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Temporal lobe epilepsy (TLE) is the most common form of drug-resistant epilepsy. A major focus of human and animal studies on TLE network has been the limbic circuit. However, there is also evidence suggesting an active role of the basal ganglia in the propagation and control of temporal lobe seizures. Here, we characterize the involvement of the substantia nigra (SN) and somatosensory cortex (SI) during temporal lobe (TL) seizures induced by penicillin injection in the hippocampus (HPC) of two nonhuman primates. The seizure onset and offset patterns were manually classified and spectral power and coherence were calculated. We then compared the 3-second segments recorded in pre-ictal, onset, offset and post-ictal periods based on the seizure onset and offset patterns. Our results demonstrated an involvement of the SN and SI dependent on the seizure onset and offset pattern. We found that low amplitude fast activity (LAF) and high amplitude slow activity (HAS) onset patterns were associated with an increase in activity of the SN while the change in activity was limited to LAF seizures in the SI. However, the increase in HPC/SN coherence was specific to the farther-spreading LAF onset pattern. As for the role of the SN in seizure cessation, we observed that the coherence between the HPC/SN was reduced during burst suppression (BS) compared to other termination phases. Additionally, we found that this coherence returned to normal levels after the seizure ended, with no significant difference in post-ictal periods among the three types of seizure offsets. This study constitutes the first demonstration of TL seizures entraining the SN in the primate brain. Moreover, these findings provide evidence that this entrainment is dependent on the onset and offset pattern and support the hypothesis that the SN might play a role in the maintenance and termination of some specific temporal lobe seizure. [ABSTRACT FROM AUTHOR]

Ischemia stroke and epilepsy are two neurological diseases that have significant patient and societal burden, with similar symptoms of neurological deficits. However, the underlying mechanism of their co-morbidity are still unclear. In this study, we performed a combined analysis of six gene expression profiles (GSE58294, GSE22255, GSE143272, GSE88723, GSE163654, and GSE174574) to reveal the common mechanisms of IS and epilepsy. In the mouse datasets, 74 genes were co-upregulated and 7 genes were co-downregulated in the stroke and epilepsy groups. Further analysis revealed that the co-expressed differentially expressed genes (DEGs) were involved in negative regulation of angiogenesis and the MAPK signaling pathway, and this was verified by Gene Set Enrichment Analysis of human datasets and single cell RNA sequence of middle cerebral artery occlusion mice. In addition, combining DEGs of human and mouse, PTGS2, TMCC3, KCNJ2, and GADD45B were identified as cross species conserved hub genes. Meanwhile, molecular docking results revealed that trichostatin A and valproic acid may be potential therapeutic drugs. In conclusion, to our best knowledge, this study conducted the first comorbidity analysis of epilepsy and ischemic stroke to identify the potential common pathogenic mechanisms and drugs. The findings may provide an important reference for the further studies on post-stroke epilepsy. [ABSTRACT FROM AUTHOR]

The genetic influence in epilepsy, characterized by unprovoked and recurrent seizures, is through variants in genes critical to brain development and function. We have carried out variant calling in Mesial Temporal Lobe Epilepsy (MTLE) patients by mapping the RNA-Seq data available at SRA, NCBI, USA onto human genome assembly hg-19. We have identified 1,75,641 SNVs in patient samples. These SNVs are distributed over 14700 genes of which 655 are already known to be associated with epilepsy. Large number of variants occur in the 3'-UTR, which is one of the regions involved in the regulation of protein translation through binding of miRNAs and RNA-binding proteins (RBP). We have focused on studying the structure-function relationship of the 3'-UTR SNVs that are common to at-least 10 of the 35 patient samples. For the first time we find SNVs exclusively in the 3'-UTR of FGF12, FAR1, NAPB, SLC1A3, SLC12A6, GRIN2A, CACNB4 and FBXO28 genes. Structural modelling reveals that the variant 3'-UTR segments possess altered secondary and tertiary structures which could affect mRNA stability and binding of RBPs to form proper ribonucleoprotein (RNP) complexes. Secondly, these SNVs have either created or destroyed miRNA-binding sites, and molecular modeling reveals that, where binding sites are created, the additional miRNAs bind strongly to 3'-UTR of only variant mRNAs. These two factors affect protein production thereby creating an imbalance in the amounts of select proteins in the cell. We suggest that in the absence of missense and nonsense variants, protein-activity imbalances associated with MTLE patients can be caused through 3'-UTR variants in relevant genes by the mechanisms mentioned above. 3'-UTR SNV has already been identified as causative variant in the neurological disorder, Tourette syndrome. Inhibition of these miRNA-mRNA bindings could be a novel way of treating drug-resistant MTLE patients. We also suggest that joint occurrence of these SNVs could serve as markers for MTLE. We find, in the present study, SNV-mediated destruction of miRNA binding site in the 3'-UTR of the gene encoding glutamate receptor subunit, and, interestingly, overexpression of one of this receptor subunit is also associated with Febrile Seizures. [ABSTRACT FROM AUTHOR]

