Evidence of an inhibitory restraint of seizure activity in humans

Single unit action potentials in humans and the effect of seizure activity

Spike-sorting algorithms have been used to identify the firing patterns of isolated neurons ('single units') from implanted electrode recordings in patients undergoing assessment for epilepsy surgery, but we do not know their potential for providing helpful clinical information. It is important therefore to characterize both the stability of these recordings and also their context. A critical consideration is where the units are located with respect to the focus of the pathology. Recent analyses of neuronal spiking activity, recorded over extended spatial areas using microelectrode arrays, have demonstrated the importance of considering seizure activity in terms of two distinct spatial territories: the ictal core and penumbral territories. The pathological information in these two areas, however, is likely to be very different. We investigated, therefore, whether units could be followed reliably over prolonged periods of times in these two areas, including during seizure epochs. We isolated unit recordings from several hundred neurons from four patients undergoing video-telemetry monitoring for surgical evaluation of focal neocortical epilepsies. Unit stability could last in excess of 40 h, and across multiple seizures. A key finding was that in the penumbra, spike stereotypy was maintained even during the seizure. There was a net tendency towards increased penumbral firing during the seizure, although only a minority of units (10-20%) showed significant changes over the baseline period, and notably, these also included neurons showing significant reductions in firing. In contrast, within the ictal core territories, regions characterized by intense hypersynchronous multi-unit firing, our spike sorting algorithms failed as the units were incorporated into the seizure activity. No spike sorting was possible from that moment until the end of the seizure, but recovery of the spike shape was rapid following seizure termination: some units reappeared within tens of seconds of the end of the seizure, and over 80% reappeared within 3 min (τrecov = 104 ± 22 s). The recovery of the mean firing rate was close to pre-ictal levels also within this time frame, suggesting that the more protracted post-ictal state cannot be explained by persistent cellular neurophysiological dysfunction in either the penumbral or the core territories. These studies lay the foundation for future investigations of how these recordings may inform clinical practice.See Kimchi and Cash (doi:10.1093/awv264) for a scientific commentary on this article.

Unit Activity of Hippocampal Interneurons before Spontaneous Seizures in an Animal Model of Temporal Lobe Epilepsy

Mechanisms of seizure initiation are unclear. To evaluate the possible roles of inhibitory neurons, unit recordings were obtained in the dentate gyrus, CA3, CA1, and subiculum of epileptic pilocarpine-treated rats as they experienced spontaneous seizures. Most interneurons in the dentate gyrus, CA1, and subiculum increased their firing rate before seizures, and did so with significant consistency from seizure to seizure. Identification of CA1 interneuron subtypes based on firing characteristics during theta and sharp waves suggested that a parvalbumin-positive basket cell and putative bistratified cells, but not oriens lacunosum moleculare cells, were activated preictally. Preictal changes occurred much earlier than those described by most previous in vitro studies. Preictal activation of interneurons began earliest (>4 min before seizure onset), increased most, was most prevalent in the subiculum, and was minimal in CA3. Preictal inactivation of interneurons was most common in CA1 (27% of interneurons) and included a putative ivy cell and parvalbumin-positive basket cell. Increased or decreased preictal activity correlated with whether interneurons fired faster or slower, respectively, during theta activity. Theta waves were more likely to occur before seizure onset, and increased preictal firing of subicular interneurons correlated with theta activity. Preictal changes by other hippocampal interneurons were largely independent of theta waves. Within seconds of seizure onset, many interneurons displayed a brief pause in firing and a later, longer drop that was associated with reduced action potential amplitude. These findings suggest that many interneurons inactivate during seizures, most increase their activity preictally, but some fail to do so at the critical time before seizure onset.

Initiation, Propagation, and Termination of Partial (Focal) Seizures

The neurophysiological patterns that correlate with partial (focal) seizures are well defined in humans by standard electroencephalogram (EEG) and presurgical depth electrode recordings. Seizure patterns with similar features are reproduced in animal models of partial seizures and epilepsy. However, the network determinants that support interictal spikes, as well as the initiation, progression, and termination of seizures, are still elusive. Recent findings show that inhibitory networks are prominently involved at the onset of these seizures, and that extracellular changes in potassium contribute to initiate and sustain seizure progression. The end of a partial seizure correlates with an increase in network synchronization, which possibly involves both excitatory and inhibitory mechanisms.

Model-based estimation of intra-cortical connectivity using electrophysiological data

This paper provides a new method for model-based estimation of intra-cortical connectivity from electrophysiological measurements. A novel closed-form solution for the connectivity function of the Amari neural field equations is derived as a function of electrophysiological observations. The resultant intra-cortical connectivity estimate is driven from experimental data, but constrained by the mesoscopic neurodynamics that are encoded in the computational model. A demonstration is provided to show how the method can be used to image physiological mechanisms that govern cortical dynamics, which are normally hidden in clinical data from epilepsy patients. Accurate estimation performance is demonstrated using synthetic data. Following the computational testing, results from patient data are obtained that indicate a dominant increase in surround inhibition prior to seizure onset that subsides in the cases when the seizures spread.

