Single-neuron dynamics in human focal epilepsy

Direct Imaging of Hippocampal Epileptiform Calcium Motifs Following Kainic Acid Administration in Freely Behaving Mice

Prolonged exposure to abnormally high calcium concentrations is thought to be a core mechanism underlying hippocampal damage in epileptic patients; however, no prior study has characterized calcium activity during seizures in the live, intact hippocampus. We have directly investigated this possibility by combining whole-brain electroencephalographic (EEG) measurements with microendoscopic calcium imaging of pyramidal cells in the CA1 hippocampal region of freely behaving mice treated with the pro-convulsant kainic acid (KA). We observed that KA administration led to systematic patterns of epileptiform calcium activity: a series of large-scale, intensifying flashes of increased calcium fluorescence concurrent with a cluster of low-amplitude EEG waveforms. This was accompanied by a steady increase in cellular calcium levels (>5 fold increase relative to the baseline), followed by an intense spreading calcium wave characterized by a 218% increase in global mean intensity of calcium fluorescence (n = 8, range [114–349%], p < 10⁻⁴; t-test). The wave had no consistent EEG phenotype and occurred before the onset of motor convulsions. Similar changes in calcium activity were also observed in animals treated with 2 different proconvulsant agents, N-methyl-D-aspartate (NMDA) and pentylenetetrazol (PTZ), suggesting the measured changes in calcium dynamics are a signature of seizure activity rather than a KA-specific pathology. Additionally, despite reducing the behavioral severity of KA-induced seizures, the anticonvulsant drug valproate (VA, 300 mg/kg) did not modify the observed abnormalities in calcium dynamics. These results confirm the presence of pathological calcium activity preceding convulsive motor seizures and support calcium as a candidate signaling molecule in a pathway connecting seizures to subsequent cellular damage. Integrating in vivo calcium imaging with traditional assessment of seizures could potentially increase translatability of pharmacological intervention, leading to novel drug screening paradigms and therapeutics designed to target and abolish abnormal patterns of both electrical and calcium excitation.

Activation of specific neuronal networks leads to different seizure onset types

OBJECTIVE

Ictal events occurring in temporal lobe epilepsy patients and in experimental models mimicking this neurological disorder can be classified, based on their onset pattern, into low-voltage, fast versus hypersynchronous onset seizures. It has been suggested that the low-voltage, fast onset pattern is mainly contributed by interneuronal (γ-aminobutyric acidergic) signaling, whereas the hypersynchronous onset involves the activation of principal (glutamatergic) cells.

METHODS

Here, we tested this hypothesis using the optogenetic control of parvalbumin-positive or somatostatin-positive interneurons and of calmodulin-dependent, protein kinase-positive, principal cells in the mouse entorhinal cortex in the in vitro 4-aminopyridine model of epileptiform synchronization.

RESULTS

We found that during 4-aminopyridine application, both spontaneous seizure-like events and those induced by optogenetic activation of interneurons displayed low-voltage, fast onset patterns that were associated with a higher occurrence of ripples than of fast ripples. In contrast, seizures induced by the optogenetic activation of principal cells had a hypersynchronous onset pattern with fast ripple rates that were higher than those of ripples.

INTERPRETATION

Our results firmly establish that under a similar experimental condition (ie, bath application of 4-aminopyridine), the initiation of low-voltage, fast and of hypersynchronous onset seizures in the entorhinal cortex depends on the preponderant involvement of interneuronal and principal cell networks, respectively.

Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures

OBJECTIVE

Current mapping of epileptic networks in patients prior to epilepsy surgery utilizes electrode arrays with sparse spatial sampling (∼1.0 cm inter-electrode spacing). Recent research demonstrates that sub-millimeter, cortical-column-scale domains have a role in seizure generation that may be clinically significant. We use high-resolution, active, flexible surface electrode arrays with 500 μm inter-electrode spacing to explore epileptiform local field potential (LFP) spike propagation patterns in two dimensions recorded from subdural micro-electrocorticographic signals in vivo in cat. In this study, we aimed to develop methods to quantitatively characterize the spatiotemporal dynamics of epileptiform activity at high-resolution.

APPROACH

We topically administered a GABA-antagonist, picrotoxin, to induce acute neocortical epileptiform activity leading up to discrete electrographic seizures. We extracted features from LFP spikes to characterize spatiotemporal patterns in these events. We then tested the hypothesis that two-dimensional spike patterns during seizures were different from those between seizures.

MAIN RESULTS

We showed that spatially correlated events can be used to distinguish ictal versus interictal spikes.

