Cellular and network mechanisms of electrographic seizures

EEG in neonatal seizures: where to look and what to see

INTRODUCTION

Neonatal seizures are frequent and carry a detrimental prognostic outlook. Diagnosis is based on EEG confirmation. Classification has recently changed.

AREAS COVERED

We consulted original papers, book chapters, atlases, and reviews to provide a narrative overview on EEG characteristics of neonatal seizures. We searched PubMed, without time restrictions (last visited: 31 May 2022). Additional papers were extracted from the references list of selected papers. We describe the typical neonatal ictal EEG discharges morphology, location, and propagation, together with age-dependent features. Etiology-dependent electroclinical features, when identifiable, are presented for both acute symptomatic neonatal seizures and neonatal-onset epilepsies and developmental/epileptic encephalopathies. The few ictal variables known to predict long-term outcome have been discussed.

EXPERT OPINION

Multimodal neuromonitoring in critically ill newborns, high-density EEG, and functional neuroimaging might increase our insight into the neurophysiological bases of seizures in newborns. Increasing availability of long-term monitoring with conventional video-EEG and automated detection methods will allow clinicians and researchers to gather an ever expanding bulk of clinical and neurophysiological data to enhance accuracy with deep phenotyping. The latest classification proposal represents an input for critically revising our diagnostic abilities with respect to seizure definition, duration, and semiology, possibly further promoting clinical research.

Classification of antiseizure drugs in cultured neuronal networks using multielectrode arrays and unsupervised learning

OBJECTIVE

Antiseizure drugs (ASDs) modulate synaptic and ion channel function to prevent abnormal hypersynchronous or excitatory activity arising in neuronal networks, but the relationship between ASDs with respect to their impact on network activity is poorly defined. In this study, we first investigated whether different ASD classes exert differential impact upon network activity, and we then sought to classify ASDs according to their impact on network activity.

METHODS

We used multielectrode arrays (MEAs) to record the network activity of cultured cortical neurons after applying ASDs from two classes: sodium channel blockers (SCBs) and γ-aminobutyric acid type A receptor-positive allosteric modulators (GABA PAMs). A two-dimensional representation of changes in network features was then derived, and the ability of this low-dimensional representation to classify ASDs with different molecular targets was assessed.

RESULTS

A two-dimensional representation of network features revealed a separation between the SCB and GABA PAM drug classes, and could classify several test compounds known to act through these molecular targets. Interestingly, several ASDs with novel targets, such as cannabidiol and retigabine, had closer similarity to the SCB class with respect to their impact upon network activity.

SIGNIFICANCE

These results demonstrate that the molecular target of two common classes of ASDs is reflected through characteristic changes in network activity of cultured neurons. Furthermore, a low-dimensional representation of network features can be used to infer an ASDs molecular target. This approach may allow for drug screening to be performed based on features extracted from MEA recordings.

A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy

Functional neuroimaging modalities have enhanced our understanding of juvenile myoclonic epilepsy (JME) underlying neural mechanisms. Due to its non-invasive, sensitive and analytical nature, functional magnetic resonance imaging (fMRI) provides valuable insights into relevant functional brain networks and their segregation and integration properties. We systematically reviewed the contribution of resting-state and task-based fMRI to the current understanding of the pathophysiology and the patterns of seizure propagation in JME Altogether, despite some discrepancies, functional findings suggest that corticothalamo-striato-cerebellar network along with default-mode network and salience network are the most affected networks in patients with JME. However, further studies are required to investigate the association between JME's main deficiencies, e.g., motor and cognitive deficiencies and fMRI findings. Moreover, simultaneous electroencephalography-fMRI (EEG-fMRI) studies indicate that alterations of these networks play a role in seizure modulation but fall short of identifying a causal relationship between altered functional properties and seizure propagation. This review highlights the complex pathophysiology of JME, which necessitates the design of more personalized diagnostic and therapeutic strategies in this group.

Role of L-Type Voltage-Gated Calcium Channels in Epileptiform Activity of Neurons

Epileptic discharges manifest in individual neurons as abnormal membrane potential fluctuations called paroxysmal depolarization shift (PDS). PDSs can combine into clusters that are accompanied by synchronous oscillations of the intracellular Ca²⁺ concentration ([Ca²⁺]_i) in neurons. Here, we investigate the contribution of L-type voltage-gated calcium channels (VGCC) to epileptiform activity induced in cultured hippocampal neurons by GABA(A)R antagonist, bicuculline. Using KCl-induced depolarization, we determined the optimal effective doses of the blockers. Dihydropyridines (nifedipine and isradipine) at concentrations ≤ 10 μM demonstrate greater selectivity than the blockers from other groups (phenylalkylamines and benzothiazepines). However, high doses of dihydropyridines evoke an irreversible increase in [Ca²⁺]_i in neurons and astrocytes. In turn, verapamil and diltiazem selectively block L-type VGCC in the range of 1–10 μM, whereas high doses of these drugs block other types of VGCC. We show that L-type VGCC blockade decreases the half-width and amplitude of bicuculline-induced [Ca²⁺]_i oscillations. We also observe a decrease in the number of PDSs in a cluster and cluster duration. However, the pattern of individual PDSs and the frequency of the cluster occurrence change insignificantly. Thus, our results demonstrate that L-type VGCC contributes to maintaining the required [Ca²⁺]_i level during oscillations, which appears to determine the number of PDSs in the cluster.

