of the HFO distribution localized the SOZ in 11 patients. High-rate HFO regions were determined in all patients by an individually adjusted threshold. Resection of high-rate HFO regions was significantly associated with a seizure-free outcome (p < 0.01). The extent/ratio of SOZ or spiking region resection did not differ between seizure-free and seizure-persistent groups. SIGNIFICANCE: Intrapatient analysis of high-rate HFOs provides more detailed description of HFO-generating areas and can mark the areas of clinically significant epileptogenicity--a crucial component of the neocortical epileptic network that should be removed to achieve a good outcome. Validating and adopting an unbiased quantitative HFO parameter has the potential to propel wider and prospective utilization of HFOs in the surgical treatment of neocortical epilepsy and to improve its outcome.

NeuroPorator: An open-source, current-limited electroporator for safe in utero gene transfer.

BACKGROUND: Electroporation is an effective technique for genetic manipulation of cells, both in vitro and in vivo. In utero electroporation (IUE) is a special case, which represents a fine application of this technique to genetically modify specific tissues of embryos during prenatal development. Commercially available electroporators are expensive and not fully customizable. We have designed and produced an inexpensive, open-design, and customizable electroporator optimized for safe IUE. We introduce NeuroPorator. METHOD: We used off-the-shelf electrical parts, a single-board microcontroller, and a cheap data logger to build an open-design electroporator. We included a safety circuit to limit the applied electrical current to protect the embryos. We added full documentation, design files, and assembly instructions. RESULT: NeuroPorator output is on par with commercially available devices. Furthermore, the adjustable current limiter protects both the embryos and the uterus from overcurrent damage. A built-in data acquisition module provides real-time visualization and recordings of the actual voltage/current pulses applied to each embryo. Function of NeuroPorator has been demonstrated by inducing focal cortical dysplasia in mice. SIGNIFICANCE AND CONCLUSION: The simple and fully open design enables quick and cheap construction of the device and facilitates further customization. The features of NeuroPorator can accelerate the IUE technique implementation in any laboratory and speed up its learning curve.

Synchronization and desynchronization in epilepsy: controversies and hypotheses.

Epilepsy has been historically seen as a functional brain disorder associated with excessive synchronization of large neuronal populations leading to a hypersynchronous state. Recent evidence showed that epileptiform phenomena, particularly seizures, result from complex interactions between neuronal networks characterized by heterogeneity of neuronal firing and dynamical evolution of synchronization. Desynchronization is often observed preceding seizures or during their early stages; in contrast, high levels of synchronization observed towards the end of seizures may facilitate termination. In this review we discuss cellular and network mechanisms responsible for such complex changes in synchronization. Recent work has identified cell-type-specific inhibitory and excitatory interactions, the dichotomy between neuronal firing and the non-local measurement of local field potentials distant to that firing, and the reflection of the neuronal dark matter problem in non-firing neurons active in seizures. These recent advances have challenged long-established views and are leading to a more rigorous and realistic understanding of the pathophysiology of epilepsy.

Dentate gyrus progenitor cell proliferation after the onset of spontaneous seizures in the tetanus toxin model of temporal lobe epilepsy.

Temporal lobe epilepsy alters adult neurogenesis. Existing experimental evidence is mainly from chronic models induced by an initial prolonged status epilepticus associated with substantial cell death. In these models, neurogenesis increases after status epilepticus. To test whether status epilepticus is necessary for this increase, we examined precursor cell proliferation and neurogenesis after the onset of spontaneous seizures in a model of temporal lobe epilepsy induced by unilateral intrahippocampal injection of tetanus toxin, which does not cause status or, in most cases, detectable neuronal loss. We found a 4.5 times increase in BrdU labeling (estimating precursor cells proliferating during the 2nd week after injection of toxin and surviving at least up to 7days) in dentate gyri of both injected and contralateral hippocampi of epileptic rats. Radiotelemetry revealed that the rats experienced 112±24 seizures, lasting 88±11s each, over a period of 8.6±1.3days from the first electrographic seizure. On the first day of seizures, their duration was a median of 103s, and the median interictal period was 23min, confirming the absence of experimentally defined status epilepticus. The total increase in cell proliferation/survival was due to significant population expansions of: radial glial-like precursor cells (type I; 7.2×), non-radial type II/III neural precursors in the dentate gyrus stem cell niche (5.6×), and doublecortin-expressing neuroblasts (5.1×). We conclude that repeated spontaneous brief temporal lobe seizures are sufficient to promote increased hippocampal neurogenesis in the absence of status epilepticus.

High-frequency oscillations as a new biomarker in epilepsy.

The discovery that electroencephalography (EEG) contains useful information at frequencies above the traditional 80Hz limit has had a profound impact on our understanding of brain function. In epilepsy, high-frequency oscillations (HFOs, >80Hz) have proven particularly important and useful. This literature review describes the morphology, clinical meaning, and pathophysiology of epileptic HFOs. To record HFOs, the intracranial EEG needs to be sampled at least at 2,000Hz. The oscillatory events can be visualized by applying a high-pass filter and increasing the time and amplitude scales, or EEG time-frequency maps can show the amount of high-frequency activity. HFOs appear excellent markers for the epileptogenic zone. In patients with focal epilepsy who can benefit from surgery, invasive EEG is often required to identify the epileptic cortex, but current information is sometimes inadequate. Removal of brain tissue generating HFOs has been related to better postsurgical outcome than removing the seizure onset zone, indicating that HFOs may mark cortex that needs to be removed to achieve seizure control. The pathophysiology of epileptic HFOs is challenging, probably involving populations of neurons firing asynchronously. They differ from physiological HFOs in not being paced by rhythmic inhibitory activity and in their possible origin from population spikes. Their link to the epileptogenic zone argues that their study will teach us much about the pathophysiology of epileptogenesis and ictogenesis. HFOs show promise for improving surgical outcome and accelerating intracranial EEG investigations. Their potential needs to be assessed by future research.