SIGNIFICANCE

We conclude that sub-millimeter-scale spatiotemporal spike patterns reveal network dynamics that are invisible to standard clinical recordings and contain information related to seizure-state.

The Long and Winding Road to Gamma-Amino-Butyric Acid as Neurotransmitter

This review centers on the discoveries made during more than six decades of neuroscience research on the role of gamma-amino-butyric acid (GABA) as neurotransmitter. In doing so, special emphasis is directed to the significant involvement of Canadian scientists in these advances. Starting with the early studies that established GABA as an inhibitory neurotransmitter at central synapses, we summarize the results pointing at the GABA receptor as a drug target as well as more recent evidence showing that GABAA receptor signaling plays a surprisingly active role in neuronal network synchronization, both during development and in the adult brain. Finally, we briefly address the involvement of GABA in neurological conditions that encompass epileptic disorders and mental retardation.

Interneurons spark seizure-like activity in the entorhinal cortex

Excessive neuronal synchronization is presumably involved in epileptiform synchronization. However, the respective roles played by interneurons (GABAergic) and principal (glutamatergic) cells during interictal and ictal discharges remain unclear. Here, we employed tetrode wire recordings to establish the involvement of these two cell types in 4-aminopyridine-induced interictal- and low-voltage fast (LVF) onset ictal-like discharges in the rat entorhinal cortex in an in vitro slice preparation. We recorded a total of 90 single units (69 putative interneurons, 17 putative principal and 4 unclassified cells) from 36 slices, and found that: (i) interneurons (66.7%) were more likely to fire during interictal discharges than principal cells (35.3%); (ii) interneuron activity increased shortly before LVF ictal onset, whereas principal cell activity did not change; (iii) interneurons and principal cells fired at high rates throughout the tonic phase of the ictal discharge; however, (iv) only interneurons showed phase-locked relationship with LVF activity at 5-15Hz during the tonic phase. Finally, the association of interneuron firing with interictal discharges was maintained during blockade of ionotropic glutamatergic transmission. Our findings demonstrate the prominent involvement of interneurons in interictal discharge generation and in the transition to LVF ictal activity in this in vitro model of epileptiform synchronization.

Hypersynchronous ictal onset in the perirhinal cortex results from dynamic weakening in inhibition

We obtained field, K(+) selective and "sharp" intracellular recordings from the rat entorhinal (EC) and perirhinal (PC) cortices in an in vitro brain slice preparation to identify the events occurring at interictal-to-ictal transition during 4-aminopyridine application. Field recordings revealed interictal- (duration: 1.1 to 2.2s) and ictal-like (duration: 31 to 103s) activity occurring synchronously in EC and PC; in addition, interictal spiking in PC increased in frequency shortly before the onset of ictal oscillatory activity thus resembling the hypersynchronous seizure onset seen in epileptic patients and in in vivo animal models. Intracellular recordings with K-acetate+QX314-filled pipettes in PC principal cells showed that spikes at ictal onset had post-burst hyperpolarizations (presumably mediated by postsynaptic GABAA receptors), which gradually decreased in amplitude. This trend was associated with a progressive positive shift of the post-burst hyperpolarization reversal potential. Finally, the transient elevations in [K(+)]o (up to 4.4mM from a base line of 3.2mM) - which occurred with the interictal events in PC - progressively increased (up to 7.3mM) with the spike immediately preceding ictal onset. Our findings indicate that hypersynchronous seizure onset in rat PC is caused by dynamic weakening of GABAA receptor signaling presumably resulting from [K(+)]o accumulation.

Early detection of human focal seizures based on cortical multiunit activity

Approximately 50 million people in the world suffer from epileptic seizures. Reliable early seizure detection could bring significantly beneficial therapeutic alternatives. In recent decades, most approaches have relied on scalp EEG and intracranial EEG signals, but practical early detection for closed-loop seizure control remains challenging. In this study, we present preliminary analyses of an early detection approach based on intracortical neuronal multiunit activity (MUA) recorded from a 96-microelectrode array (MEA). The approach consists of (1) MUA detection from broadband field potentials recorded at 30 kHz by the MEA; (2) MUA feature extraction; (3) cost-sensitive support vector machine classification of ictal and interictal samples; and (4) Kalman-filtering postprocessing. MUA was here defined as the number of threshold crossing (spike counts) applied to the 300 Hz-6 kHz bandpass filtered local field potentials in 0.1 sec time windows. MUA features explored in this study included the mean, variance, and Fano-factor, computed across the MEA channels. In addition, we used the leading eigenvalues of MUA spatial and temporal correlation matrices computed in 1-sec moving time windows. We assessed the seizure detection approach on out-of-sample data from one-participant recordings with six seizure events and 4.73-hour interictal data. The proposed MUA-based detection approach yielded a 100% sensitivity (6/6) and no false positives, and a latency of 4.17 ± 2.27 sec (mean ± SD) with respect to ECoG-identified seizure onsets. These preliminary results indicate intracortical MUA may be a useful signal for early detection of human epileptic seizures.