The mechanisms underlying the emergence of seizures are one of the most important unresolved issues in epilepsy research. In this paper, we study how perturbations, exogenous or endogenous, may promote or delay seizure emergence. To this aim, due to the increasingly adopted view of epileptic dynamics in terms of slow-fast systems, we perform a theoretical analysis of the phase response of a generic relaxation oscillator. As relaxation oscillators are effectively bistable systems at the fast time scale, it is intuitive that perturbations of the non-seizing state with a suitable direction and amplitude may cause an immediate transition to seizure. By contrast, and perhaps less intuitively, smaller amplitude perturbations have been found to delay the spontaneous seizure initiation. By studying the isochrons of relaxation oscillators, we show that this is a generic phenomenon, with the size of such delay depending on the slow flow component. Therefore, depending on perturbation amplitudes, frequency and timing, a train of perturbations causes an occurrence increase, decrease or complete suppression of seizures. This dependence lends itself to analysis and mechanistic understanding through methods outlined in this paper. We illustrate this methodology by computing the isochrons, phase response curves and the response to perturbations in several epileptic models possessing different slow vector fields. While our theoretical results are applicable to any planar relaxation oscillator, in the motivating context of epilepsy they elucidate mechanisms of triggering and abating seizures, thus suggesting stimulation strategies with effects ranging from mere delaying to full suppression of seizures. Author summary: Despite its simplicity, the modelling of epileptic dynamics as a slow-fast transition between low and high activity states mediated by some slow feedback variable is a relatively novel albeit fruitful approach. This study is the first, to our knowledge, characterizing the response of such slow-fast models of epileptic brain to perturbations by computing its isochrons. Besides its numerical computation, we theoretically determine which factors shape the geometry of isochrons for planar slow-fast oscillators. As a consequence, we introduce a theoretical approach providing a clear understanding of the response of perturbations of slow-fast oscillators. Within the epilepsy context, this elucidates the origin of the contradictory role of interictal epileptiform discharges in the transition to seizure, manifested by both pro-convulsive and anti-convulsive effect depending on the amplitude, frequency and timing. More generally, this paper provides theoretical framework highlighting the role of the slow flow component on the response to perturbations in relaxation oscillators, pointing to the general phenomena in such slow-fast oscillators ubiquitous in biological systems. [ABSTRACT FROM AUTHOR]

Surgical interventions in epileptic patients aimed at the removal of the epileptogenic zone have success rates at only 60-70%. This failure can be partly attributed to the insufficient spatial sampling by the implanted intracranial electrodes during the clinical evaluation, leading to an incomplete picture of spatio-temporal seizure organization in the regions that are not directly observed. Utilizing the partial observations of the seizure spreading through the brain network, complemented by the assumption that the epileptic seizures spread along the structural connections, we infer if and when are the unobserved regions recruited in the seizure. To this end we introduce a data-driven model of seizure recruitment and propagation across a weighted network, which we invert using the Bayesian inference framework. Using a leave-one-out cross-validation scheme on a cohort of 45 patients we demonstrate that the method can improve the predictions of the states of the unobserved regions compared to an empirical estimate that does not use the structural information, yet it is on the same level as the estimate that takes the structure into account. Furthermore, a comparison with the performed surgical resection and the surgery outcome indicates a link between the inferred excitable regions and the actual epileptogenic zone. The results emphasize the importance of the structural connectome in the large-scale spatio-temporal organization of epileptic seizures and introduce a novel way to integrate the patient-specific connectome and intracranial seizure recordings in a whole-brain computational model of seizure spread. Author summary: The electrical activity of the brain during an epileptic seizure can be observed with intracranial EEG, that is electrodes implanted in the patient's brain. However, due to the practical constraints only selected brain regions can be implanted, which brings a risk that the abnormal electrical activity in some non-implanted regions is hidden from the observers. In this work we introduce a method to infer what is happening in the unobserved parts based on the incomplete observations of the epileptic seizure. The method relies on the assumption that the seizure spreads along the white-matter structural connections, and finds the explanation of the whole-brain seizure spread consistent with the data. The structural connectome can be estimated from diffusion-weighted imaging for an individual patient, therefore this way the patient-specific structural connectome is utilized to better analyze the patients' seizure recordings. [ABSTRACT FROM AUTHOR]

The extraction of electrophysiological features that reliably forecast the occurrence of seizures is one of the most challenging goals in epilepsy research. Among possible approaches to tackle this problem is the use of active probing paradigms in which responses to stimuli are used to detect underlying system changes leading up to seizures. This work evaluates the theoretical and mechanistic underpinnings of this strategy using two coupled populations of the well-studied Wendling neural mass model. Different model settings are evaluated, shifting parameters (excitability, slow inhibition, or inter-population coupling gains) from normal towards ictal states while probing stimuli are applied every 2 seconds to the input of either one or both populations. The correlation between the extracted features and the ictogenic parameter shifting indicates if the impending transition to the ictal state may be identified in advance. Results show that not only can the response to the probing stimuli forecast seizures but this is true regardless of the altered ictogenic parameter. That is, similar feature changes are highlighted by probing stimuli responses in advance of the seizure including: increased response variance and lag-1 autocorrelation, decreased skewness, and increased mutual information between the outputs of both model subsets. These changes were mostly restricted to the stimulated population, showing a local effect of this perturbational approach. The transition latencies from normal activity to sustained discharges of spikes were not affected, suggesting that stimuli had no pro-ictal effects. However, stimuli were found to elicit interictal-like spikes just before the transition to the ictal state. Furthermore, the observed feature changes highlighted by probing the neuronal populations may reflect the phenomenon of critical slowing down, where increased recovery times from perturbations may signal the loss of a systems' resilience and are common hallmarks of an impending critical transition. These results provide more evidence that active probing approaches highlight information about underlying system changes involved in ictogenesis and may be able to play a role in assisting seizure forecasting methods which can be incorporated into early-warning systems that ultimately enable closing the loop for targeted seizure-controlling interventions. Author summary: Epilepsy is characterized by spontaneous and recurrent seizures. Developing a method to forecast the occurrence of these events would ease part of the burden to patients by providing warning systems and identifying critical periods for closed-loop seizure suppressing methods. However, this task is far from trivial and doing this in a clinical setting has been a challenge that is not yet solved. A possible way to achieve this is by using active probing paradigms, in which stimuli are used to highlight otherwise hidden changes in brain dynamics that may lead to seizures. In this work, this approach is tested in a computational model with two coupled neuronal populations. Active probing responses highlighted underlying model parameter changes that led neuronal activity closer to seizures, something that was not detected with the passive observation in most evaluated model settings. Observed feature changes revealed higher excitability, longer recovery times from stimuli, and increased synchrony between populations as the threshold to seizure-like activity approached. This indicates that low frequency stimuli may be used to reveal early-warning signs and assist in seizure forecasting methods. [ABSTRACT FROM AUTHOR]