Patient-Specific Network Connectivity Combined With a Next Generation Neural Mass Model to Test Clinical Hypothesis of Seizure Propagation

Dynamics underlying epileptic seizures span multiple scales in space and time, therefore, understanding seizure mechanisms requires identifying the relations between seizure components within and across these scales, together with the analysis of their dynamical repertoire. In this view, mathematical models have been developed, ranging from single neuron to neural population. In this study, we consider a neural mass model able to exactly reproduce the dynamics of heterogeneous spiking neural networks. We combine mathematical modeling with structural information from non invasive brain imaging, thus building large-scale brain network models to explore emergent dynamics and test the clinical hypothesis. We provide a comprehensive study on the effect of external drives on neuronal networks exhibiting multistability, in order to investigate the role played by the neuroanatomical connectivity matrices in shaping the emergent dynamics. In particular, we systematically investigate the conditions under which the network displays a transition from a low activity regime to a high activity state, which we identify with a seizure-like event. This approach allows us to study the biophysical parameters and variables leading to multiple recruitment events at the network level. We further exploit topological network measures in order to explain the differences and the analogies among the subjects and their brain regions, in showing recruitment events at different parameter values. We demonstrate, along with the example of diffusion-weighted magnetic resonance imaging (dMRI) connectomes of 20 healthy subjects and 15 epileptic patients, that individual variations in structural connectivity, when linked with mathematical dynamic models, have the capacity to explain changes in spatiotemporal organization of brain dynamics, as observed in network-based brain disorders. In particular, for epileptic patients, by means of the integration of the clinical hypotheses on the epileptogenic zone (EZ), i.e., the local network where highly synchronous seizures originate, we have identified the sequence of recruitment events and discussed their links with the topological properties of the specific connectomes. The predictions made on the basis of the implemented set of exact mean-field equations turn out to be in line with the clinical pre-surgical evaluation on recruited secondary networks.

Low-frequency electrical stimulation reduces cortical excitability in the human brain

Effective seizure control remains challenging for about 30% of epilepsy patients who are resistant to present-day pharmacotherapy. Novel approaches that not only reduce the severity and frequency of seizures, but also have limited side effects are therefore desirable. Accordingly, various neuromodulation approaches such as cortical electrical stimulation have been implemented to reduce seizure burden; however, the underlying mechanisms are not completely understood. Given that the initiation and spread of epileptic seizures critically depend on cortical excitability, understanding the neuromodulatory effects of cortical electrical stimulation on cortical excitability levels is paramount. Based on observations that synchronization in the electrocorticogram closely tracks brain excitability level, the effects of low-frequency (1 Hz) intracranial brain stimulation on the levels of cortical phase synchronization before, during, and after 1 Hz electrical stimulation were assessed in twelve patients. Analysis of phase synchronization levels across three broad frequency bands (1-45 Hz, 55-95 Hz, and 105-195 Hz) revealed that in patients with stimulation sites in the neocortex, phase synchronization levels were significantly reduced within the 55-95 Hz and 105-195 Hz bands during post-stimulation intervals compared to baseline; this effect persisted for at least 30 min post-stimulation. Similar effects were observed when phase synchronization levels were examined in the classic frequency bands, whereby a significant reduction was found during the post-stimulation intervals in the alpha, beta, and gamma bands. The anatomical extent of these effects was then assessed. Analysis of the results from six patients with intracranial electrodes in both hemispheres indicated that reductions in phase synchronization in the 1-45 Hz and 55-95 Hz frequency ranges were more prominent in the stimulated hemisphere. Overall, these findings demonstrate that low-frequency electrical stimulation reduces phase synchronization and hence cortical excitability in the human brain. Low-frequency stimulation of the epileptic focus may therefore contribute to the prevention of impending epileptic seizures.

How Can an Na+ Channel Inhibitor Ameliorate Seizures in Lennox-Gastaut Syndrome?

OBJECTIVE

Lennox-Gastaut syndrome (LGS) is an epileptic encephalopathy frequently associated with multiple types of seizures. The classical Na⁺ channel inhibitors are in general ineffective against the seizures in LGS. Rufinamide is a new Na⁺ channel inhibitor, but approved for the treatment of LGS. This is not consistent with a choice of antiseizure drugs (ASDs) according to simplistic categorical grouping.

METHODS

The effect of rufinamide on the Na⁺ channel, cellular discharges, and seizure behaviors was quantitatively characterized in native neurons and mammalian models of epilepsy, and compared with the other Na⁺ channel inhibitors.

RESULTS

With a much faster binding rate to the inactivated Na⁺ channel than phenytoin, rufinamide is distinctively effective if the seizure discharges chiefly involve short bursts interspersed with hyperpolarized interburst intervals, exemplified by spike and wave discharges (SWDs) on electroencephalograms. Consistently, rufinamide, but not phenytoin, suppresses SWD-associated seizures in pentylenetetrazol or AY-9944 models, which recapitulate the major electrophysiological and behavioral manifestations in typical and atypical absence seizures, including LGS.

INTERPRETATION

Na⁺ channel inhibitors shall have sufficiently fast binding to exert an action during the short bursts and then suppress SWDs, in which cases rufinamide is superior. For the epileptiform discharges where the interburst intervals are not so hyperpolarized, phenytoin could be better because of the higher affinity. Na⁺ channel inhibitors with different binding kinetics and affinity to the inactivated channels may have different antiseizure scope. A rational choice of ASDs according to in-depth molecular pharmacology and the attributes of ictal discharges is advisable. ANN NEUROL 2021;89:1099-1113.

In silico model reveals the key role of GABA in KCNT1-epilepsy in infancy with migrating focal seizures

OBJECTIVE

This study was undertaken to investigate how gain of function (GOF) of slack channel due to a KCNT1 pathogenic variant induces abnormal neuronal cortical network activity and generates specific electroencephalographic (EEG) patterns of epilepsy in infancy with migrating focal seizures.

METHODS

We used detailed microscopic computational models of neurons to explore the impact of GOF of slack channel (explicitly coded) on each subtype of neurons and on a cortical micronetwork. Then, we adapted a thalamocortical macroscopic model considering results obtained in detailed models and immature properties related to epileptic brain in infancy. Finally, we compared simulated EEGs resulting from the macroscopic model with interictal and ictal patterns of affected individuals using our previously reported EEG markers.