Joint analysis of extracellular spike waveforms and neuronal network bursts

BACKGROUND

Neuronal networks are routinely assessed based on extracellular electrophysiological microelectrode array (MEA) measurements by spike sorting, and spike and burst statistics. We propose to jointly analyze sorted spikes and detected bursts, and hypothesize that the obtained spike type compositions of the bursts can provide new information on the functional networks.

NEW METHOD

Spikes are detected and sorted to obtain spike types and bursts are detected. In the proposed joint analysis, each burst spike is associated with a spike type, and the spike type compositions of the bursts are assessed.

RESULTS

The proposed method was tested with simulations and MEA measurements of in vitro human stem cell derived neuronal networks under different pharmacological treatments. The results show that the treatments altered the spike type compositions of the bursts. For example, 6-cyano-7-nitroquinoxaline-2,3-dione almost completely abolished two types of spikes which had composed the bursts in the baseline, while bursts of spikes of two other types appeared more frequently. This phenomenon was not observable by spike sorting or burst analysis alone, but was revealed by the proposed joint analysis.

COMPARISON WITH EXISTING METHODS

The existing methods do not provide the information obtainable with the proposed method: for the first time, the spike type compositions of bursts are analyzed.

CONCLUSIONS

We showed that the proposed method provides useful and novel information, including the possible changes in the spike type compositions of the bursts due to external factors. Our method can be employed on any data exhibiting sortable action potential waveforms and detectable bursts.

An AKT3-FOXG1-reelin network underlies defective migration in human focal malformations of cortical development

Focal malformations of cortical development (FMCDs) account for the majority of drug-resistant pediatric epilepsy. Postzygotic somatic mutations activating the phosphatidylinositol-4,5-bisphosphate-3-kinase (PI3K)-protein kinase B (AKT)-mammalian target of rapamycin (mTOR) pathway are found in a wide range of brain diseases, including FMCDs. It remains unclear how a mutation in a small fraction of cells disrupts the architecture of the entire hemisphere. Within human FMCD-affected brain, we found that cells showing activation of the PI3K-AKT-mTOR pathway were enriched for the AKT3(E17K) mutation. Introducing the FMCD-causing mutation into mouse brain resulted in electrographic seizures and impaired hemispheric architecture. Mutation-expressing neural progenitors showed misexpression of reelin, which led to a non-cell autonomous migration defect in neighboring cells, due at least in part to derepression of reelin transcription in a manner dependent on the forkhead box (FOX) transcription factor FOXG1. Treatments aimed at either blocking downstream AKT signaling or inactivating reelin restored migration. These findings suggest a central AKT-FOXG1-reelin signaling pathway in FMCD and support pathway inhibitors as potential treatments or therapies for some forms of focal epilepsy.

Microcircuits in Epilepsy: Heterogeneity and Hub Cells in Network Synchronization

Epilepsy is a complex disorder involving neurological alterations that lead to the pathological development of spontaneous, recurrent seizures. For decades, seizures were thought to be largely repetitive, and had been examined at the macrocircuit level using electrophysiological recordings. However, research mapping the dynamics of large neuronal populations has revealed that seizures are not simply recurrent bursts of hypersynchrony. Instead, it is becoming clear that seizures involve a complex interplay of different neurons and circuits. Herein, we will review studies examining microcircuit changes that may underlie network hyperexcitability, discussing observations from network theory, computational modeling, and optogenetics. We will delve into the idea of hub cells as pathological centers for seizure activity, and will explore optogenetics as a novel avenue to target and treat pathological circuits. Finally, we will conclude with a discussion on future directions in the field.

Intracranial neuronal ensemble recordings and analysis in epilepsy

Pathological neuronal firing was demonstrated 50 years ago as the hallmark of epileptically transformed cortex with the use of implanted microelectrodes. Since then, microelectrodes remained only experimental tools in humans to detect unitary neuronal activity to reveal physiological and pathological brain functions. This recording technique has evolved substantially in the past few decades; however, based on recent human data implying their usefulness as diagnostic tools, we expect a substantial increase in the development of microelectrodes in the near future. Here, we review the technological background and history of microelectrode array development for human examinations in epilepsy, including discussions on of wire-based and microelectrode arrays fabricated using micro-electro-mechanical system (MEMS) techniques and novel future techniques to record neuronal ensemble. We give an overview of clinical and surgical considerations, and try to provide a list of probes on the market with their availability for human recording. Then finally, we briefly review the literature on modulation of single neuron for the treatment of epilepsy, and highlight the current topics under examination that can be background for the future development.