Epilepsy is a dynamic and complex neurological disease affecting about 1% of the worldwide population, among which 30% of the patients are drug-resistant. Epilepsy is characterized by recurrent episodes of paroxysmal neural discharges (the so-called seizures), which manifest themselves through a large-amplitude rhythmic activity observed in depth-EEG recordings, in particular in local field potentials (LFPs). The signature characterizing the transition to seizures involves complex oscillatory patterns, which could serve as a marker to prevent seizure initiation by triggering appropriate therapeutic neurostimulation methods. To investigate such protocols, neurophysiological lumped-parameter models at the mesoscopic scale, namely neural mass models, are powerful tools that not only mimic the LFP signals but also give insights on the neural mechanisms related to different stages of seizures. Here, we analyze the multiple time-scale dynamics of a neural mass model and explain the underlying structure of the complex oscillations observed before seizure initiation. We investigate population-specific effects of the stimulation and the dependence of stimulation parameters on synaptic timescales. In particular, we show that intermediate stimulation frequencies (>20 Hz) can abort seizures if the timescale difference is pronounced. Those results have the potential in the design of therapeutic brain stimulation protocols based on the neurophysiological properties of tissue. Author summary: Epilepsy is a complex disease affecting 1% of the worldwide population of which 30% of the patients are drug-resistant and seeking for alternative therapeutic methods, such as neurostimulation. Epileptic seizures can be hallmarked by preceding pre-ictal phases which are a possible window of opportunity to trigger electrical stimulation with the objective to prevent seizure initiation. Biophysiological models are an appropriate framework to understand underlying dynamics and transitions between different epileptogenic phases. In this study, we consider a typical pre-ictal regime with complex bursting-type oscillations, which can be accurately reproduced by a neural mass model. By analyzing the multiple time-scaled structure of the model, we identify the key role of the subpopulations of GABAergic interneurons. We show that appropriate brain stimulation targeting GABAergic interneurons is able to abort pre-ictal bursting, thus preventing seizures to develop. [ABSTRACT FROM AUTHOR]

The mechanisms of epileptic discharge generation and spread are not yet fully known. A recently proposed simple biophysical model of interictal and ictal discharges, Epileptor-2, reproduces well the main features of neuronal excitation and ionic dynamics during discharge generation. In order to distinguish between two hypothesized mechanisms of discharge propagation, we extend the model to the case of two-dimensional propagation along the cortical neural tissue. The first mechanism is based on extracellular potassium diffusion, and the second is the propagation of spikes and postsynaptic signals along axons and dendrites. Our simulations show that potassium diffusion is too slow to reproduce an experimentally observed speed of ictal wavefront propagation (tenths of mm/s). By contrast, the synaptic mechanism predicts well the speed and synchronization of the pre-ictal bursts before the ictal front and the afterdischarges in the ictal core. Though this fact diminishes the role of diffusion and electrodiffusion, the model nevertheless highlights the role of potassium extrusion during neuronal excitation, which provides a positive feedback that changes at the ictal wavefront the balance of excitation versus inhibition in favor of excitation. This finding may help to find a target for a treatment to prevent seizure propagation. [ABSTRACT FROM AUTHOR]

Objective: To clarify the complex mechanism underlying epileptogeneis, a novel animal model was generated. Methods: In our previous research, we have generated a melanocyte-lineage mTOR hyperactivation mouse model (Mitf-M-Cre Tsc2 KO mice; cKO mice) to investigate mTOR pathway in melanogenesis regulation, markedly reduced skin pigmentation was observed. Very unexpectedly, spontaneous recurrent epilepsy was also developed in this mouse model. Results: Compared with control littermates, no change was found in either brain size or brain mass in cKO mice. Hematoxylin staining revealed no obvious aberrant histologic features in the whole brains of cKO mice. Histoimmunofluorescence staining and electron microscopy examination revealed markedly increased mTOR signaling and hyperproliferation of mitochondria in cKO mice, especially in the hippocampus. Furthermore, rapamycin treatment reversed these abnormalities. Conclusions: This study suggests that our melanocyte-lineage mTOR hyperactivation mouse is a novel animal model of epilepsy, which may promote the progress of both epilepsy and neurophysiology research. [ABSTRACT FROM AUTHOR]