RESULTS

The pathogenic variants of KCNT1 strongly decreased the firing rate properties of γ-aminobutyric acidergic (GABAergic) interneurons and, to a lesser extent, those of pyramidal cells. This change led to hyperexcitability with increased synchronization in a cortical micronetwork. At the macroscopic scale, introducing slack GOF effect resulted in epilepsy of infancy with migrating focal seizures (EIMFS) EEG interictal patterns. Increased excitation-to-inhibition ratio triggered seizure, but we had to add dynamic depolarizing GABA between somatostatin-positive interneurons and pyramidal cells to obtain migrating seizure. The simulated migrating seizures were close to EIMFS seizures, with similar values regarding the delay between the different ictal activities (one of the specific EEG markers of migrating focal seizures due to KCNT1 pathogenic variants).

SIGNIFICANCE

This study illustrates the interest of biomathematical models to explore pathophysiological mechanisms bridging the gap between the functional effect of gene pathogenic variants and specific EEG phenotype. Such models can be complementary to in vitro cellular and animal models. This multiscale approach provides an in silico framework that can be further used to identify candidate innovative therapies.

Antiepileptic drugs induce subcritical dynamics in human cortical networks

Cortical network functioning critically depends on finely tuned interactions to afford neuronal activity propagation over long distances while avoiding runaway excitation. This importance is highlighted by the pathological consequences and impaired performance resulting from aberrant network excitability in psychiatric and neurological diseases, such as epilepsy. Theory and experiment suggest that the control of activity propagation by network interactions can be adequately described by a branching process. This hypothesis is partially supported by strong evidence for balanced spatiotemporal dynamics observed in the cerebral cortex; however, evidence of a causal relationship between network interactions and cortex activity, as predicted by a branching process, is missing in humans. Here this cause-effect relationship is tested by monitoring cortex activity under systematic pharmacological reduction of cortical network interactions with antiepileptic drugs. This study reports that cortical activity cascades, presented by the propagating patterns of epileptic spikes, as well as temporal correlations decline precisely as predicted for a branching process. The results provide a missing link to the branching process theory of cortical network function with implications for understanding the foundations of cortical excitability and its monitoring in conditions like epilepsy.

Seizure prediction and intervention

Epilepsy treatment is challenging due to a lack of essential diagnostic tools, including methods for reliable seizure detection in the ambulatory setting, to assess seizure risk over time and to monitor treatment efficacy. This lack of objective diagnostics constitutes a significant barrier to better treatments, raises methodological concerns about the antiseizure medication evaluation process and, to patients, is a main issue contributing to the disease burden. Recent years have seen rapid progress towards better diagnostics that meet these needs of epilepsy patients and clinicians. Availability of comprehensive data and the rise of more powerful computational analysis methods have driven progress in this area. Here, we provide an overview on data- and theory-driven approaches aimed at identifying methods to reliably detect and forecast seizures as well as to monitor brain excitability and treatment efficacy in epilepsy. We provide a particular account on neural criticality, the hypothesis that cortical networks may be poised in a critical state at the boundary between different types of dynamics, and discuss its role in informing diagnostics to track cortex excitability and seizure risk in recent experiments. With the further expansion of digitalization in medicine, tele-medicine and long-term, ambulatory monitoring, these computationally based methods may gain more relevance in epilepsy in the future. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.

Unified analysis of global and focal aspects of absence epilepsy via neural field theory of the corticothalamic system

Absence epilepsy is characterized by a sudden paroxysmal loss of consciousness accompanied by oscillatory activity propagating over many brain areas. Although primary generalized absence seizures are supported by the global corticothalamic system, converging experimental evidence supports a focal theory of absence epilepsy. Here a physiology-based corticothalamic model is investigated with spatial heterogeneity due to focal epilepsy to unify global and focal aspects of absence epilepsy. Numeric and analytic calculations are employed to investigate the emergent spatiotemporal dynamics as well as their underlying dynamical mechanisms. They can be categorized into three scenarios: suppressed epilepsy, focal seizures, or generalized seizures, as summarized from a phase diagram vs focal width and characteristic axon range. The corresponding temporal frequencies and spatial extents of cortical waves in generalized seizures and focal seizures agree well with experimental observations of global and focal aspects of absence epilepsy, respectively. The emergence of the spatiotemporal dynamics corresponding to focal seizures provides a biophysical explanation of the temporally higher frequency but spatially more localized cortical waves observed in genetic rat models that display characteristics of human absence epilepsy. Predictions are also presented for further experimental test.

Diagnosis of seizures and encephalopathy using conventional EEG and amplitude integrated EEG

Seizures are more common in the neonatal period than at any other time of life, partly due to the relative hyperexcitability of the neonatal brain. Brain monitoring of sick neonates in the NICU using either conventional electroencephalography or amplitude integrated EEG is essential to accurately detect seizures. Treatment of seizures is important, as evidence increasingly indicates that seizures damage the brain in addition to that caused by the underlying etiology. Prompt treatment has been shown to reduce seizure burden with the potential to ameliorate seizure-mediated damage. Neonatal encephalopathy most commonly caused by a hypoxia-ischemia results in an alteration of mental status and problems such as seizures, hypotonia, apnea, and feeding difficulties. Confirmation of encephalopathy with EEG monitoring can act as an important adjunct to other investigations and the clinical examination, particularly when considering treatment strategies such as therapeutic hypothermia. Brain monitoring also provides useful early prognostic indicators to clinicians. Recent use of machine learning in algorithms to continuously monitor the neonatal EEG, detect seizures, and grade encephalopathy offers the exciting prospect of real-time decision support in the NICU in the very near future.

Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons

Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show here that a sufficient condition for this network bursting is the presence of an excitatory population of oscillatory neurons which displays spike-driven adaptation. We provide an analytic model to analyze network bursts generated by coupled adaptive exponential integrate-and-fire neurons. We show that, for strong synaptic coupling, intrinsically tonic spiking neurons evolve to reach a synchronized intermittent bursting state. The presence of inhibitory neurons or plastic synapses can then modulate this dynamics in many ways but is not necessary for its appearance. Thanks to a simple self-consistent equation, our model gives an intuitive and semi-quantitative tool to understand the bursting behavior. Furthermore, it suggests that after-hyperpolarization currents are sufficient to explain bursting termination. Through a thorough mapping between the theoretical parameters and ion-channel properties, we discuss the biological mechanisms that could be involved and the relevance of the explored parameter-space. Such an insight enables us to propose experimentally-testable predictions regarding how blocking fast, medium or slow after-hyperpolarization channels would affect the firing rate and burst duration, as well as the interburst interval.