Human brain slices for epilepsy research: Pitfalls, solutions and future challenges

Increasingly, neuroscientists are taking the opportunity to use live human tissue obtained from elective neurosurgical procedures for electrophysiological studies in vitro. Access to this valuable resource permits unique studies into the network dynamics that contribute to the generation of pathological electrical activity in the human epileptic brain. Whilst this approach has provided insights into the mechanistic features of electrophysiological patterns associated with human epilepsy, it is not without technical and methodological challenges. This review outlines the main difficulties associated with working with epileptic human brain slices from the point of collection, through the stages of preparation, storage and recording. Moreover, it outlines the limitations, in terms of the nature of epileptic activity that can be observed in such tissue, in particular, the rarity of spontaneous ictal discharges, we discuss manipulations that can be utilised to induce such activity. In addition to discussing conventional electrophysiological techniques that are routinely employed in epileptic human brain slices, we review how imaging and multielectrode array recordings could provide novel insights into the network dynamics of human epileptogenesis. Acute studies in human brain slices are ultimately limited by the lifetime of the tissue so overcoming this issue provides increased opportunity for information gain. We review the literature with respect to organotypic culture techniques that may hold the key to prolonging the viability of this material. A combination of long-term culture techniques, viral transduction approaches and electrophysiology in human brain slices promotes the possibility of large scale monitoring and manipulation of neuronal activity in epileptic microcircuits.

Suppressing cAMP response element-binding protein transcription shortens the duration of status epilepticus and decreases the number of spontaneous seizures in the pilocarpine model of epilepsy

OBJECTIVE

Current epilepsy therapies directed at altering the function of neurotransmitter receptors or ion channels, or release of synaptic vesicles fail to prevent seizures in approximately 30% of patients. A better understanding of the molecular mechanism underlying epilepsy is needed to provide new therapeutic targets. The activity of cyclic AMP (cAMP) response element-binding protein (CREB), a major transcription factor promoting CRE-mediated transcription, increases following a prolonged seizure called status epilepticus. It is also increased in the seizure focus of patients with medically intractable focal epilepsy. Herein we explored the effect of acute suppression of CREB activity on status epilepticus and spontaneous seizures in a chronic epilepsy model.

METHODS

Pilocarpine chemoconvulsant was used to induce status epilepticus. To suppress CREB activity, a transgenic mouse line expressing an inducible dominant negative mutant of CREB (CREB(IR) ) with a serine to alanine 133 substitution was used. Status epilepticus and spontaneous seizures of transgenic and wild-type mice were analyzed using video-electroencephalography (EEG) to assess the effect of CREB suppression on seizures.

RESULTS

Our findings indicate that activation of CREB(IR) shortens the duration of status epilepticus. The frequency of spontaneous seizures decreased in mice with chronic epilepsy during CREB(IR) induction; however, the duration of the spontaneous seizures was unchanged. Of interest, we found significantly reduced levels of phospho-CREB Ser133 upon activation of CREB(IR) , supporting prior work suggesting that binding to the CRE site is important for CREB phosphorylation.

SIGNIFICANCE

Our results suggest that CRE transcription supports seizure activity both during status epilepticus and in spontaneous seizures. Thus, blocking of CRE transcription is a novel target for the treatment of epilepsy.

Insulin growth factor-1 (IGF-1) enhances hippocampal excitatory and seizure activity through IGF-1 receptor-mediated mechanisms in the epileptic brain