The emergence of single neurons in clinical neurology

Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the CNS trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this Perspective, we focus on single-neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics.

Towards large-scale, human-based, mesoscopic neurotechnologies

Direct human brain recordings have transformed the scope of neuroscience in the past decade. Progress has relied upon currently available neurophysiological approaches in the context of patients undergoing neurosurgical procedures for medical treatment. While this setting has provided precious opportunities for scientific research, it also has presented significant constraints on the development of new neurotechnologies. A major challenge now is how to achieve high-resolution spatiotemporal neural recordings at a large scale. By narrowing the gap between current approaches, new directions tailored to the mesoscopic (intermediate) scale of resolution may overcome the barriers towards safe and reliable human-based neurotechnology development, with major implications for advancing both basic research and clinical translation.

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

OBJECTIVE

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

APPROACH

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

MAIN RESULTS

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

SIGNIFICANCE

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

Future of seizure prediction and intervention: closing the loop

The ultimate goal of epilepsy therapies is to provide seizure control for all patients while eliminating side effects. Improved specificity of intervention through on-demand approaches may overcome many of the limitations of current intervention strategies. This article reviews the progress in seizure prediction and detection, potential new therapies to provide improved specificity, and devices to achieve these ends. Specifically, we discuss (1) potential signal modalities and algorithms for seizure detection and prediction, (2) closed-loop intervention approaches, and (3) hardware for implementing these algorithms and interventions. Seizure prediction and therapies maximize efficacy, whereas minimizing side effects through improved specificity may represent the future of epilepsy treatments.

Seizure localization using ictal phase-locked high gamma: A retrospective surgical outcome study

OBJECTIVE

To determine whether resection of areas with evidence of intense, synchronized neural firing during seizures is an accurate indicator of postoperative outcome.

METHODS

Channels meeting phase-locked high gamma (PLHG) criteria were identified retrospectively from intracranial EEG recordings (102 seizures, 46 implantations, 45 patients). Extent of removal of both the seizure onset zone (SOZ) and PLHG was correlated with seizure outcome, classified as good (Engel class I or II, n = 32) or poor (Engel class III or IV, n = 13).

RESULTS

Patients with good outcomes had significantly greater proportions of both SOZ and the first 4 (early) PLHG sites resected. Improved outcome classification was noted with early PLHG, as measured by the area under the receiver operating characteristic curves (PLHG 0.79, SOZ 0.68) and by odds ratios for resections including at least 75% of sites identified by each measure (PLHG 9.7 [95% CI: 2.3-41.5], SOZ 5.3 [95% CI: 1.2-23.3]). Among patients with resection of at least 75% of the SOZ, 78% (n = 30) had good outcomes, increasing to 91% when the resection also included at least 75% of early PLHG sites (n = 22).

CONCLUSIONS

This study demonstrates the localizing value of early PLHG, which is comparable to that provided by the SOZ. Incorporation of PLHG into the clinical evaluation may improve surgical efficacy and help to focus resections on the most critical areas.

Microcircuits and their interactions in epilepsy: is the focus out of focus?

Epileptic seizures represent dysfunctional neural networks dominated by excessive and/or hypersynchronous activity. Recent progress in the field has outlined two concepts regarding mechanisms of seizure generation, or ictogenesis. First, all seizures, even those associated with what have historically been thought of as 'primary generalized' epilepsies, appear to originate in local microcircuits and then propagate from that initial ictogenic zone. Second, seizures propagate through cerebral networks and engage microcircuits in distal nodes, a process that can be weakened or even interrupted by suppressing activity in such nodes. We describe various microcircuit motifs, with a special emphasis on one that has been broadly implicated in several epilepsies: feed-forward inhibition. Furthermore, we discuss how, in the dynamic network in which seizures propagate, focusing on circuit 'choke points' remote from the initiation site might be as important as that of the initial dysfunction, the seizure 'focus'.

Synchronous inhibitory potentials precede seizure-like events in acute models of focal limbic seizures

Interictal spikes in models of focal seizures and epilepsies are sustained by the synchronous activation of glutamatergic and GABAergic networks. The nature of population spikes associated with seizure initiation (pre-ictal spikes; PSs) is still undetermined. We analyzed the networks involved in the generation of both interictal and PSs in acute models of limbic cortex ictogenesis induced by pharmacological manipulations. Simultaneous extracellular and intracellular recordings from both principal cells and interneurons were performed in the medial entorhinal cortex of the in vitro isolated guinea pig brain during focal interictal and ictal discharges induced in the limbic network by intracortical and brief arterial infusions of either bicuculline methiodide (BMI) or 4-aminopyridine (4AP). Local application of BMI in the entorhinal cortex did not induce seizure-like events (SLEs), but did generate periodic interictal spikes sensitive to the glutamatergic non-NMDA receptor antagonist DNQX. Unlike local applications, arterial perfusion of either BMI or 4AP induced focal limbic SLEs. PSs just ahead of SLE were associated with hyperpolarizing potentials coupled with a complete blockade of firing in principal cells and burst discharges in putative interneurons. Interictal population spikes recorded from principal neurons between two SLEs correlated with a depolarizing potential. We demonstrate in two models of acute limbic SLE that PS events are different from interictal spikes and are sustained by synchronous activation of inhibitory networks. Our findings support a prominent role of synchronous network inhibition in the initiation of a focal seizure.