Individual brain structure and modelling predict seizure propagation

See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions.

Control of Absence Seizures by the Thalamic Feed-Forward Inhibition

As a subtype of idiopathic generalized epilepsies, absence epilepsy is believed to be caused by pathological interactions within the corticothalamic (CT) system. Using a biophysical mean-field model of the CT system, we demonstrate here that the feed-forward inhibition (FFI) in thalamus, i.e., the pathway from the cerebral cortex (Ctx) to the thalamic reticular nucleus (TRN) and then to the specific relay nuclei (SRN) of thalamus that are also directly driven by the Ctx, may participate in controlling absence seizures. In particular, we show that increasing the excitatory Ctx-TRN coupling strength can significantly suppress typical electrical activities during absence seizures. Further, investigation demonstrates that the GABA_A- and GABA_B-mediated inhibitions in the TRN-SRN pathway perform combination roles in the regulation of absence seizures. Overall, these results may provide an insightful mechanistic understanding of how the thalamic FFI serves as an intrinsic regulator contributing to the control of absence seizures.

Lognormal firing rate distribution reveals prominent fluctuation-driven regime in spinal motor networks

When spinal circuits generate rhythmic movements it is important that the neuronal activity remains within stable bounds to avoid saturation and to preserve responsiveness. Here, we simultaneously record from hundreds of neurons in lumbar spinal circuits of turtles and establish the neuronal fraction that operates within either a 'mean-driven' or a 'fluctuation-driven' regime. Fluctuation-driven neurons have a 'supralinear' input-output curve, which enhances sensitivity, whereas the mean-driven regime reduces sensitivity. We find a rich diversity of firing rates across the neuronal population as reflected in a lognormal distribution and demonstrate that half of the neurons spend at least 50 % of the time in the 'fluctuation-driven' regime regardless of behavior. Because of the disparity in input-output properties for these two regimes, this fraction may reflect a fine trade-off between stability and sensitivity in order to maintain flexibility across behaviors.

Computational modeling of epileptiform activities in medial temporal lobe epilepsy combined with in vitro experiments

In this paper, we propose a comprehensive computational model that is able to reproduce three epileptiform activities. The model targets a hippocampal formation that is known to be an important lesion in medial temporal lobe epilepsy. It consists of four sub-networks consisting of excitatory and inhibitory neurons and well-known signal pathways, with consideration of propagation delay. The three epileptiform activities involve fast and slow interictal discharge and ictal discharge, and those activities can be induced in vitro by application of 4-Aminopyridine in entorhinal cortex combined hippocampal slices. We model the three epileptiform activities upon previously reported biological mechanisms and verify the simulation results by comparing them with in vitro experimental data obtained using a microelectrode array. We use the results of Granger causality analysis of recorded data to set input gains of signal pathways in the model, so that the compatibility between the computational and experimental models can be improved. The proposed model can be expanded to evaluate the suppression effect of epileptiform activities due to new treatment methods.

Rapid chain generation of interpostsynaptic functional LINKs can trigger seizure generation: Evidence for potential interconnections from pathology to behavior

The experimental finding that a paroxysmal depolarizing shift (PDS), an electrophysiological correlate of seizure activity, is a giant excitatory postsynaptic potential (EPSP) necessitates a mechanism for spatially summating several EPSPs at the level of the postsynaptic terminals (dendritic spines). In this context, we will examine reversible interpostsynaptic functional LINKs (IPLs), a proposed mechanism for inducing first-person virtual internal sensations of higher brain functions concurrent with triggering behavioral motor activity for possible pathological changes that may contribute to seizures. Pathological conditions can trigger a rapid chain generation and propagation of different forms of IPLs leading to seizure generation. A large number of observations made at different levels during both ictal and interictal periods are explained by this mechanism, including the tonic and clonic motor activity, different types of hallucinations, loss of consciousness, gradual worsening of cognitive abilities, a relationship with kindling (which uses an augmented stimulation protocol than that used for inducing long-term potentiation (LTP), which is an electrophysiological correlate of behavioral makers of internal sensation of memory), effect of a ketogenic diet on seizure prevention, dendritic spine loss in seizure disorders, neurodegenerative changes, and associated behavioral changes. The interconnectable nature of these findings is explained as loss of function states of a proposed normal functioning of the nervous system.

Intrinsic excitability measures track antiepileptic drug action and uncover increasing/decreasing excitability over the wake/sleep cycle

Pathological changes in excitability of cortical tissue commonly underlie the initiation and spread of seizure activity in patients suffering from epilepsy. Accordingly, monitoring excitability and controlling its degree using antiepileptic drugs (AEDs) is of prime importance for clinical care and treatment. To date, adequate measures of excitability and action of AEDs have been difficult to identify. Recent insights into ongoing cortical activity have identified global levels of phase synchronization as measures that characterize normal levels of excitability and quantify any deviation therefrom. Here, we explore the usefulness of these intrinsic measures to quantify cortical excitability in humans. First, we observe a correlation of such markers with stimulation-evoked responses suggesting them to be viable excitability measures based on ongoing activity. Second, we report a significant covariation with the level of AED load and a wake-dependent modulation. Our results indicate that excitability in epileptic networks is effectively reduced by AEDs and suggest the proposed markers as useful candidates to quantify excitability in routine clinical conditions overcoming the limitations of electrical or magnetic stimulation. The wake-dependent time course of these metrics suggests a homeostatic role of sleep, to rebalance cortical excitability.

The Effect of Spinal Cord Stimulation on Epileptic Seizures

OBJECTIVE

Spinal cord stimulation (SCS) has been applied to relieve chronic pain for decades. Recent studies suggested that SCS also might alleviate epileptic seizures, but the most effective stimulation parameters are not known. The objective of this work was to investigate the role of SCS frequency in alleviating spike-and-wave (SW) discharges induced in rats by pentylenetetrazole (PTZ) infusion.