Insulin-like growth factor-1 (IGF-1) is known to promote neurogenesis and survival. However, recent studies have suggested that IGF-1 regulates neuronal firing and excitatory neurotransmission. In the present study, focusing on temporal lobe epilepsy, we found that IGF-1 levels and IGF-1 receptor activation are increased in human epileptogenic tissues, and pilocarpine- and pentylenetetrazole-treated rat models. Using an acute model of seizures, we showed that lateral cerebroventricular infusion of IGF-1 elevates IGF-1 receptor (IGF-1R) signalling before pilocarpine application had proconvulsant effects. In vivo electroencephalogram recordings and power spectrogram analysis of local field potential revealed that IGF-1 promotes epileptiform activities. This effect is diminished by co-application of an IGF-1R inhibitor. In an in vitro electrophysiological study, we demonstrated that IGF-1 enhancement of excitatory neurotransmission and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor- and N-methyl-D-aspartate receptor-mediated currents is inhibited by IGF-1R inhibitor. Finally, activation of extracellular signal-related kinase (ERK)-1/2 and protein kinase B (Akt) in seizures in rats is increased by exogenous IGF-1 and diminished by picropodophyllin. A behavioural study reveals that the ERK1/2 or Akt inhibitor attenuates seizure activity. These results indicate that increased IGF-1 levels after recurrent hippocampal neuronal firings might, in turn, promote seizure activity via IGF-1R-dependent mechanisms. The present study presents a previously unappreciated role of IGF-1R in the development of seizure activity.

Microscale spatiotemporal dynamics during neocortical propagation of human focal seizures

Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4×4 mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) a newly developed stage segmentation method, applied to local field potentials (LFPs) and multiunit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~2-3 Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25-60 Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the MUA peak onset time (in seizures where such peak onset occurred) and changes in MUA or LFP propagation patterns. Overall, our findings indicate that the recruitment of neocortical territories into ictal activity undergoes complex spatiotemporal dynamics evolving in slow discrete states, which are consistent across seizures within each patient. Furthermore, ictal states at finer spatiotemporal scales (individual SWDs or gamma oscillations) are organized by slower time scale network dynamics evolving through these discrete stages.

GABAergic inhibition shapes interictal dynamics in awake epileptic mice

Epilepsy is characterized by recurrent seizures and brief, synchronous bursts called interictal spikes that are present in-between seizures and observed as transient events in EEG signals. While GABAergic transmission is known to play an important role in shaping healthy brain activity, the role of inhibition in these pathological epileptic dynamics remains unclear. Examining the microcircuits that participate in interictal spikes is thus an important first step towards addressing this issue, as the function of these transient synchronizations in either promoting or prohibiting seizures is currently under debate. To identify the microcircuits recruited in spontaneous interictal spikes in the absence of any proconvulsive drug or anaesthetic agent, we combine a chronic model of epilepsy with in vivo two-photon calcium imaging and multiunit extracellular recordings to map cellular recruitment within large populations of CA1 neurons in mice free to run on a self-paced treadmill. We show that GABAergic neurons, as opposed to their glutamatergic counterparts, are preferentially recruited during spontaneous interictal activity in the CA1 region of the epileptic mouse hippocampus. Although the specific cellular dynamics of interictal spikes are found to be highly variable, they are consistently associated with the activation of GABAergic neurons, resulting in a perisomatic inhibitory restraint that reduces neuronal spiking in the principal cell layer. Given the role of GABAergic neurons in shaping brain activity during normal cognitive function, their aberrant unbalanced recruitment during these transient events could have important downstream effects with clinical implications.

Altered structure and function of astrocytes following status epilepticus

Temporal lobe epilepsy (TLE) is a devastating seizure disorder that is often caused by status epilepticus (SE). Temporal lobe epilepsy can be very difficult to control with currently available antiseizure drugs, and there are currently no disease-modifying therapies that can prevent the development of TLE in those patients who are at risk. While the functional changes that occur in neurons following SE and leading to TLE have been well studied, only recently has research attention turned to the role in epileptogenesis of astrocytes, the other major cell type of the brain. Given that epilepsy is a neural circuit disorder, innovative ways to evaluate the contributions that both neurons and astrocytes make to aberrant circuit activity will be critical for the understanding of the emergent network properties that result in seizures. Recently described approaches using genetically encoded calcium-indicating proteins can be used to image dynamic calcium transients, a marker of activity in both neurons and glial cells. It is anticipated that this work will lead to novel insights into the process of epileptogenesis at the network level and may identify disease-modifying therapeutic targets that have been missed because of a largely neurocentric view of seizure generation following SE. This article is part of a Special Issue entitled "Status Epilepticus".

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.

An EEG-fMRI Study on the Termination of Generalized Spike-And-Wave Discharges in Absence Epilepsy

Introduction

Different studies have investigated by means of EEG-fMRI coregistration the brain networks related to generalized spike-and-wave discharges (GSWD) in patients with idiopathic generalized epilepsy (IGE). These studies revealed a widespread GSWD-related neural network that involves the thalamus and regions of the default mode network. In this study we investigated which brain regions are critically involved in the termination of absence seizures (AS) in a group of IGE patients.