Modeling focal epileptic activity in the Wilson-cowan model with depolarization block

Measurements of neuronal signals during human seizure activity and evoked epileptic activity in experimental models suggest that, in these pathological states, the individual nerve cells experience an activity driven depolarization block, i.e. they saturate. We examined the effect of such a saturation in the Wilson-Cowan formalism by adapting the nonlinear activation function; we substituted the commonly applied sigmoid for a Gaussian function. We discuss experimental recordings during a seizure that support this substitution. Next we perform a bifurcation analysis on the Wilson-Cowan model with a Gaussian activation function. The main effect is an additional stable equilibrium with high excitatory and low inhibitory activity. Analysis of coupled local networks then shows that such high activity can stay localized or spread. Specifically, in a spatial continuum we show a wavefront with inhibition leading followed by excitatory activity. We relate our model simulations to observations of spreading activity during seizures.

ELECTRONIC SUPPLEMENTARY MATERIAL

The online version of this article (doi:10.1186/s13408-015-0019-4) contains supplementary material 1.

Synaptic GABA release prevents GABA transporter type-1 reversal during excessive network activity

GABA transporters control extracellular GABA, which regulates the key aspects of neuronal and network behaviour. A prevailing view is that modest neuronal depolarization results in GABA transporter type-1 (GAT-1) reversal causing non-vesicular GABA release into the extracellular space during intense network activity. This has important implications for GABA uptake-targeting therapies. Here we combined a realistic kinetic model of GAT-1 with experimental measurements of tonic GABA_A receptor currents in ex vivo hippocampal slices to examine GAT-1 operation under varying network conditions. Our simulations predict that synaptic GABA release during network activity robustly prevents GAT-1 reversal. We test this in the 0 Mg²⁺ model of epileptiform discharges using slices from healthy and chronically epileptic rats and find that epileptiform activity is associated with increased synaptic GABA release and is not accompanied by GAT-1 reversal. We conclude that sustained efflux of GABA through GAT-1 is unlikely to occur during physiological or pathological network activity.

Membrane depolarization during increased neuronal activity as seen during epilepsy has been suggested to easily reverse neuronal GABA transporters. Here the authors use modelling and experimental data and challenge this view by showing that synaptic GABA release during excessive neuronal firing averts reversal of GABA uptake.

Preictal activity of subicular, CA1, and dentate gyrus principal neurons in the dorsal hippocampus before spontaneous seizures in a rat model of temporal lobe epilepsy

Previous studies suggest that spontaneous seizures in patients with temporal lobe epilepsy might be preceded by increased action potential firing of hippocampal neurons. Preictal activity is potentially important because it might provide new opportunities for predicting when a seizure is about to occur and insight into how spontaneous seizures are generated. We evaluated local field potentials and unit activity of single, putative excitatory neurons in the subiculum, CA1, CA3, and dentate gyrus of the dorsal hippocampus in epileptic pilocarpine-treated rats as they experienced spontaneous seizures. Average action potential firing rates of neurons in the subiculum, CA1, and dentate gyrus, but not CA3, increased significantly and progressively beginning 2-4 min before locally recorded spontaneous seizures. In the subiculum, CA1, and dentate gyrus, but not CA3, 41-57% of neurons displayed increased preictal activity with significant consistency across multiple seizures. Much of the increased preictal firing of neurons in the subiculum and CA1 correlated with preictal theta activity, whereas preictal firing of neurons in the dentate gyrus was independent of theta. In addition, some CA1 and dentate gyrus neurons displayed reduced firing rates preictally. These results reveal that different hippocampal subregions exhibit differences in the extent and potential underlying mechanisms of preictal activity. The finding of robust and significantly consistent preictal activity of subicular, CA1, and dentate neurons in the dorsal hippocampus, despite the likelihood that many seizures initiated in other brain regions, suggests the existence of a broader neuronal network whose activity changes minutes before spontaneous seizures initiate.

Epilepsy: new advances

Epilepsy affects 65 million people worldwide and entails a major burden in seizure-related disability, mortality, comorbidities, stigma, and costs. In the past decade, important advances have been made in the understanding of the pathophysiological mechanisms of the disease and factors affecting its prognosis. These advances have translated into new conceptual and operational definitions of epilepsy in addition to revised criteria and terminology for its diagnosis and classification. Although the number of available antiepileptic drugs has increased substantially during the past 20 years, about a third of patients remain resistant to medical treatment. Despite improved effectiveness of surgical procedures, with more than half of operated patients achieving long-term freedom from seizures, epilepsy surgery is still done in a small subset of drug-resistant patients. The lives of most people with epilepsy continue to be adversely affected by gaps in knowledge, diagnosis, treatment, advocacy, education, legislation, and research. Concerted actions to address these challenges are urgently needed.