MATERIALS AND METHODS

The SW discharges were induced in nine rats. An epidural electrode was placed in the spinal canal at the cervical level. SCS was delivered at four frequencies (30, 80, 130 and 180 Hz) and compared with control intervals without stimulation. The effect was evaluated by analyzing electrocorticographic and intracortical (IC) signals. The means of normalized SW spike power (mSP) and frequency (mSF) were derived from the IC recordings and used to estimate the seizure severity.

RESULTS

Compared with the control intervals, SCS conducted at 30 Hz significantly increased the mSP and mSF indicating an increase of the SW spiking activity; 80 Hz did not induce significant changes of the features. In contrast, 130- and 180-Hz SCS reduced both mSP and mSF significantly indicating a reduction of the SW spiking activity.

CONCLUSIONS

The present results showed that 130-Hz and 180-Hz SCS reduced the SWs power and frequency which may indicate an anticonvulsive effect of these SCS frequencies, whereas 30-Hz SCS induced the opposite effects and, therefore, may be proconvulsive.

Neocortical focus: experimental view

All brain normal or pathological activities occur in one of the states of vigilance: wake, slow-wave sleep, or REM sleep. Neocortical seizures preferentially occur during slow-wave sleep. We provide a description of neuronal behavior and mechanisms mediating such a behavior within neocortex taking place in natural states of vigilance as well as during seizures pointing to similarities and differences exhibited during sleep and seizures. A concept of epileptic focus is described using a model of cortical undercut, because in that model, the borders of the focus are well defined. In this model, as in other models of acquired epilepsy, the main factor altering excitability is deafferentation, which upregulates neuronal excitability that promotes generation of seizures. Periods of disfacilitation recorded during slow-wave sleep further upregulate neuronal excitability. It appears that the state of neurons and neuronal network in the epileptic focus produced by deafferentation are such that seizures cannot be generated there. Instead, seizures always start around the perimeter of the undercut cortex. Therefore, we define these areas as the seizure focus. In this zone, neuronal connectivity and excitability are moderately enhanced, lowering the threshold for seizure generation.

SWDreader: a wavelet-based algorithm using spectral phase to characterize spike-wave morphological variation in genetic models of absence epilepsy

BACKGROUND

Spike-wave discharges (SWD) found in neuroelectrical recordings are pathognomonic to absence epilepsy. The characteristic spike-wave morphology of the spike-wave complex (SWC) constituents of SWDs can be mathematically described by a subset of possible spectral power and phase values. Morlet wavelet transform (MWT) generates time-frequency representations well-suited to identifying this SWC-associated subset.

NEW METHOD

MWT decompositions of SWDs reveal spectral power concentrated at harmonic frequencies. The phase relationships underlying SWC morphology were identified by calculating the differences between phase values at SWD fundamental frequency from the 2nd, 3rd, and 4th harmonics, then using the three phase differences as coordinates to generate a density distribution in a {360°×360°×360°} phase difference space. Strain-specific density distributions were generated from SWDs of mice carrying the Gria4, Gabrg2, or Scn8a mutations to determine whether SWC morphological variants reliably mapped to the same regions of the distribution, and if distribution values could be used to detect SWD.

COMPARISON WITH EXISTING METHODS

To the best of our knowledge, this algorithm is the first to employ spectral phase to quantify SWC morphology, making it possible to computationally distinguish SWC morphological subtypes and detect SWDs.

RESULTS/CONCLUSIONS

Proof-of-concept testing of the SWDfinder algorithm shows: (1) a major pattern of variation in SWC morphology maps to one axis of the phase difference distribution, (2) variability between the strain-specific distributions reflects differences in the proportions of SWC subtypes generated during SWD, and (3) regularities in the spectral power and phase profiles of SWCs can be used to detect waveforms possessing SWC-like morphology.

Permittivity coupling across brain regions determines seizure recruitment in partial epilepsy

Brain regions generating seizures in patients with refractory partial epilepsy are referred to as the epileptogenic zone (EZ). During a seizure, paroxysmal activity is not restricted to the EZ, but may recruit other brain regions and propagate activity through large brain networks, which comprise brain regions that are not necessarily epileptogenic. The identification of the EZ is crucial for candidates for neurosurgery and requires unambiguous criteria that evaluate the degree of epileptogenicity of brain regions. To obtain such criteria and investigate the mechanisms of seizure recruitment and propagation, we develop a mathematical framework of coupled neural populations, which can interact via signaling through a slow permittivity variable. The permittivity variable captures effects evolving on slow timescales, including extracellular ionic concentrations and energy metabolism, with time delays of up to seconds as observed clinically. Our analyses provide a set of indices quantifying the degree of epileptogenicity and predict conditions, under which seizures propagate to nonepileptogenic brain regions, explaining the responses to intracerebral electric stimulation in epileptogenic and nonepileptogenic areas. In conjunction, our results provide guidance in the presurgical evaluation of epileptogenicity based on electrographic signatures in intracerebral electroencephalograms.

The influence of ion concentrations on the dynamic behavior of the Hodgkin-Huxley model-based cortical network

Action potentials (APs) in the form of very short pulses arise when the cell is excited by any internal or external stimulus exceeding the critical threshold of the membrane. During AP generation, the membrane potential completes its natural cycle through typical phases that can be formatted by ion channels, gates and ion concentrations, as well as the synaptic excitation rate. On the basis of the Hodgkin-Huxley cell model, a cortical network consistent with the real anatomic structure is realized with randomly interrelated small population of neurons to simulate a cerebral cortex segment. Using this model, we investigated the effects of Na(+) and K(+) ion concentrations on the outcome of this network in terms of regularity, phase locking, and synchronization. The results suggested that Na(+) concentration does slightly affect the amplitude but not considerably affects the other parameters specified by depolarization and repolarization. K(+) concentration significantly influences the form, regularity, and synchrony of the network-generated APs. No previous study dealing directly with the effects of both Na(+) and K(+) ion concentrations on regularity and synchronization of the simulated cortical network-generated APs, allowing for the comparison of results obtained using our methods, was encountered in the literature. The results, however, were consistent with those obtained through studies concerning resonance and synchronization from another perspective and with the information revealed through physiological and pharmacological experiments concerning changing ion concentrations or blocking ion channels. Our results demonstrated that the regularity and reliability of brain functions have a strong relationship with cellular ion concentrations, and suggested the management of the dynamic behavior of the cellular network with ion concentrations.