Methods

Eighteen patients (6 male; mean age 25 years) with AS were included in the EEG-fMRI study. Functional data were acquired at 3T with continuous simultaneous video-EEG recording. Event-related analysis was performed with SPM8 software, using the following regressors: (1) GSWD onset and duration; (2) GSWD offset. Data were analyzed at single-subject and at group level with a second level random effect analysis.

Results

A mean of 17 events for patient was recorded (mean duration of 4.2 sec). Group-level analysis related to GSWD onset respect to rest confirmed previous findings revealing thalamic activation and a precuneus/posterior cingulate deactivation. At GSWD termination we observed a decrease in BOLD signal over the bilateral dorsolateral frontal cortex respect to the baseline (and respect to GSWD onset). The contrast GSWD offset versus onset showed a BOLD signal increase over the precuneus-posterior cingulate region bilaterally. Parametric correlations between electro-clinical variables and BOLD signal at GSWD offset did not reveal significant effects.

Conclusion

The role of the decreased neural activity of lateral prefrontal cortex at GSWD termination deserve future investigations to ascertain if it has a role in promoting the discharge offset, as well as in the determination of the cognitive deficits often present in patients with AS. The increased BOLD signal at precuneal/posterior cingulate cortex might reflect the recovery of neural activity in regions that are “suspended” during spike and waves activity, as previously hypothesized.

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.

An externally head-mounted wireless neural recording device for laboratory animal research and possible human clinical use

In this paper we present a new type of head-mounted wireless neural recording device in a highly compact package, dedicated for untethered laboratory animal research and designed for future mobile human clinical use. The device, which takes its input from an array of intracortical microelectrode arrays (MEA) has ninety-seven broadband parallel neural recording channels and was integrated on to two custom designed printed circuit boards. These house several low power, custom integrated circuits, including a preamplifier ASIC, a controller ASIC, plus two SAR ADCs, a 3-axis accelerometer, a 48MHz clock source, and a Manchester encoder. Another ultralow power RF chip supports an OOK transmitter with the center frequency tunable from 3GHz to 4GHz, mounted on a separate low loss dielectric board together with a 3V LDO, with output fed to a UWB chip antenna. The IC boards were interconnected and packaged in a polyether ether ketone (PEEK) enclosure which is compatible with both animal and human use (e.g. sterilizable). The entire system consumes 17mA from a 1.2Ahr 3.6V Li-SOCl2 1/2AA battery, which operates the device for more than 2 days. The overall system includes a custom RF receiver electronics which are designed to directly interface with any number of commercial (or custom) neural signal processors for multi-channel broadband neural recording. Bench-top measurements and in vivo testing of the device in rhesus macaques are presented to demonstrate the performance of the wireless neural interface.

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 Pro-inflammatory Cytokine Interleukin-1β is a Key Regulatory Factor for the Postictal Suppression in Mice

AIMS

The postictal suppression (PS) is a common and important period following an epileptic seizure but has not been well studied. This study was designed to determine whether interleukin-1β (IL-1β) is involved in the PS.

METHODS

The effects of IL-1β on the PS were tested in three independent seizure models induced by hippocampal kindling, maximal electroshock seizure (MES), and 4-aminopyridine, respectively.

RESULTS

IL-1R1 knockout or IL-1RA enhanced the seizure refractory phenomenon without influencing the baseline seizure threshold in intermittent MES model. IL-1β attenuated the seizure refractory phenomenon without affecting the severity of the preceding seizures in hippocampal kindling model, while IL-1RA enhanced it. Besides, IL-1β reduced the postictal EEG suppression period, while IL-1RA prolonged it. And IL-1β showed no further effect on the postictal EEG suppression and seizure refractory phenomenon in IL-1R1 knockout mice. In addition, 30 min after intrahippocampal injection of 4-aminopyridine, IL-1β increased the incidence of SE, while IL-1RA prolonged the intervals between recurrent seizures.

CONCLUSIONS

This study provides the first direct evidence that IL-1β is key regulatory factor for the PS, and its receptor IL-1R1 may be a potential target for adjuvant treatment of postictal problems.

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.