Excitatory effects of parvalbumin-expressing interneurons maintain hippocampal epileptiform activity via synchronous afterdischarges

Epileptic seizures are characterized by periods of hypersynchronous, hyperexcitability within brain networks. Most seizures involve two stages: an initial tonic phase, followed by a longer clonic phase that is characterized by rhythmic bouts of synchronized network activity called afterdischarges (ADs). Here we investigate the cellular and network mechanisms underlying hippocampal ADs in an effort to understand how they maintain seizure activity. Using in vitro hippocampal slice models from rats and mice, we performed electrophysiological recordings from CA3 pyramidal neurons to monitor network activity and changes in GABAergic signaling during epileptiform activity. First, we show that the highest synchrony occurs during clonic ADs, consistent with the idea that specific circuit dynamics underlie this phase of the epileptiform activity. We then show that ADs require intact GABAergic synaptic transmission, which becomes excitatory as a result of a transient collapse in the chloride (Cl(-)) reversal potential. The depolarizing effects of GABA are strongest at the soma of pyramidal neurons, which implicates somatic-targeting interneurons in AD activity. To test this, we used optogenetic techniques to selectively control the activity of somatic-targeting parvalbumin-expressing (PV(+)) interneurons. Channelrhodopsin-2-mediated activation of PV(+) interneurons during the clonic phase generated excitatory GABAergic responses in pyramidal neurons, which were sufficient to elicit and entrain synchronous AD activity across the network. Finally, archaerhodopsin-mediated selective silencing of PV(+) interneurons reduced the occurrence of ADs during the clonic phase. Therefore, we propose that activity-dependent Cl(-) accumulation subverts the actions of PV(+) interneurons to perpetuate rather than terminate pathological network hyperexcitability during the clonic phase of seizures.

A biologically constrained, mathematical model of cortical wave propagation preceding seizure termination

Epilepsy--the condition of recurrent, unprovoked seizures--manifests in brain voltage activity with characteristic spatiotemporal patterns. These patterns include stereotyped semi-rhythmic activity produced by aggregate neuronal populations, and organized spatiotemporal phenomena, including waves. To assess these spatiotemporal patterns, we develop a mathematical model consistent with the observed neuronal population activity and determine analytically the parameter configurations that support traveling wave solutions. We then utilize high-density local field potential data recorded in vivo from human cortex preceding seizure termination from three patients to constrain the model parameters, and propose basic mechanisms that contribute to the observed traveling waves. We conclude that a relatively simple and abstract mathematical model consisting of localized interactions between excitatory cells with slow adaptation captures the quantitative features of wave propagation observed in the human local field potential preceding seizure termination.

Resolution revolution: epilepsy dynamics at the microscale

Our understanding of the neuronal mechanisms behind epilepsy dynamics has recently advanced due to the application of novel technologies, monitoring hundreds of neurons with single cell resolution. These developments have provided new theories on the relationship between physiological and pathological states, as well as common motifs for the propagation of paroxysmal activity. Although traditional electroencephalogram (EEG) recordings continue to describe normal network oscillations and abnormal epileptic events within and outside of the seizure focus, analysis of epilepsy dynamics at the microscale has found variability in the composition of macroscopically repetitive epileptiform events. These novel results point to heterogeneity in the underlying dynamics of the disorder, highlighting both the need and potential for more specific and targeted therapies.

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG-fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological-haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG-fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG-fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG-fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations.

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.

Mapping epileptic activity: sources or networks for the clinicians?

Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity.

Application of high-frequency Granger causality to analysis of epileptic seizures and surgical decision making

OBJECTIVE

In recent decades intracranial EEG (iEEG) recordings using increasing numbers of electrodes, higher sampling rates, and a variety of visual and quantitative analyses have indicated the presence of widespread, high frequency ictal and preictal oscillations (HFOs) associated with regions of seizure onset. Seizure freedom has been correlated with removal of brain regions generating pathologic HFOs. However, quantitative analysis of preictal HFOs has seldom been applied to the clinical problem of planning the surgical resection. We performed Granger causality (GC) analysis of iEEG recordings to analyze features of preictal seizure networks and to aid in surgical decision making.

METHODS

Ten retrospective and two prospective patients were chosen on the basis of individually stereotyped seizure patterns by visual criteria. Prospective patients were selected, additionally, for failure of those criteria to resolve apparent multilobar ictal onsets. iEEG was recorded at 500 or 1,000 Hz, using up to 128 surface and depth electrodes. Preictal and early ictal GC from individual electrodes was characterized by the strength of causal outflow, spatial distribution, and hierarchical causal relationships.

RESULTS

In all patients we found significant, widespread preictal GC network activity at peak frequencies from 80 to 250 Hz, beginning 2-42 s before visible electrographic onset. In the two prospective patients, GC source/sink comparisons supported the exclusion of early ictal regions that were not the dominant causal sources, and contributed to planning of more limited surgical resections. Both patients have a class 1 outcome at 1 year.