Epilepsy is a significant contributor to worldwide disability. In epilepsy, disability can be broadly divided into two components: ictal (pertaining to the burden of unpredictable seizures and associated medical complications including death) and interictal (pertaining to more pervasive debilitating changes in cognitive and emotional behavior). In this study, we objectively and noninvasively appraise aspects of ictal and interictal behavior in mice using instrumented home-cage chambers designed to assay kinematic and appetitive behavioral measures. Through daily intraperitoneal injections of the chemoconvulsant pentylenetetrazole (PTZ) applied to C57BL/6J mice, we coordinately measure how "behavioral severity" (complex dynamic changes in movement and sheltering behavior) and convulsive severity (latency and occurrence of convulsive seizures) evolve or kindle with repeated injections. By closely studying long epochs between PTZ injections, we identify an interictal syndrome of nocturnal hypoactivity and increased sheltering behavior which remits with the cessation of seizure induction. We observe elements of this interictal behavioral syndrome in seizure-prone DBA/2J mice and in mice with a pathogenic Scn1a mutation (modeling Dravet syndrome). Through analyzing their responses to PTZ, we illustrate how convulsive severity and "behavioral" severity are distinct and independent aspects of the overall severity of a PTZ-induced seizure. Our results illustrate the utility of an ethologically centered automated approach to quantitatively appraise murine expressions of disability in mouse models of seizures and epilepsy. In doing so, this study highlights the very unique psychopharmacological profile of PTZ. [ABSTRACT FROM AUTHOR]

Information transmission in the human brain is a fundamentally dynamic network process. In partial epilepsy, this process is perturbed and highly synchronous seizures originate in a local network, the so-called epileptogenic zone (EZ), before recruiting other close or distant brain regions. We studied patient-specific brain network models of 15 drug-resistant epilepsy patients with implanted stereotactic electroencephalography (SEEG) electrodes. Each personalized brain model was derived from structural data of magnetic resonance imaging (MRI) and diffusion tensor weighted imaging (DTI), comprising 88 nodes equipped with region specific neural mass models capable of demonstrating a range of epileptiform discharges. Each patient’s virtual brain was further personalized through the integration of the clinically hypothesized EZ. Subsequent simulations and connectivity modulations were performed and uncovered a finite repertoire of seizure propagation patterns. Across patients, we found that (i) patient-specific network connectivity is predictive for the subsequent seizure propagation pattern; (ii) seizure propagation is characterized by a systematic sequence of brain states; (iii) propagation can be controlled by an optimal intervention on the connectivity matrix; (iv) the degree of invasiveness can be significantly reduced via the proposed seizure control as compared to traditional resective surgery. To stop seizures, neurosurgeons typically resect the EZ completely. We showed that stability analysis of the network dynamics, employing structural and dynamical information, estimates reliably the spatiotemporal properties of seizure propagation. This suggests novel less invasive paradigms of surgical interventions to treat and manage partial epilepsy. [ABSTRACT FROM AUTHOR]

Quantification of interictal spikes in EEG may provide insight on epilepsy disease burden, but manual quantification of spikes is time-consuming and subject to bias. We present a probability-based, automated method for the classification and quantification of interictal events, using EEG data from kainate- and saline-injected mice (C57BL/6J background) several weeks post-treatment. We first detected high-amplitude events, then projected event waveforms into Principal Components space and identified clusters of spike morphologies using a Gaussian Mixture Model. We calculated the odds-ratio of events from kainate- versus saline-treated mice within each cluster, converted these values to probability scores, P(kainate), and calculated an Hourly Epilepsy Index for each animal by summing the probabilities for events where the cluster P(kainate) > 0.5 and dividing the resultant sum by the record duration. This Index is predictive of whether an animal received an epileptogenic treatment (i.e., kainate), even if a seizure was never observed. We applied this method to an out-of-sample dataset to assess epileptiform spike morphologies in five kainate mice monitored for ~1 month. The magnitude of the Index increased over time in a subset of animals and revealed changes in the prevalence of epileptiform (P(kainate) > 0.5) spike morphologies. Importantly, in both data sets, animals that had electrographic seizures also had a high Index. This analysis is fast, unbiased, and provides information regarding the salience of spike morphologies for disease progression. Future refinement will allow a better understanding of the definition of interictal spikes in quantitative and unambiguous terms. [ABSTRACT FROM AUTHOR]

Epileptic seizures are known to follow specific changes in brain dynamics. While some algorithms can nowadays robustly detect these changes, a clear understanding of the mechanism by which these alterations occur and generate seizures is still lacking. Here, we provide crossvalidated evidence that such changes are initiated by an alteration of physiological network state dynamics. Specifically, our analysis of long intracranial electroencephalography (iEEG) recordings from a group of 10 patients identifies a critical phase of a few hours in which time-dependent network states become less variable ("degenerate"), and this phase is followed by a global functional connectivity reduction before seizure onset. This critical phase is characterized by an abnormal occurrence of highly correlated network instances and is shown to be particularly associated with the activity of the resected regions in patients with validated postsurgical outcome. Our approach characterizes preseizure network dynamics as a cascade of 2 sequential events providing new insights into seizure prediction and control. [ABSTRACT FROM AUTHOR]