On the nature of seizure dynamics

Seizures can occur spontaneously and in a recurrent manner, which defines epilepsy; or they can be induced in a normal brain under a variety of conditions in most neuronal networks and species from flies to humans. Such universality raises the possibility that invariant properties exist that characterize seizures under different physiological and pathological conditions. Here, we analysed seizure dynamics mathematically and established a taxonomy of seizures based on first principles. For the predominant seizure class we developed a generic model called Epileptor. As an experimental model system, we used ictal-like discharges induced in vitro in mouse hippocampi. We show that only five state variables linked by integral-differential equations are sufficient to describe the onset, time course and offset of ictal-like discharges as well as their recurrence. Two state variables are responsible for generating rapid discharges (fast time scale), two for spike and wave events (intermediate time scale) and one for the control of time course, including the alternation between 'normal' and ictal periods (slow time scale). We propose that normal and ictal activities coexist: a separatrix acts as a barrier (or seizure threshold) between these states. Seizure onset is reached upon the collision of normal brain trajectories with the separatrix. We show theoretically and experimentally how a system can be pushed toward seizure under a wide variety of conditions. Within our experimental model, the onset and offset of ictal-like discharges are well-defined mathematical events: a saddle-node and homoclinic bifurcation, respectively. These bifurcations necessitate a baseline shift at onset and a logarithmic scaling of interspike intervals at offset. These predictions were not only confirmed in our in vitro experiments, but also for focal seizures recorded in different syndromes, brain regions and species (humans and zebrafish). Finally, we identified several possible biophysical parameters contributing to the five state variables in our model system. We show that these parameters apply to specific experimental conditions and propose that there exists a wide array of possible biophysical mechanisms for seizure genesis, while preserving central invariant properties. Epileptor and the seizure taxonomy will guide future modeling and translational research by identifying universal rules governing the initiation and termination of seizures and predicting the conditions necessary for those transitions.

GABA actions and ionic plasticity in epilepsy

Concepts of epilepsy, based on a simple change in neuronal excitation/inhibition balance, have subsided in face of recent insights into the large diversity and context-dependence of signaling mechanisms at the molecular, cellular and neuronal network level. GABAergic transmission exerts both seizure-suppressing and seizure-promoting actions. These two roles are prone to short-term and long-term alterations, evident both during epileptogenesis and during individual epileptiform events. The driving force of GABAergic currents is controlled by ion-regulatory molecules such as the neuronal K-Cl cotransporter KCC2 and cytosolic carbonic anhydrases. Accumulating evidence suggests that neuronal ion regulation is highly plastic, thereby contributing to the multiple roles ascribed to GABAergic signaling during epileptogenesis and epilepsy.

Transplantation of GABAergic Interneurons into the Neonatal Primary Visual Cortex Reduces Absence Seizures in Stargazer Mice

Epilepsies are debilitating neurological disorders characterized by repeated episodes of pathological seizure activity. Absence epilepsy (AE) is a poorly understood type of seizure with an estimated 30% of affected patients failing to respond to antiepileptic drugs. Thus, novel therapies are needed for the treatment of AE. A promising cell-based therapeutic strategy is centered on transplantation of embryonic neural stem cells from the medial ganglionic eminence (MGE), which give rise to gamma-aminobutyric acidergic (GABAergic) interneurons during embyronic development. Here, we used the Stargazer (Stg) mouse model of AE to map affected loci using c-Fos immunohistochemistry, which revealed intense seizure-induce activity in visual and somatosensory cortices. We report that transplantation of MGE cells into the primary visual cortex (V1) of Stg mice significantly reduces AE episodes and lowers mortality. Electrophysiological analysis in acute cortical slices of visual cortex demonstrated that Stg V1 neurons exhibit more pronounced increases in activity in response to a potassium-mediated excitability challenge than wildtypes (WT). The defective network activity in V1 was significantly altered following WT MGE transplantation, associating it with behavioral rescue of seizures in Stgs. Taken together, these findings present MGE grafting in the V1 as a possible clinical approach in the treatment of AE.

Intrinsically active and pacemaker neurons in pluripotent stem cell-derived neuronal populations

Neurons generated from pluripotent stem cells (PSCs) self-organize into functional neuronal assemblies in vitro, generating synchronous network activities. Intriguingly, PSC-derived neuronal assemblies develop spontaneous activities that are independent of external stimulation, suggesting the presence of thus far undetected intrinsically active neurons (IANs). Here, by using mouse embryonic stem cells, we provide evidence for the existence of IANs in PSC-neuronal networks based on extracellular multielectrode array and intracellular patch-clamp recordings. IANs remain active after pharmacological inhibition of fast synaptic communication and possess intrinsic mechanisms required for autonomous neuronal activity. PSC-derived IANs are functionally integrated in PSC-neuronal populations, contribute to synchronous network bursting, and exhibit pacemaker properties. The intrinsic activity and pacemaker properties of the neuronal subpopulation identified herein may be particularly relevant for interventions involving transplantation of neural tissues. IANs may be a key element in the regulation of the functional activity of grafted as well as preexisting host neuronal networks.