SIGNIFICANCE

GC analysis of iEEG has the potential to increase understanding of preictal network activity, and to help improve surgical outcomes in cases of otherwise ambiguous iEEG onset.

Neuronal ensemble synchrony during human focal seizures

Seizures are classically characterized as the expression of hypersynchronous neural activity, yet the true degree of synchrony in neuronal spiking (action potentials) during human seizures remains a fundamental question. We quantified the temporal precision of spike synchrony in ensembles of neocortical neurons during seizures in people with pharmacologically intractable epilepsy. Two seizure types were analyzed: those characterized by sustained gamma (∼40-60 Hz) local field potential (LFP) oscillations or by spike-wave complexes (SWCs; ∼3 Hz). Fine (<10 ms) temporal synchrony was rarely present during gamma-band seizures, where neuronal spiking remained highly irregular and asynchronous. In SWC seizures, phase locking of neuronal spiking to the SWC spike phase induced synchrony at a coarse 50-100 ms level. In addition, transient fine synchrony occurred primarily during the initial ∼20 ms period of the SWC spike phase and varied across subjects and seizures. Sporadic coherence events between neuronal population spike counts and LFPs were observed during SWC seizures in high (∼80 Hz) gamma-band and during high-frequency oscillations (∼130 Hz). Maximum entropy models of the joint neuronal spiking probability, constrained only on single neurons' nonstationary coarse spiking rates and local network activation, explained most of the fine synchrony in both seizure types. Our findings indicate that fine neuronal ensemble synchrony occurs mostly during SWC, not gamma-band, seizures, and primarily during the initial phase of SWC spikes. Furthermore, these fine synchrony events result mostly from transient increases in overall neuronal network spiking rates, rather than changes in precise spiking correlations between specific pairs of neurons.

Dynamic mechanisms of neocortical focal seizure onset

Recent experimental and clinical studies have provided diverse insight into the mechanisms of human focal seizure initiation and propagation. Often these findings exist at different scales of observation, and are not reconciled into a common understanding. Here we develop a new, multiscale mathematical model of cortical electric activity with realistic mesoscopic connectivity. Relating the model dynamics to experimental and clinical findings leads us to propose three classes of dynamical mechanisms for the onset of focal seizures in a unified framework. These three classes are: (i) globally induced focal seizures; (ii) globally supported focal seizures; (iii) locally induced focal seizures. Using model simulations we illustrate these onset mechanisms and show how the three classes can be distinguished. Specifically, we find that although all focal seizures typically appear to arise from localised tissue, the mechanisms of onset could be due to either localised processes or processes on a larger spatial scale. We conclude that although focal seizures might have different patient-specific aetiologies and electrographic signatures, our model suggests that dynamically they can still be classified in a clinically useful way. Additionally, this novel classification according to the dynamical mechanisms is able to resolve some of the previously conflicting experimental and clinical findings.

According to the WHO fact sheet, epilepsy is a neurological disorder affecting about 50 million people worldwide. Even today 30% of epilepsy patients do not respond well to drug therapies. Neocortical focal epilepsy is a particular type of epilepsy in which drug treatments fail and surgical success rate is low. Hence, research is essential to improve the treatment of this type of epilepsy. Recent advances in brain recording methods have led to new observations regarding the nature of neocortical focal epilepsy. However, some of the observations appear to be contradictory. Here, we develop a computational modelling framework that can explain the different observations as different aspects of possible mechanisms that can all lead to seizure onset. Specifically, we classify three main conditions under which focal seizure onset can happen. This classification is clinically important, as our model predicts different treatment strategies for each class. We conclude that focal seizures are diverse, not only in their electrographic appearance and aetiology, but also in their onset mechanism. Combined multiscale recordings as well as stimulation studies are required to elucidate the onset mechanism in each patient. Our work provides the first classification of possible onset mechanism.

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

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

Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX): comparing multi-electrode recordings from simulated and biological mammalian cortical tissue

Local field potentials (LFPs) sampled with extracellular electrodes are frequently used as a measure of population neuronal activity. However, relating such measurements to underlying neuronal behaviour and connectivity is non-trivial. To help study this link, we developed the Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX). We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons. We then developed VERTEX as an easy-to-use Matlab tool for simulating LFPs from large populations (>100,000 neurons). A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue. Our model, with virtual electrodes placed anywhere in 3D, allows direct comparisons with the in vitro recording setup. We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.

Coupling between gamma-band power and cerebral blood volume during recurrent acute neocortical seizures

Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using non-invasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (>30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2-dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25-90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue.

Dynamics of regional brain activity in epilepsy: a cross-disciplinary study on both intracranial and scalp-recorded epileptic seizures

OBJECTIVE

Recent cross-disciplinary literature suggests a dynamical analogy between earthquakes and epileptic seizures. This study extends the focus of inquiry for the applicability of models for earthquake dynamics to examine both scalp-recorded and intracranial electroencephalogram recordings related to epileptic seizures.