Seizure clustering is a common and significant phenomenon in patients with epilepsy. The clustering of spontaneous recurrent seizures (SRSs) in animal models of epilepsy, including mouse pilocarpine models, has been reported. However, most studies have analyzed seizures for a short duration after the induction of status epilepticus (SE). In this study, we investigated the detailed characteristics of seizure clustering in the chronic stage of a mouse pilocarpine-induced epilepsy model for an extended duration by continuous 24/7 video-EEG monitoring. A seizure cluster was defined as the occurrence of one or more seizures per day for at least three consecutive days and at least five seizures during the cluster period. We analyzed the cluster duration, seizure-free period, cluster interval, and numbers of seizures within and outside the seizure clusters. The video-EEG monitoring began 84.5±33.7 days after the induction of SE and continued for 53.7±20.4 days. Every mouse displayed seizure clusters, and 97.0% of the seizures occurred within a cluster period. The seizure clusters were followed by long seizure-free periods of 16.3±6.8 days, showing a cyclic pattern. The SRSs also occurred in a grouped pattern within a day. We demonstrate that almost all seizures occur in clusters with a cyclic pattern in the chronic stage of a mouse pilocarpine-induced epilepsy model. The seizure-free periods between clusters were long. These findings should be considered when performing in vivo studies using this animal model. Furthermore, this model might be appropriate for studying the unrevealed mechanism of ictogenesis. [ABSTRACT FROM AUTHOR]

Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understand how dynamics change when parameters are varied. Despite being considered low dimensional in comparison to micro-scale, neuronal network models, with regards to understanding the relationship between parameters and dynamics, NMMs are still prohibitively high dimensional for classical approaches such as numerical continuation. Therefore, we need alternative methods to characterise dynamics of NMMs in high dimensional parameter spaces. Here, we introduce a statistical framework that enables the efficient exploration of the relationship between model parameters and selected features of the simulated, emergent model dynamics of NMMs. We combine the classical machine learning approaches of trees and random forests to enable studying the effect that varying multiple parameters has on the dynamics of a model. The method proceeds by using simulations to transform the mathematical model into a database. This database is then used to partition parameter space with respect to dynamic features of interest, using random forests. This allows us to rapidly explore dynamics in high dimensional parameter space, capture the approximate location of qualitative transitions in dynamics and assess the relative importance of all parameters in the model in all dimensions simultaneously. We apply this method to a commonly used NMM in the context of transitions to seizure dynamics. We find that the inhibitory sub-system is most crucial for the generation of seizure dynamics, confirm and expand previous findings regarding the ratio of excitation and inhibition, and demonstrate that previously overlooked parameters can have a significant impact on model dynamics. We advocate the use of this method in future to constrain high dimensional parameter spaces enabling more efficient, person-specific, model calibration. [ABSTRACT FROM AUTHOR]

Reduced gamma-aminobutyric acid (GABA) inhibition has been implicated in both anxiety and epilepsy. GAD65-/- (NOD/LtJ) mice have significantly decreased basal GABA levels in the brain and a lowered threshold for seizure generation. One fifth of GAD65 -/- mice experienced stress-induced seizures upon exposure to an open field at 4 weeks of age. In each successive week until 8 weeks of age, the latency to seizures decreased with prior seizure experience. 100% of GAD65-/- mice exhibited stress-induced seizures by the end of 8 weeks. GAD65-/- mice also exhibited marked impairment in open field exploratory behavior and deficits in spatial learning acquisition on a Barnes maze. Anxiety-like behavior in an open field was observed prior to seizure onset and was predictive of subsequent seizures. Immunohistochemical characterization of interneuron subtypes in GAD65-/- mice showed a selective decrease in GABA and neuropeptide Y (NPY) levels and no change in calbindin (CLB) or calretinin (CLR) immunoreactivity in the hippocampus. Stem cells from the medial ganglionic eminence (MGE) were injected into the hippocampal hilus to restore GABAergic interneurons. One week after transplantation, MGE-transplanted mice demonstrated significant seizure resistance compared to sham surgical controls. The percent area of GFP+ MGE graft in the hippocampus correlated significantly with the increase in seizure latency. Our data indicate that impaired GABAergic neurotransmission can cause anxiety-like behavior and stress-induced seizures that can be rescued by MGE stem cell transplantation. [ABSTRACT FROM AUTHOR]

Epilepsy is one of the most common neurological disorders affecting about 1% of the world population. For patients with focal seizures that cannot be treated with antiepileptic drugs, the common treatment is a surgical procedure for removal of the seizure onset zone (SOZ). In this work we introduce an algorithm for automatic localization of the seizure onset zone (SOZ) in epileptic patients based on electrocorticography (ECoG) recordings. The proposed algorithm builds upon the hypothesis that the abnormal excessive (or synchronous) neuronal activity in the brain leading to seizures starts in the SOZ and then spreads to other areas in the brain. Thus, when this abnormal activity starts, signals recorded at electrodes close to the SOZ should have a relatively large causal influence on the rest of the recorded signals. The SOZ localization is executed in two steps. First, the algorithm represents the set of electrodes using a directed graph in which nodes correspond to recording electrodes and the edges’ weights quantify the pair-wise causal influence between the recorded signals. Then, the algorithm infers the SOZ from the estimated graph using a variant of the PageRank algorithm followed by a novel post-processing phase. Inference results for 19 patients show a close match between the SOZ inferred by the proposed approach and the SOZ estimated by expert neurologists (success rate of 17 out of 19). [ABSTRACT FROM AUTHOR]