Computational modeling allows unsupervised classification of epileptic brain states across species.

Current advances in epilepsy treatment aim to personalize and responsively adjust treatment parameters to overcome patient heterogeneity in treatment efficiency. For tailoring treatment to the individual and the current brain state, tools are required that help to identify the patient- and time-point-specific parameters of epilepsy. Computational modeling has long proven its utility in gaining mechanistic insight. Recently, the technique has been introduced as a diagnostic tool to predict individual treatment outcomes. In this article, the Wendling model, an established computational model of epilepsy dynamics, is used to automatically classify epileptic brain states in intracranial EEG from patients (n = 4) and local field potential recordings from in vitro rat data (high-potassium model of epilepsy, n = 3). Five-second signal segments are classified to four types of brain state in epilepsy (interictal, preonset, onset, ictal) by comparing a vector of signal features for each data segment to four prototypical feature vectors obtained by Wendling model simulations. The classification result is validated against expert visual assessment. Model-driven brain state classification achieved a classification performance significantly above chance level (mean sensitivity 0.99 on model data, 0.77 on rat data, 0.56 on human data in a four-way classification task). Model-driven prototypes showed similarity with data-driven prototypes, which we obtained from real data for rats and humans. Our results indicate similar electrophysiological patterns of epileptic states in the human brain and the animal model that are well-reproduced by the computational model, and captured by a key set of signal features, enabling fully automated and unsupervised brain state classification in epilepsy.

Structural connectivity-based predictors of cognitive impairment in stroke patients attributable to aging.

Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients' cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.

Rapid reversal of impaired inhibitory and excitatory transmission but not spine dysgenesis in a mouse model of mental retardation.

Intellectual disability affects 2-3% of the population: those due to mutations of the X-chromosome are a major cause of moderate to severe cases (1.8/1000 males). Established theories ascribe the cellular aetiology of intellectual disability to malformations of dendritic spines. Recent work has identified changes in synaptic physiology in some experimental models. Here, we investigated the pathophysiology of a mouse model of intellectual disability using electrophysiological recordings combined with confocal imaging of dentate gyrus granule neurons. Lack of oligophrenin-1 resulted in reductions in dendritic tree complexity and mature dendritic spine density and in evoked and spontaneous EPSCs and IPSCs. In the case of inhibitory transmission, the physiological change was associated with a reduction in the readily releasable pool and vesicle recycling which impaired the efficiency of inhibitory synaptic transmission. Acute inhibition of the downstream signalling pathway of oligophrenin-1 fully reversed the functional changes in synaptic transmission but not the dendritic abnormalities. The impaired inhibitory (as well as excitatory) synaptic transmission at frequencies associated with cognitive function suggests a cellular mechanism for the intellectual disability, because cortical oscillations associated with cognition normally depend on inhibitory neurons firing on every cycle.

High-frequency network activity, global increase in neuronal activity, and synchrony expansion precede epileptic seizures in vitro.

How seizures start is a major question in epilepsy research. Preictal EEG changes occur in both human patients and animal models, but their underlying mechanisms and relationship with seizure initiation remain unknown. Here we demonstrate the existence, in the hippocampal CA1 region, of a preictal state characterized by the progressive and global increase in neuronal activity associated with a widespread buildup of low-amplitude high-frequency activity (HFA) (>100 Hz) and reduction in system complexity. HFA is generated by the firing of neurons, mainly pyramidal cells, at much lower frequencies. Individual cycles of HFA are generated by the near-synchronous (within approximately 5 ms) firing of small numbers of pyramidal cells. The presence of HFA in the low-calcium model implicates nonsynaptic synchronization; the presence of very similar HFA in the high-potassium model shows that it does not depend on an absence of synaptic transmission. Immediately before seizure onset, CA1 is in a state of high sensitivity in which weak depolarizing or synchronizing perturbations can trigger seizures. Transition to seizure is characterized by a rapid expansion and fusion of the neuronal populations responsible for HFA, associated with a progressive slowing of HFA, leading to a single, massive, hypersynchronous cluster generating the high-amplitude low-frequency activity of the seizure.

Epileptic high-frequency network activity in a model of non-lesional temporal lobe epilepsy.

High-frequency cortical activity, particularly in the 250-600 Hz (fast ripple) band, has been implicated in playing a crucial role in epileptogenesis and seizure generation. Fast ripples are highly specific for the seizure initiation zone. However, evidence for the association of fast ripples with epileptic foci depends on animal models and human cases with substantial lesions in the form of hippocampal sclerosis, which suggests that neuronal loss may be required for fast ripples. In the present work, we tested whether cell loss is a necessary prerequisite for the generation of fast ripples, using a non-lesional model of temporal lobe epilepsy that lacks hippocampal sclerosis. The model is induced by unilateral intrahippocampal injection of tetanus toxin. Recordings from the hippocampi of freely-moving epileptic rats revealed high-frequency activity (>100 Hz), including fast ripples. High-frequency activity was present both during interictal discharges and seizure onset. Interictal fast ripples proved a significantly more reliable marker of the primary epileptogenic zone than the presence of either interictal discharges or ripples (100-250 Hz). These results suggest that fast ripple activity should be considered for its potential value in the pre-surgical workup of non-lesional temporal lobe epilepsy.