APPROACH

First, we provide an updated definition of the electric event in terms of magnitude and we focus on the applicability of (i) a model for earthquake dynamics, rooted in a nonextensive Tsallis framework, (ii) the traditional Gutenberg and Richter law and (iii) an alternative method for the magnitude-frequency relation for earthquakes. Second, we apply spatiotemporal analysis in terms of nonextensive statistical physics and we further examine the behavior of the parameters included in the nonextensive formula for both types of electroencephalogram recordings under study.

MAIN RESULTS

We confirm the previously observed power-law distribution, showing that the nonextensive formula can adequately describe the sequences of electric events included in both types of electroencephalogram recordings. We also show the intermittent behavior of the epileptic seizure cycle which is analogous to the earthquake cycles and we provide evidence of self-affinity of the regional electroencephalogram epileptic seizure activity.

SIGNIFICANCE

This study may provide a framework for the analysis and interpretation of epileptic brain activity and other biological phenomena with similar underlying dynamical mechanisms.

Oxygen and seizure dynamics: I. Experiments

We utilized a novel ratiometric nanoquantum dot fluorescence resonance energy transfer (NQD-FRET) optical sensor to quantitatively measure oxygen dynamics from single cell microdomains during hypoxic episodes as well as during 4-aminopyridine (4-AP)-induced spontaneous seizure-like events in rat hippocampal slices. Coupling oxygen sensing with electrical recordings, we found the greatest reduction in the O2 concentration ([O2]) in the densely packed cell body stratum (st.) pyramidale layer of the CA1 and differential layer-specific O2 dynamics between the st. pyramidale and st. oriens layers. These hypoxic decrements occurred up to several seconds before seizure onset could be electrically measured extracellularly. Without 4-AP, we quantified a narrow range of [O2], similar to the endogenous hypoxia found before epileptiform activity, which permits a quiescent network to enter into a seizure-like state. We demonstrated layer-specific patterns of O2 utilization accompanying layer-specific neuronal interplay in seizure. None of the oxygen overshoot artifacts seen with polarographic measurement techniques were observed. We therefore conclude that endogenously generated hypoxia may be more than just a consequence of increased cellular excitability but an influential and critical factor for orchestrating network dynamics associated with epileptiform activity.

Imaging preictal hemodynamic changes in neocortical epilepsy

OBJECT

The ability to predict seizure occurrence is extremely important to trigger abortive therapies and to warn patients and their caregivers. Optical imaging of hemodynamic parameters such as blood flow, blood volume, and tissue and hemoglobin oxygenation has already been shown to successfully localize epileptic events with high spatial and temporal resolution. The ability to actually predict seizure occurrence using hemodynamic parameters is less well explored.

METHODS

In this article, the authors critically review data from the literature on neocortical epilepsy and optical imaging, and they discuss the preictal hemodynamic changes and their application in neurosurgery.

RESULTS

Recent optical mapping studies have demonstrated preictal hemodynamic changes in both human and animal neocortex.

CONCLUSIONS

Optical measurements of blood flow and oxygenation may become increasingly important for predicting and localizing epileptic events. The ability to successfully predict ictal onsets may be useful to trigger closed-loop abortive therapies.

Determination of seizure propagation across microdomains using spectral measures of causality

The use of microelectrode arrays to measure electrical activity from the surface of the brain is increasingly being investigated as a means to improve seizure focus localization. In this work, we determine seizure propagation across microdomains sampled by such microelectrode arrays and compare the results using two widely used frequency domain measures of causality, namely the partial directed coherence and the directed direct transfer function. We show that these two measures produce very similar propagation patterns for simulated microelectrode activity over a relatively smaller number of channels. However as the number of channels increases, partial directed coherence produces better estimates of the actual propagation pattern. Additionally, we apply these two measures to determine seizure propagation over microelectrode arrays measured from a patient undergoing intracranial monitoring for seizure focus localization and find very similar patterns which also agree with a threshold based reconstruction during seizure onset.

What is a seizure network? Long-range network consequences of focal seizures

What defines the spatial and temporal boundaries of seizure activity in brain networks? To fully answer this question a precise and quantitative definition of seizures is needed, which unfortunately remains elusive. Nevertheless, it is possible to ask under conditions where clearly divergent patterns of activity occur in large-scale brain networks whether certain activity patterns are part of the seizure while others are not. Here we examine brain network activity during focal limbic seizures, including diverse regions such as the hippocampus, subcortical arousal systems and fronto-parietal association cortex. Based on work from patients and from animal models we describe a characteristic pattern of intense increases in neuronal firing, cerebral blood flow, cerebral blood volume, blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI) signals and cerebral metabolic rate of oxygen consumption in the hippocampus during focal limbic seizures. Similar increases are seen in certain closely linked subcortical structures such as the lateral septal nuclei and anterior hypothalamus, which contain inhibitory neurons. In marked contrast, decreases in all of these parameters are seen in the subcortical arousal systems of the upper brainstem and intralaminar thalamus, as well as in the fronto-parietal association cortex. We propose that the seizure proper can be defined as regions showing intense increases, while those areas showing opposite changes are inhibited by the seizure network and constitute long-range network consequences beyond the seizure itself. Importantly, the fronto-parietal cortex shows sleep-like slow wave activity and depressed metabolism under these conditions, associated with impaired consciousness. Understanding which brain networks are directly involved in seizures versus which sustain secondary consequences can provide new insights into the mechanisms of brain dysfunction in epilepsy, hopefully leading to innovative treatment approaches.