Network Mechanisms Generating Abnormal and Normal Hippocampal High-Frequency Oscillations: A Computational Analysis

High-frequency oscillations (HFOs) are an intriguing potential biomarker for epilepsy, typically categorized according to peak frequency as either ripples (100–250 Hz) or fast ripples (>250 Hz). In the hippocampus, fast ripples were originally thought to be more specific to epileptic tissue, but it is still very difficult to distinguish which HFOs are caused by normal versus pathological brain activity. In this study, we use a computational model of hippocampus to investigate possible network mechanisms underpinning normal ripples, pathological ripples, and fast ripples. Our results unify several prior findings regarding HFO mechanisms, and also make several new predictions regarding abnormal HFOs. We show that HFOs are generic, emergent phenomena whose characteristics reflect a wide range of connectivity and network input. Although produced by different mechanisms, both normal and abnormal HFOs generate similar ripple frequencies, underscoring that peak frequency is unable to distinguish the two. Abnormal ripples are generic phenomena that arise when input to pyramidal cells overcomes network inhibition, resulting in high-frequency, uncoordinated firing. In addition, fast ripples transiently and sporadically arise from the precise conditions that produce abnormal ripples. Lastly, we show that such abnormal conditions do not require any specific network structure to produce coherent HFOs, as even completely asynchronous activity is capable of producing abnormal ripples and fast ripples in this manner. These results provide a generic, network-based explanation for the link between pathological ripples and fast ripples, and a unifying description for the entire spectrum from normal ripples to pathological fast ripples.

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.

Epilepsy surgery: current status and ongoing challenges

This article reviews the current status of surgical treatment of epilepsy and introduces the ongoing challenges. Seizure outcome of resective surgery for focal seizures associated with focal lesions is satisfactory. Particularly for mesial temporal lobe epilepsy, surgical treatment should be considered from the earlier stage of the disease. Meanwhile, surgical outcome in nonlesional extratemporal lobe epilepsy is still to be improved using various approaches. Disconnective surgeries reduce surgical complications of extensive resections while achieving equivalent or better seizure outcomes. Multiple subpial transection is still being modified expecting a better outcome by transection to the vertical cortices along the sulci- and multi-directional transection from a single entry point. Hippocampal transection is expected to preserve memory function while interrupting the abnormal epileptic synchronization. Proper selection or combination of subdural and depth electrodes and a wide-band analysis of electroencephalography may improve the accurate localization of epileptogenic region. Patients for whom curative resective surgery is not indicated because of generalized or bilateral multiple nature of their epilepsies, neuromodulation therapies are options of treatment which palliate their seizures.

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.

Measuring predictability of autonomous network transitions into bursting dynamics

Understanding spontaneous transitions between dynamical modes in a network is of significant importance. These transitions may separate pathological and normal functions of the brain. In this paper, we develop a set of measures that, based on spatio-temporal features of network activity, predict autonomous network transitions from asynchronous to synchronous dynamics under various conditions. These metrics quantify spike-timing distributions within a narrow time window as a function of the relative location of the active neurons. We applied these metrics to investigate the properties of these transitions in excitatory-only and excitatory-and-inhibitory networks and elucidate how network topology, noise level, and cellular heterogeneity affect both the reliability and the timeliness of the predictions. The developed measures can be calculated in real time and therefore potentially applied in clinical situations.

Evidence for consolidation of neuronal assemblies after seizures in humans

The establishment of memories involves reactivation of waking neuronal activity patterns and strengthening of associated neural circuits during slow-wave sleep (SWS), a process known as "cellular consolidation" (Dudai and Morris, 2013). Reactivation of neural activity patterns during waking behaviors that occurs on a timescale of seconds to minutes is thought to constitute memory recall (O'Keefe and Nadel, 1978), whereas consolidation of memory traces may be revealed and served by correlated firing (reactivation) that appears during sleep under conditions suitable for synaptic modification (Buhry et al., 2011). Although reactivation has been observed in human neuronal recordings (Gelbard-Sagiv et al., 2008; Miller et al., 2013), reactivation during sleep has not, likely because data are difficult to obtain and the effect is subtle. Seizures, however, provide intense and synchronous, yet sparse activation (Bower et al., 2012) that could produce a stronger consolidation effect if seizures activate learning-related mechanisms similar to those activated by learned tasks. Continuous wide-bandwidth recordings from patients undergoing intracranial monitoring for drug-resistant epilepsy revealed reactivation of seizure-related neuronal activity during subsequent SWS, but not wakefulness. Those neuronal assemblies that were most strongly activated during seizures showed the largest correlation changes, suggesting that consolidation selectively strengthened neuronal circuits activated by seizures. These results suggest that seizures "hijack" physiological learning mechanisms and also suggest a novel epilepsy therapy targeting neuronal dynamics during post-seizure sleep.

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.

SPIKY: a graphical user interface for monitoring spike train synchrony

Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels.