The synchronization among the activities of neural populations in functional regions is one of the most important electrophysiological phenomena in epileptic brains. The spatiotemporal dynamics of phase synchronization was investigated to reveal the reciprocal interaction between different functional regions during epileptogenesis. Local field potentials (LFPs) were recorded simultaneously from the basolateral amygdala (BLA), the cornu ammonis 1 of hippocampus (CA1) and the mediodorsal nucleus of thalamus (MDT) in the mouse amygdala-kindling models during the development of epileptic seizures. The synchronization of LFPs was quantified between BLA, CA1 and MDT using phase-locking value (PLV). During amygdala kindling, behavioral changes (from stage 0 to stage 5) of mice were accompanied by after-discharges (ADs) of similar waveforms appearing almost simultaneously in CA1, MDT, as well as BLA. AD durations were positively related to the intensity of seizures. During seizures at stages 1~2, PLVs remained relatively low and increased dramatically shortly after the termination of the seizures; by contrast, for stages 3~5, PLVs remained a relatively low level during the initial period but increased dramatically before the seizure termination. And in the theta band, the degree of PLV enhancement was positively associated with seizure intensity. The results suggested that during epileptogenesis, the functional regions were kept desynchronized rather than hyper-synchronized during either the initial or the entire period of the seizures; so different dynamic patterns of phase synchronization may be involved in different periods of the epileptogenesis, and this might also reflect that during seizures at different stages, the mechanisms underlying the dynamics of phase synchronization were different. [ABSTRACT FROM AUTHOR]

Although there are now a number of antiepileptic drugs (AEDs) available, approximately one-third of epilepsy patients respond poorly to drug intervention. The reasons for this are complex, but are probably reflective of the increasing number of identified mutations that predispose individuals to this disease. Thus, there is a clear requirement for the development of novel treatments to address this unmet clinical need. The existence of gene mutations that mimic a seizure-like behaviour in the fruit fly, Drosophila melanogaster, offers the possibility to exploit the powerful genetics of this insect to identify novel cellular targets to facilitate design of more effective AEDs. In this study we use neuronal expression of GCaMP, a potent calcium reporter, to image neuronal activity using a non-invasive and rapid method. Expression in motoneurons in the isolated CNS of third instar larvae shows waves of calcium-activity that pass between segments of the ventral nerve cord. Time between calcium peaks, in the same neurons, between adjacent segments usually show a temporal separation of greater than 200 ms. Exposure to proconvulsants (picrotoxin or 4-aminopyridine) reduces separation to below 200 ms showing increased synchrony of activity across adjacent segments. Increased synchrony, characteristic of epilepsy, is similarly observed in genetic seizure mutants: bangsenseless1 (bss1) and paralyticK1270T (paraK1270T). Exposure of bss1 to clinically-used antiepileptic drugs (phenytoin or gabapentin) significantly reduces synchrony. In this study we use the measure of synchronicity to evaluate the effectiveness of known and novel anticonvulsive compounds (antipain, isethionate, etopiside rapamycin and dipyramidole) to reduce seizure-like CNS activity. We further show that such compounds also reduce the Drosophila voltage-gated persistent Na+ current (INaP) in an identified motoneuron (aCC). Our combined assays provide a rapid and reliable method to screen unknown compounds for potential to function as anticonvulsants. [ABSTRACT FROM AUTHOR]

Epileptic seizure dynamics span multiple scales in space and time. Understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. Mathematical models have been developed to reproduce seizure dynamics across scales ranging from the single neuron to the neural population. In this study, we develop a network model of spiking neurons and systematically investigate the conditions, under which the network displays the emergent dynamic behaviors known from the Epileptor, which is a well-investigated abstract model of epileptic neural activity. This approach allows us to study the biophysical parameters and variables leading to epileptiform discharges at cellular and network levels. Our network model is composed of two neuronal populations, characterized by fast excitatory bursting neurons and regular spiking inhibitory neurons, embedded in a common extracellular environment represented by a slow variable. By systematically analyzing the parameter landscape offered by the simulation framework, we reproduce typical sequences of neural activity observed during status epilepticus. We find that exogenous fluctuations from extracellular environment and electro-tonic couplings play a major role in the progression of the seizure, which supports previous studies and further validates our model. We also investigate the influence of chemical synaptic coupling in the generation of spontaneous seizure-like events. Our results argue towards a temporal shift of typical spike waves with fast discharges as synaptic strengths are varied. We demonstrate that spike waves, including interictal spikes, are generated primarily by inhibitory neurons, whereas fast discharges during the wave part are due to excitatory neurons. Simulated traces are compared with in vivo experimental data from rodents at different stages of the disorder. We draw the conclusion that slow variations of global excitability, due to exogenous fluctuations from extracellular environment, and gap junction communication push the system into paroxysmal regimes. We discuss potential mechanisms underlying such machinery and the relevance of our approach, supporting previous detailed modeling studies and reflecting on the limitations of our methodology. [ABSTRACT FROM AUTHOR]

S100B is a reporter of blood-brain barrier (BBB) integrity which appears in blood when the BBB is breached. Circulating S100B derives from either extracranial sources or release into circulation by normal fluctuations in BBB integrity or pathologic BBB disruption (BBBD). Elevated S100B matches the clinical presence of indices of BBBD (gadolinium enhancement or albumin coefficient). After repeated sub-concussive episodes, serum S100B triggers an antigen-driven production of anti-S100B autoantibodies. We tested the hypothesis that the presence of S100B in extracranial tissue is due to peripheral cellular uptake of serum S100B by antigen presenting cells, which may induce the production of auto antibodies against S100B. To test this hypothesis, we used animal models of seizures, enrolled patients undergoing repeated BBBD, and collected serum samples from epileptic patients. We employed a broad array of techniques, including immunohistochemistry, RNA analysis, tracer injection and serum analysis. mRNA for S100B was segregated to barrier organs (testis, kidney and brain) but S100B protein was detected in immunocompetent cells in spleen, thymus and lymph nodes, in resident immune cells (Langerhans, satellite cells in heart muscle, etc.) and BBB endothelium. Uptake of labeled S100B by rat spleen CD4+ or CD8+ and CD86+ dendritic cells was exacerbated by pilocarpine-induced status epilepticus which is accompanied by BBBD. Clinical seizures were preceded by a surge of serum S100B. In patients undergoing repeated therapeutic BBBD, an autoimmune response against S100B was measured. In addition to its role in the central nervous system and its diagnostic value as a BBBD reporter, S100B may integrate blood-brain barrier disruption to the control of systemic immunity by a mechanism involving the activation of immune cells. We propose a scenario where extravasated S100B may trigger a pathologic autoimmune reaction linking systemic and CNS immune responses. [ABSTRACT FROM AUTHOR]