Epileptic focus and alteration of metabolism

Epilepsy is one of the most common neurologic disorders affecting a substantial part of the population worldwide. Epileptic seizures represent the situation of increased neuronal activity associated with the enhanced demands for sufficient energy supply. For that purpose, very efficient regulatory mechanisms have to operate to ensure that cerebral blood flow, delivery of oxygen, and nutrients are continuously adapted to the local metabolic needs. The sophisticated regulation has to function in concert at several levels (systemic, tissue, cellular, and subcellular). Particularly, mitochondria play a key role not only in the energy production, but they are also central to many other processes including those leading to neuronal death. Impairment of any of the involved pathways can result in serious functional alterations, neurodegeneration, and potentially in epileptogenesis. The present review will address some of the important issues concerning vascular and metabolic changes in pathophysiology of epilepsy.

Mechanisms of ictogenesis

Epilepsy is a paroxysmal condition characterized by repeated transient seizures separated by longer interictal periods. Ictogenesis describes the processes of transition from the interictal state to a seizure. The processes include a preictal state, with specific clinical signs and a distinct electrophysiology which may provide opportunities to anticipate, or even prevent, seizures. Biological mechanisms of ictogenesis remain poorly understood and may vary between conditions/syndromes. We review here ictogenic processes including the involvement of pyramidal cells, interneurons and astrocytes, GABAergic and glutamatergic signaling, and ionic perturbations. Our review suggests that specific excitatory influences at the transition to an ictal event include (1) GABA receptor activation with a neuronal Cl(-) load and (2) a transient increase in external K(+).

Field effects and ictal synchronization: insights from in homine observations

It has been well established in animal models that electrical fields generated during inter-ictal and ictal discharges are strong enough in intensity to influence action potential firing threshold and synchronization. We discuss recently published data from microelectrode array recordings of human neocortical seizures and speculate about the possible role of field effects in neuronal synchronization. We have identified two distinct seizure territories that cannot be easily distinguished by traditional EEG analysis. The ictal core exhibits synchronized neuronal burst firing, while the surrounding ictal penumbra exhibits asynchronous and relatively sparse neuronal activity. In the ictal core large amplitude rhythmic ictal discharges produce large electric fields that correspond with highly synchronous neuronal firing. In the penumbra rhythmic ictal discharges are smaller in amplitude, but large enough to influence spike timing, yet neuronal synchrony is not observed. These in homine observations are in accord with decades of animal studies supporting a role of field effects in neuronal synchronization during seizures, yet also highlight how field effects may be negated in the presence of strong synaptic inhibition in the penumbra.

Ictal high frequency oscillations distinguish two types of seizure territories in humans

High frequency oscillations have been proposed as a clinically useful biomarker of seizure generating sites. We used a unique set of human microelectrode array recordings (four patients, 10 seizures), in which propagating seizure wavefronts could be readily identified, to investigate the basis of ictal high frequency activity at the cortical (subdural) surface. Sustained, repetitive transient increases in high gamma (80-150 Hz) amplitude, phase-locked to the low-frequency (1-25 Hz) ictal rhythm, correlated with strong multi-unit firing bursts synchronized across the core territory of the seizure. These repetitive high frequency oscillations were seen in recordings from subdural electrodes adjacent to the microelectrode array several seconds after seizure onset, following ictal wavefront passage. Conversely, microelectrode recordings demonstrating only low-level, heterogeneous neural firing correlated with a lack of high frequency oscillations in adjacent subdural recording sites, despite the presence of a strong low-frequency signature. Previously, we reported that this pattern indicates a failure of the seizure to invade the area, because of a feedforward inhibitory veto mechanism. Because multi-unit firing rate and high gamma amplitude are closely related, high frequency oscillations can be used as a surrogate marker to distinguish the core seizure territory from the surrounding penumbra. We developed an efficient measure to detect delayed-onset, sustained ictal high frequency oscillations based on cross-frequency coupling between high gamma amplitude and the low-frequency (1-25 Hz) ictal rhythm. When applied to the broader subdural recording, this measure consistently predicted the timing or failure of ictal invasion, and revealed a surprisingly small and slowly spreading seizure core surrounded by a far larger penumbral territory. Our findings thus establish an underlying neural mechanism for delayed-onset, sustained ictal high frequency oscillations, and provide a practical, efficient method for using them to identify the small ictal core regions. Our observations suggest that it may be possible to reduce substantially the extent of cortical resections in epilepsy surgery procedures without compromising seizure control.