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PSC-neuronal assemblies harbor intrinsically active neurons (IANs)

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IANs remain active after inhibition of fast glutamatergic synaptic transmission

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Autonomous activities of PSC IANs depend on persistent active sodium currents

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PSC IANs contribute to concerted network activity and have pacemaker properties

Rational design of transcranial current stimulation (TCS) through mechanistic insights into cortical network dynamics

Transcranial current stimulation (TCS) is a promising method of non-invasive brain stimulation to modulate cortical network dynamics. Preliminary studies have demonstrated the ability of TCS to enhance cognition and reduce symptoms in both neurological and psychiatric illnesses. Despite the encouraging results of these studies, the mechanisms by which TCS and endogenous network dynamics interact remain poorly understood. Here, we propose that the development of the next generation of TCS paradigms with increased efficacy requires such mechanistic understanding of how weak electric fields (EFs) imposed by TCS interact with the nonlinear dynamics of large-scale cortical networks. We highlight key recent advances in the study of the interaction dynamics between TCS and cortical network activity. In particular, we illustrate an interdisciplinary approach that bridges neurobiology and electrical engineering. We discuss the use of (1) hybrid biological-electronic experimental approaches to disentangle feedback interactions; (2) large-scale computer simulations for the study of weak global perturbations imposed by TCS; and (3) optogenetic manipulations informed by dynamic systems theory to probe network dynamics. Together, we here provide the foundation for the use of rational design for the development of the next generation of TCS neurotherapeutics.

Mechanisms of seizure propagation in 2-dimensional centre-surround recurrent networks

Understanding how seizures spread throughout the brain is an important problem in the treatment of epilepsy, especially for implantable devices that aim to avert focal seizures before they spread to, and overwhelm, the rest of the brain. This paper presents an analysis of the speed of propagation in a computational model of seizure-like activity in a 2-dimensional recurrent network of integrate-and-fire neurons containing both excitatory and inhibitory populations and having a difference of Gaussians connectivity structure, an approximation to that observed in cerebral cortex. In the same computational model network, alternative mechanisms are explored in order to simulate the range of seizure-like activity propagation speeds (0.1-100 mm/s) observed in two animal-slice-based models of epilepsy: (1) low extracellular [Formula: see text], which creates excess excitation and (2) introduction of gamma-aminobutyric acid (GABA) antagonists, which reduce inhibition. Moreover, two alternative connection topologies are considered: excitation broader than inhibition, and inhibition broader than excitation. It was found that the empirically observed range of propagation velocities can be obtained for both connection topologies. For the case of the GABA antagonist model simulation, consistent with other studies, it was found that there is an effective threshold in the degree of inhibition below which waves begin to propagate. For the case of the low extracellular [Formula: see text] model simulation, it was found that activity-dependent reductions in inhibition provide a potential explanation for the emergence of slowly propagating waves. This was simulated as a depression of inhibitory synapses, but it may also be achieved by other mechanisms. This work provides a localised network understanding of the propagation of seizures in 2-dimensional centre-surround networks that can be tested empirically.

Dynamics of high-frequency synchronization during seizures

Pathological synchronization of neuronal firing is considered to be an inherent property of epileptic seizures. However, it remains unclear whether the synchrony increases for the high-frequency multiunit activity as well as for the local field potentials (LFPs). We present spatio-temporal analysis of synchronization during epileptiform activity using wide-band (up to 2,000 Hz) spectral analysis of multielectrode array recordings at up to 60 locations throughout the mouse hippocampus in vitro. Our study revealed a prominent structure of LFP profiles during epileptiform discharges, triggered by elevated extracellular potassium, with characteristic distribution of current sinks and sources with respect to anatomical structure. The cross-coherence of high-frequency activity (500-2,000 Hz) across channels was reduced during epileptic bursts compared with baseline activity and showed the opposite trend for lower frequencies. Furthermore, the magnitude of cross-coherence during epileptiform activity was dependent on distance: electrodes closer to the epileptic foci showed increased cross-coherence and electrodes further away showed reduced cross-coherence for high-frequency activity. These experimental observations were re-created and supported in a computational model. Our study suggests that different intrinsic and synaptic processes can mediate paroxysmal synchronization at low, medium, and high frequencies.

Neural mass activity, bifurcations, and epilepsy

In this letter, we propose a general framework for studying neural mass models defined by ordinary differential equations. By studying the bifurcations of the solutions to these equations and their sensitivity to noise, we establish an important relation, similar to a dictionary, between their behaviors and normal and pathological, especially epileptic, cortical patterns of activity. We then apply this framework to the analysis of two models that feature most phenomena of interest, the Jansen and Rit model, and the slightly more complex model recently proposed by Wendling and Chauvel. This model-based approach allows us to test various neurophysiological hypotheses on the origin of pathological cortical behaviors and investigate the effect of medication. We also study the effects of the stochastic nature of the inputs, which gives us clues about the origins of such important phenomena as interictal spikes, interictal bursts, and fast onset activity that are of particular relevance in epilepsy.

Ionic dynamics mediate spontaneous termination of seizures and postictal depression state

Epileptic seizures are characterized by periods of recurrent, highly synchronized activity that spontaneously terminates, followed by postictal state when neuronal activity is generally depressed. The mechanisms for spontaneous seizure termination and postictal depression remain poorly understood. Using a realistic computational model, we demonstrate that termination of seizure and postictal depression state may be mediated by dynamics of the intracellular and extracellular ion concentrations. Spontaneous termination was linked to progressive increase of intracellular sodium concentration mediated by activation of sodium channels during highly active epileptic state. In contrast, an increase of intracellular chloride concentration extended seizure duration making possible long-lasting epileptic activity characterized by multiple transitions between tonic and clonic states. After seizure termination, the extracellular potassium was reduced below baseline, resulting in postictal depression. Our study suggests that the coupled dynamics of sodium, potassium, and chloride ions play a critical role in the development and termination of seizures. Findings from this study could help identify novel therapeutics for seizure disorder.

A spatially extended model for macroscopic spike-wave discharges

Spike-wave discharges are a distinctive feature of epileptic seizures. So far, they have not been reported in spatially extended neural field models. We study a space-independent version of the Amari neural field model with two competing inhibitory populations. We show that this competition leads to robust spike-wave dynamics if the inhibitory populations operate on different time-scales. The spike-wave oscillations present a fold/homoclinic type bursting. From this result we predict parameters of the extended Amari system where spike-wave oscillations produce a spatially homogeneous pattern. We propose this mechanism as a prototype of macroscopic epileptic spike-wave discharges. To our knowledge this is the first example of robust spike-wave patterns in a spatially extended neural field model.