Epilepsy and other seizure disorders are not adequately managed with currently available drugs. We recently synthesized a series of dibromophenyl enaminones and demonstrated that AK6 and E249 were equipotent to previous analogs but more efficacious in suppressing neuronal excitation. Here we examined the actions of these lead compounds on in vitro and in vivo seizure models. In vitro seizures were induced in the hippocampal slice chemically (zero Mg2+ buffer and picrotoxin) and electrically using patterned high frequency stimulation (HFS) of afferents. In vivo seizures were induced in rats using the 6 Hz and the maximal electroshock models. AK6 (10 µM) and E249 (10 µM) depressed the amplitude of population spikes recorded in area CA1 of the hippocampus by −50.5±4.3% and −40.1±3.1% respectively, with partial recovery after washout. In the zero Mg2+ model, AK6 (10 µM) depressed multiple population spiking (mPS) by −59.3±6.9% and spontaneous bursts (SBs) by −65.9±7.2% and in the picrotoxin-model by −43.3±7.2% and −50.0±8.3%, respectively. Likewise, E249 (10 µM) depressed the zero-Mg2+-induced mPS by −48.8±9.5% and SBs by −55.8±15.5%, and in the picrotoxin model by −37.1±5.5% and −56.5±11.4%, respectively. They both suppressed post-HFS induced afterdischarges and SBs. AK6 and E249 dose-dependently protected rats in maximal electroshock and 6 Hz models of in vivo seizures after 30 min pretreatment. Their level of protection in both models was similar to that obtained with phenytoin Finally, while AK6 had no effect on locomotion in rats, phenytoin significantly decreased locomotion. AK6 and E249, suppressed in vitro and in vivo seizures to a similar extent. Their in vivo activities are comparable with but not superior to phenytoin. The most efficacious, AK6 produced no locomotor suppression while phenytoin did. Thus, AK6 and E249 may be excellent candidates for further investigation as potential agents for the treatment of epilepsy syndromes with possibly less CNS side effects. [ABSTRACT FROM AUTHOR]

Epilepsy is a disorder characterized by excessive synchronized neural activity. The hippocampus and surrounding temporal lobe structures appear particularly sensitive to epileptiform activity. Somatostatin (SST)-positive interneurons within the hilar region have been suggested to gate hippocampal activity, and therefore may play a crucial role in the dysregulation of hippocampal activity. In this study, we examined SST interneuron activity in the in vitro 4-aminopyridine (4-AP) model of epilepsy. We employed a multi-disciplinary approach, combining extracellular multi-electrode array (MEA) recordings with patch-clamp recordings and optical imaging using a genetically encoded calcium sensor. We observed that hilar SST interneurons are strongly synchronized during 4-AP-induced local field potentials (LFPs), as assayed by Ca2+ imaging as well as juxtacellular or intracellular recording. SST interneurons were particularly responsive to GABA-mediated LFPs that occurred in the absence of ionotropic glutamatergic transmission. Our results present evidence that the extensive synchronized activity of SST-expressing interneurons contribute to the generation of GABAergic LFPs in an in vitro model of temporal lobe seizures. [ABSTRACT FROM AUTHOR]

Epileptic seizure is a paroxysmal and self-limited phenomenon characterized by abnormal hypersynchrony of a large population of neurons. However, our current understanding of seizure dynamics is still limited. Here we propose a novel in vivo model of seizure-like afterdischarges using optogenetics, and report on investigation of directional network dynamics during seizure along the septo-temporal (ST) axis of hippocampus. Repetitive pulse photostimulation was applied to the rodent hippocampus, in which channelrhodopsin-2 (ChR2) was expressed, under simultaneous recording of local field potentials (LFPs). Seizure-like afterdischarges were successfully induced after the stimulation in both W-TChR2V4 transgenic (ChR2V-TG) rats and in wild type rats transfected with adeno-associated virus (AAV) vectors carrying ChR2. Pulse frequency at 10 and 20 Hz, and a 0.05 duty ratio were optimal for afterdischarge induction. Immunohistochemical c-Fos staining after a single induced afterdischarge confirmed neuronal activation of the entire hippocampus. LFPs were recorded during seizure-like afterdischarges with a multi-contact array electrode inserted along the ST axis of hippocampus. Granger causality analysis of the LFPs showed a bidirectional but asymmetric increase in signal flow along the ST direction. State space presentation of the causality and coherence revealed three discrete states of the seizure-like afterdischarge phenomenon: 1) resting state; 2) afterdischarge initiation with moderate coherence and dominant septal-to-temporal causality; and 3) afterdischarge termination with increased coherence and dominant temporal-to-septal causality. A novel in vivo model of seizure-like afterdischarge was developed using optogenetics, which was advantageous in its reproducibility and artifact-free electrophysiological observations. Our results provide additional evidence for the potential role of hippocampal septo-temporal interactions in seizure dynamics in vivo. Bidirectional networks work hierarchically along the ST hippocampus in the genesis and termination of epileptic seizures. [ABSTRACT FROM AUTHOR]