Closed-loop control of a fragile network: application to seizure-like dynamics of an epilepsy model

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Closed-loop therapy could therefore entail detecting when the network goes unstable, and then stimulating with an exogenous current to stabilize the network. In this study, a non-linear stochastic model of a neuronal network was used to simulate both seizure and non-seizure activity. In particular, synaptic weights between neurons were chosen such that the network's fixed point is stable during non-seizure periods, and a subset of these connections (the most fragile) were perturbed to make the same fixed point unstable to model seizure events; and, the model randomly transitions between these two modes. The goal of this study was to measure spike train observations from this epileptic network and then apply a feedback controller that (i) detects when the network goes unstable, and then (ii) applies a state-feedback gain control input to the network to stabilize it. The stability detector is based on a 2-state (stable, unstable) hidden Markov model (HMM) of the network, and detects the transition from the stable mode to the unstable mode from using the firing rate of the most fragile node in the network (which is the output of the HMM). When the unstable mode is detected, a state-feedback gain is applied to generate a control input to the fragile node bringing the network back to the stable mode. Finally, when the network is detected as stable again, the feedback control input is switched off. High performance was achieved for the stability detector, and feedback control suppressed seizures within 2 s after onset.

Prospects of epileptogenesis prevention

Epilepsy is a common neurologic disease, affecting about 1-2% of the population. In around 30% of patients with epilepsy, their seizures are not satisfactorily controlled and drug-resistant epilepsy constitutes a real therapeutic challenge. Consequently, there are efforts aimed at the inhibition of epileptogenesis, a process of converting a normal into an epileptic brain. Data on this problem have been mainly obtained in post-status epilepticus rodent models in which spontaneous seizure activity and behavioral disturbances develop over time. Among antiepileptic drugs, diazepam at high dose of 20mg/kg given during status epilepticus, significantly inhibited the development of spontaneous seizures and also, a strong neuroprotective effect was evident. Also gabapentin and valproate (over a period of 40 days) proved effective in the inhibition of spontaneous seizure activity and reduction of behavioral deficit. However, there are also data that valproate (over 28 days) significantly improved the behavioral performance without affecting the occurrence of spontaneous seizures. A number of antiepileptic drugs, carbamazepine, lamotrigine, levetiracetam, phenobarbital, and topiramate were completely ineffective. Among non-antiepileptic drugs, some promise show rapamycin, losartan and combinations of anti-inflammatory drugs, targeting different inflammatory pathways. Inhibition of epileptogenesis may become a valuable therapeutic approach provided that there are reliable markers of this process. Actually, such markers begin to emerge.

Optical triggered seizures using a caged 4-Aminopyridine

Animal models of epilepsy are critical not only for understanding the fundamental mechanism of epilepsy but also for testing the efficacy of new antiepileptic drugs and novel therapeutic interventions. Photorelease of caged molecules is widely used in biological research to control pharmacologic events with high spatio-temporal resolution. We developed a technique for in vivo optical triggering of neocortical seizures using a novel caged compound based on ruthenium photochemistry (RuBi-4AP). Epileptiform events in mouse cortex were induced with blue light in both whole brain and focal illumination. Multi-electrode array recording and optical techniques were used to characterize the propagation of these epileptic events, including interictal spikes, polyspikes, and ictal discharges. These results demonstrate a novel optically-triggered seizure model, with high spatio-temporal control, that could have widespread application in the investigation of ictal onset, propagation and to develop novel light-based therapeutic interventions.

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.

Instability detector of a fragile neural network: application to seizure detection in epilepsy

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Therefore, one method for detecting seizures is to detect when the neuronal network has gone unstable. This is important for implementing a closed-loop therapy to suppress seizures. In this paper, we consider a widely used nonlinear stochastic model of a neuronal network, and assume that spiking dynamics during non-seizure periods correspond to certain synaptic connections that render its fixed point stable. We then apply a minimum energy perturbation theory we recently developed for networks to determine the changes in the most fragile node's synaptic connections that make the same fixed point unstable (our model during seizure). Then a detector is designed as follows. First a 2-state HMM is constructed (stable=state 1 and unstable=state 2) with fixed state transition probabilities, where the output observation is the firing rate of the most fragile node in the network. The output density functions are assumed to be Gaussian with parameters computed using maximum likelihood estimation on data generated from the nonlinear network model in each state. Then, to detect a transition from stable to unstable, spiking activity is simulated in all nodes from the nonlinear model. The detector first measures the firing rate of the fragile node, and computes the derivative of the cumulative likelihood ratio of the observed firing rate from the HMM's output distributions. When the derivative exceeds a certain threshold, a transition to the unstable state is detected. Various thresholds were tested when firing rate was computed by averaging over a different number of windows of different lengths. High performance was achieved and a tradeoff was found between the accuracy of the detector and the detection delay.