Dynamics of epileptiform activity in mouse hippocampal slices

Increase of the extracellular K⁺ concentration mediates seizure-like synchronized activities in vitro and was proposed to be one of the main factors underlying epileptogenesis in some types of seizures in vivo. While underlying biophysical mechanisms clearly involve cell depolarization and overall increase in excitability, it remains unknown what qualitative changes of the spatio-temporal network dynamics occur after extracellular K⁺ increase. In this study, we used multi-electrode recordings from mouse hippocampal slices to explore changes of the network activity during progressive increase of the extracellular K⁺ concentration. Our analysis revealed complex spatio-temporal evolution of epileptiform activity and demonstrated a sequence of state transitions from relatively simple network bursts into complex bursting, with multiple synchronized events within each burst. We describe these transitions as qualitative changes of the state attractors, constructed from experimental data, mediated by elevation of extracellular K⁺ concentration.

Intermittent spike-wave dynamics in a heterogeneous, spatially extended neural mass model

Generalised epileptic seizures are frequently accompanied by sudden, reversible transitions from low amplitude, irregular background activity to high amplitude, regular spike-wave discharges (SWD) in the EEG. The underlying mechanisms responsible for SWD generation and for the apparently spontaneous transitions to SWD and back again are still not fully understood. Specifically, the role of spatial cortico-cortical interactions in ictogenesis is not well studied. We present a macroscopic, neural mass model of a cortical column which includes two distinct time scales of inhibition. This model can produce both an oscillatory background and a pathological SWD rhythm. We demonstrate that coupling two of these cortical columns can lead to a bistability between out-of-phase, low amplitude background dynamics and in-phase, high amplitude SWD activity. Stimuli can cause state-dependent transitions from background into SWD. In an extended local area of cortex, spatial heterogeneities in a model parameter can lead to spontaneous reversible transitions from a desynchronised background to synchronous SWD due to intermittency. The deterministic model is therefore capable of producing absence seizure-like events without any time dependent adjustment of model parameters. The emergence of such mechanisms due to spatial coupling demonstrates the importance of spatial interactions in modelling ictal dynamics, and in the study of ictogenesis.

Activity-dependent intracellular chloride accumulation and diffusion controls GABA(A) receptor-mediated synaptic transmission

In the CNS, prolonged activation of GABA(A) receptors (GABA(A)Rs) has been shown to evoke biphasic postsynaptic responses, consisting of an initial hyperpolarization followed by a depolarization. A potential mechanism underlying the depolarization is an acute chloride (Cl(-)) accumulation resulting in a shift of the GABA(A) reversal potential (E(GABA)). The amount of GABA-evoked Cl(-) accumulation and accompanying depolarization depends on presynaptic and postsynaptic properties of GABAergic transmission, as well as on cellular morphology and regulation of Cl(-) intracellular concentration ([Cl(-)](i)). To analyze the influence of these factors on the Cl(-) and voltage behavior, we studied spatiotemporal dynamics of activity-dependent [Cl(-)](i) changes in multicompartmental models of hippocampal cells based on realistic morphological data. Simulated Cl(-) influx through GABA(A) Rs was able to exceed physiological Cl(-) extrusion rates thereby evoking HCO(3)(-) -dependent E(GABA) shift and depolarizing responses. Depolarizations were observed in spite of GABA(A) receptor desensitization. The amplitude of the depolarization was frequency-dependent and determined by intracellular Cl(-) accumulation. Changes in the dendritic diameter and in the speed of GABA clearance in the synaptic cleft were significant sources of depolarization variability. In morphologically reconstructed granule cells subjected to an intense GABAergic background activity, dendritic inhibition was more affected by accumulation of intracellular Cl(-) than somatic inhibition. Interestingly, E(GABA) changes induced by activation of a single dendritic synapse propagated beyond the site of Cl(-) influx and affected neighboring synapses. The simulations suggest that E(GABA) may differ even along a single dendrite supporting the idea that it is necessary to assign E(GABA) to a given GABAergic input and not to a given neuron.

The K+-Cl cotransporter KCC2 promotes GABAergic excitation in the mature rat hippocampus

GABAergic excitatory [K(+)](o) transients can be readily evoked in the mature rat hippocampus by intense activation of GABA(A) receptors (GABA(A)Rs). Here we show that these [K(+)](o) responses induced by high-frequency stimulation or GABA(A) agonist application are generated by the neuronal K(+)-Cl() cotransporter KCC2 and that the transporter-mediated KCl extrusion is critically dependent on the bicarbonate-driven accumulation of Cl() in pyramidal neurons. The mechanism underlying GABAergic [K(+)](o) transients was studied in CA1 stratum pyramidale using intracellular sharp microelectrodes and extracellular ion-sensitive microelectrodes. The evoked [K(+)](o) transients, as well as the associated afterdischarges, were strongly suppressed by 0.5-1 mm furosemide, a KCl cotransport inhibitor. Importantly, the GABA(A)R-mediated intrapyramidal accumulation of Cl(), as measured by monitoring the reversal potential of fused IPSPs, was unaffected by the drug. It was further confirmed that the reduction in the [K(+)](o) transients was not due to effects of furosemide on the Na(+)-dependent K(+)-Cl() cotransporter NKCC1 or on intraneuronal carbonic anhydrase activity. Blocking potassium channels by Ba(2+) enhanced [K(+)](o) transients whereas pyramidal cell depolarizations were attenuated in further agreement with a lack of contribution by channel-mediated K(+) efflux. The key role of the GABA(A)R channel-mediated anion fluxes in the generation of the [K(+)](o) transients was examined in experiments where bicarbonate was replaced with formate. This anion substitution had no significant effect on the rate of Cl() accumulation, [K(+)](o) response or afterdischarges. Our findings reveal a novel excitatory mode of action of KCC2 that can have substantial implications for the role of GABAergic transmission during ictal epileptiform activity.