Emergence of metastable state dynamics in interconnected cortical networks with propagation delays

The importance of the large number of thin-diameter and unmyelinated axons that connect different cortical areas is unknown. The pronounced propagation delays in these axons may prevent synchronization of cortical networks and therefore hinder efficient information integration and processing. Yet, such global information integration across cortical areas is vital for higher cognitive function. We hypothesized that delays in communication between cortical areas can disrupt synchronization and therefore enhance the set of activity trajectories and computations interconnected networks can perform. To evaluate this hypothesis, we studied the effect of long-range cortical projections with propagation delays in interconnected large-scale cortical networks that exhibited spontaneous rhythmic activity. Long-range connections with delays caused the emergence of metastable, spatio-temporally distinct activity states between which the networks spontaneously transitioned. Interestingly, the observed activity patterns correspond to macroscopic network dynamics such as globally synchronized activity, propagating wave fronts, and spiral waves that have been previously observed in neurophysiological recordings from humans and animal models. Transient perturbations with simulated transcranial alternating current stimulation (tACS) confirmed the multistability of the interconnected networks by switching the networks between these metastable states. Our model thus proposes that slower long-range connections enrich the landscape of activity states and represent a parsimonious mechanism for the emergence of multistability in cortical networks. These results further provide a mechanistic link between the known deficits in connectivity and cortical state dynamics in neuropsychiatric illnesses such as schizophrenia and autism, as well as suggest non-invasive brain stimulation as an effective treatment for these illnesses.

The contribution of synaptic location to inhibitory gain control in pyramidal cells

THE ACTIVITY OF PYRAMIDAL CELLS IS CONTROLLED BY TWO OPPOSING FORCES: synaptic inhibition and synaptic excitation. Interestingly, these synaptic inputs are not distributed evenly across the dendritic trees of cortical pyramidal cells. Excitatory synapses are densely packed along only the more peripheral dendrites, but are absent from the proximal stems and the soma. In contrast, inhibitory synapses are located throughout the dendritic tree, the soma, and the axon initial segment. Thus both excitatory and inhibitory inputs exist on the peripheral dendritic tree, while the proximal segments only receive inhibition. The functional consequences of this uneven organization remain unclear. We used both optogenetics and dynamic patch clamp techniques to simulate excitatory synaptic conductances in pyramidal cells, and then assessed how their firing output is modulated by gamma-amino-butyric acid type A (GABAA) receptor activation at different regions of the somatodendritic axis. We report here that activation of GABAA receptor on the same dendritic compartment as excitatory inputs causes a rightwards shift in the function relating firing rate to excitatory conductance (the input-output function). In contrast, GABAA receptor activation proximal to the soma causes both a rightwards shift and also a reduction in the maximal firing rate. The experimental data are well reproduced in a simple, four compartmental model of a neuron with inhibition either on the same compartment, or proximal, to the excitatory drive.

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.

Neural circuit mechanisms of post-traumatic epilepsy

Traumatic brain injury (TBI) greatly increases the risk for a number of mental health problems and is one of the most common causes of medically intractable epilepsy in humans. Several models of TBI have been developed to investigate the relationship between trauma, seizures, and epilepsy-related changes in neural circuit function. These studies have shown that the brain initiates immediate neuronal and glial responses following an injury, usually leading to significant cell loss in areas of the injured brain. Over time, long-term changes in the organization of neural circuits, particularly in neocortex and hippocampus, lead to an imbalance between excitatory and inhibitory neurotransmission and increased risk for spontaneous seizures. These include alterations to inhibitory interneurons and formation of new, excessive recurrent excitatory synaptic connectivity. Here, we review in vivo models of TBI as well as key cellular mechanisms of synaptic reorganization associated with post-traumatic epilepsy (PTE). The potential role of inflammation and increased blood-brain barrier permeability in the pathophysiology of PTE is also discussed. A better understanding of mechanisms that promote the generation of epileptic activity versus those that promote compensatory brain repair and functional recovery should aid development of successful new therapies for PTE.

GABA progenitors grafted into the adult epileptic brain control seizures and abnormal behavior

Impaired GABA-mediated neurotransmission has been implicated in many neurologic diseases, including epilepsy, intellectual disability and psychiatric disorders. We found that inhibitory neuron transplantation into the hippocampus of adult mice with confirmed epilepsy at the time of grafting markedly reduced the occurrence of electrographic seizures and restored behavioral deficits in spatial learning, hyperactivity and the aggressive response to handling. In the recipient brain, GABA progenitors migrated up to 1,500 μm from the injection site, expressed genes and proteins characteristic for interneurons, differentiated into functional inhibitory neurons and received excitatory synaptic input. In contrast with hippocampus, cell grafts into basolateral amygdala rescued the hyperactivity deficit, but did not alter seizure activity or other abnormal behaviors. Our results highlight a critical role for interneurons in epilepsy and suggest that interneuron cell transplantation is a powerful approach to halting seizures and rescuing accompanying deficits in severely epileptic mice.