Targeting pro-inflammatory events to reduce seizures is gaining momentum. Experimentally, antagonism of inflammatory processes and of blood-brain barrier (BBB) damage has been demonstrated to be beneficial in reducing status epilepticus (SE). Clinically, a role of inflammation in the pathophysiology of drug resistant epilepsies is suspected. However, the use anti-inflammatory drug such as glucocorticosteroids (GCs) is limited to selected pediatric epileptic syndromes and spasms. Lack of animal data may be one of the reasons for the limited use of GCs in epilepsy. We evaluated the effect of the CG dexamethasone in reducing the onset and the severity of pilocarpine SE in rats. We assessed BBB integrity by measuring serum S100β and Evans Blue brain extravasation. Electrophysiological monitoring and hematologic measurements (WBCs and IL-1β) were performed. We reviewed the effect of add on dexamethasone treatment on a population of pediatric patients affected by drug resistant epilepsy. We excluded subjects affected by West, Landau-Kleffner or Lennox-Gastaut syndromes and Rasmussen encephalitis, known to respond to GCs or adrenocorticotropic hormone (ACTH). The effect of two additional GCs, methylprednisolone and hydrocortisone, was also reviewed in this population. When dexamethasone treatment preceded exposure to the convulsive agent pilocarpine, the number of rats developing status epilepticus (SE) was reduced. When SE developed, the time-to-onset was significantly delayed compared to pilocarpine alone and mortality associated with pilocarpine-SE was abolished. Dexamethasone significantly protected the BBB from damage. The clinical study included pediatric drug resistant epileptic subjects receiving add on GC treatments. Decreased seizure frequency (≥50%) or interruption of status epilepticus was observed in the majority of the subjects, regardless of the underlying pathology. Our experimental results point to a seizure-reducing effect of dexamethasone. The mechanism encompasses improvement of BBB integrity. Our results also suggest that add on GCs could be of efficacy in controlling pediatric drug resistant seizures. [ABSTRACT FROM AUTHOR]

Seizures in focal epilepsies are sustained by a highly synchronous neuronal discharge that arises at restricted brain sites and subsequently spreads to large portions of the brain. Despite intense experimental research in this field, the earlier cellular events that initiate and sustain a focal seizure are still not well defined. Their identification is central to understand the pathophysiology of focal epilepsies and to develop new pharmacological therapies for drug-resistant forms of epilepsy. The prominent involvement of astrocytes in ictogenesis was recently proposed. We test here whether a cooperation between astrocytes and neurons is a prerequisite to support ictal (seizure-like) and interictal epileptiform events. Simultaneous patchclamp recording and Ca2+ imaging techniques were performed in a new in vitro model of focal seizures induced by local applications of N-methyl-D-aspartic acid (NMDA) in rat entorhinal cortex slices. We found that a Ca2+ elevation in astrocytes correlates with both the initial development and the maintenance of a focal, seizure-like discharge. A delayed astrocyte activation during ictal discharges was also observed in other models (including the whole in vitro isolated guinea pig brain) in which the site of generation of seizure activity cannot be precisely monitored. In contrast, interictal discharges were not associated with Ca2+ changes in astrocytes. Selective inhibition or stimulation of astrocyte Ca2+ signalling blocked or enhanced, respectively, ictal discharges, but did not affect interictal discharge generation. Our data reveal that neurons engage astrocytes in a recurrent excitatory loop (possibly involving gliotransmission) that promotes seizure ignition and sustains the ictal discharge. This neuron-astrocyte interaction may represent a novel target to develop effective therapeutic strategies to control seizures. [ABSTRACT FROM AUTHOR]

Seizures in focal epilepsies are sustained by a highly synchronous neuronal discharge that arises at restricted brain sites and subsequently spreads to large portions of the brain. Despite intense experimental research in this field, the earlier cellular events that initiate and sustain a focal seizure are still not well defined. Their identification is central to understand the pathophysiology of focal epilepsies and to develop new pharmacological therapies for drug-resistant forms of epilepsy. The prominent involvement of astrocytes in ictogenesis was recently proposed. We test here whether a cooperation between astrocytes and neurons is a prerequisite to support ictal (seizure-like) and interictal epileptiform events. Simultaneous patchclamp recording and Ca2+ imaging techniques were performed in a new in vitro model of focal seizures induced by local applications of N-methyl-D-aspartic acid (NMDA) in rat entorhinal cortex slices. We found that a Ca2+ elevation in astrocytes correlates with both the initial development and the maintenance of a focal, seizure-like discharge. A delayed astrocyte activation during ictal discharges was also observed in other models (including the whole in vitro isolated guinea pig brain) in which the site of generation of seizure activity cannot be precisely monitored. In contrast, interictal discharges were not associated with Ca2+ changes in astrocytes. Selective inhibition or stimulation of astrocyte Ca2+ signalling blocked or enhanced, respectively, ictal discharges, but did not affect interictal discharge generation. Our data reveal that neurons engage astrocytes in a recurrent excitatory loop (possibly involving gliotransmission) that promotes seizure ignition and sustains the ictal discharge. This neuron-astrocyte interaction may represent a novel target to develop effective therapeutic strategies to control seizures. [ABSTRACT FROM AUTHOR]