Transition to seizure: from "macro"- to "micro"-mysteries

Transition to seizure in focal epilepsy: From SEEG phenomenology to underlying mechanisms

OBJECTIVE

For the pre-surgical evaluation of patients with drug-resistant focal epilepsy, stereo-electroencephalographic (SEEG) signals are routinely recorded to identify the epileptogenic zone network (EZN). This network consists of remote brain regions involved in seizure initiation. However, the pathophysiological mechanisms underlying typical SEEG patterns that occur during the transition from interictal to ictal activity in distant brain nodes of the EZN remain poorly understood. The primary aim is to identify and explain these mechanisms using a novel physiologically-plausible model of the EZN.

METHODS

We analyzed SEEG signals recorded from the EZN in 10 patients during the transition from interictal to ictal activity. This transition consisted of a sequence of periods during which SEEG signals from distant neocortical regions showed stereotypical patterns of activity: sustained preictal spiking activity preceding a fast activity occurring at seizure onset, followed by the ictal activity. Spectral content and non-linear correlation of SEEG signals were analyzed. In addition, we developed a novel neuro-inspired computational model consisting of bidirectionally coupled neuronal populations.

RESULTS

The proposed model captured the essential characteristics of the patient signals, including the quasi-synchronous onset of rapid discharges in distant interconnected epileptogenic zones. Statistical analysis confirmed the dynamic correlation/de-decorrelation pattern observed in the patient signals and accurately reproduced in the simulated signals.

SIGNIFICANCE

This study provides insight into the abnormal dynamic changes in glutamatergic and γ-aminobutyric acid (GABA)ergic synaptic transmission that occur during the transition to seizures. The results strongly support the hypothesis that bidirectional connections between distant neuronal populations of the EZN (from pyramidal cells to vaso-intestinal peptide-positive interneurons) play a key role in this transition, while parvalbumin-positive interneurons intervene in the emergence of rapid discharges at seizure onset.

Intrinsic neural diversity quenches the dynamic volatility of neural networks

Heterogeneity is the norm in biology. The brain is no different: Neuronal cell types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs, and ion channel distributions. While this biophysical diversity enriches neural systems' dynamical repertoire, it remains challenging to reconcile with the robustness and persistence of brain function over time (resilience). To better understand the relationship between excitability heterogeneity (variability in excitability within a population of neurons) and resilience, we analyzed both analytically and numerically a nonlinear sparse neural network with balanced excitatory and inhibitory connections evolving over long time scales. Homogeneous networks demonstrated increases in excitability, and strong firing rate correlations-signs of instability-in response to a slowly varying modulatory fluctuation. Excitability heterogeneity tuned network stability in a context-dependent way by restraining responses to modulatory challenges and limiting firing rate correlations, while enriching dynamics during states of low modulatory drive. Excitability heterogeneity was found to implement a homeostatic control mechanism enhancing network resilience to changes in population size, connection probability, strength and variability of synaptic weights, by quenching the volatility (i.e., its susceptibility to critical transitions) of its dynamics. Together, these results highlight the fundamental role played by cell-to-cell heterogeneity in the robustness of brain function in the face of change.

Loss of neuronal heterogeneity in epileptogenic human tissue impairs network resilience to sudden changes in synchrony

A myriad of pathological changes associated with epilepsy can be recast as decreases in cell and circuit heterogeneity. We thus propose recontextualizing epileptogenesis as a process where reduction in cellular heterogeneity, in part, renders neural circuits less resilient to seizure. By comparing patch clamp recordings from human layer 5 (L5) cortical pyramidal neurons from epileptogenic and non-epileptogenic tissue, we demonstrate significantly decreased biophysical heterogeneity in seizure-generating areas. Implemented computationally, this renders model neural circuits prone to sudden transitions into synchronous states with increased firing activity, paralleling ictogenesis. This computational work also explains the surprising finding of significantly decreased excitability in the population-activation functions of neurons from epileptogenic tissue. Finally, mathematical analyses reveal a bifurcation structure arising only with low heterogeneity and associated with seizure-like dynamics. Taken together, this work provides experimental, computational, and mathematical support for the theory that ictogenic dynamics accompany a reduction in biophysical heterogeneity.

Exploring the Inhibitory Effect of Low-frequency Magnetic Fields on Epileptiform Discharges in Juvenile Rat Hippocampus

Stimulation with a low frequency electromagnetic field (LF-EMF) has proven to represent a powerful method for the suppression of seizures, as demonstrated in select clinical and laboratory studies. However, the mechanism by which LF-EMF suppresses seizures remains unclear. The purpose of the present study was to explore the modulatory effect of LF-EMF on epileptiform discharges (EDs) using rat hippocampal slices and investigate the underlying mechanisms that mediate these effects. EDs in hippocampal slices was induced by magnesium-free (zero-Mg²⁺) artificial cerebrospinal fluid (ACSF) and recorded using an in vitro micro-electrode array (MEA). A small sub-decimeter coil was designed and incorporated in a flexible magnetic stimulation device that allowed electromagnetic fields with different parameters to be delivered to slices. After a stable ED event was recorded, magnetic fields of 0.5 Hz (30 min) with a magnetic intensity of 0.13 mT (5 V_pp voltage input) and 0.25 mT (20 V_pp voltage input) were applied. The results indicated that a high-amplitude 0.5 Hz magnetic field could lead to persistent suppression of ictal discharges (IDs), while low-amplitude magnetic fields did not influence IDs. The persistent suppression of complex ED was prevented if the magnetic fields were applied in the presence of 10 μmol/L bicuculline (BIC), a γ-aminobutyric acid type A (GABA_A) receptor antagonist, while the application of BIC subsequent to a magnetic field application led to the reappearance of ID. The addition of BIC resulted in EDs that had previously been inhibited by magnetic fields, reappearing. Low-frequency magnetic stimulation was able to inhibit the conversion from interictal discharges (IIDs) or preictal discharges (PIDs) to IDs. This suppression was attributed to the modulation of GABA_A receptor activity.

An Excitatory and Epileptogenic Effect of Dentate Gyrus Mossy Cells in a Mouse Model of Epilepsy

The sparse activity of hippocampal dentate gyrus (DG) granule cells (GCs) is thought to be critical for cognition and behavior, whereas excessive DG activity may contribute to disorders such as temporal lobe epilepsy (TLE). Glutamatergic mossy cells (MCs) of the DG are potentially critical to normal and pathological functions of the DG because they can regulate GC activity through innervation of GCs or indirectly through GABAergic neurons. Here, we test the hypothesis that MC excitation of GCs is normally weak, but under pathological conditions, MC excitation of GCs is dramatically strengthened. We show that selectively inhibiting MCs during severe seizures reduced manifestations of those seizures, hippocampal injury, and chronic epilepsy. In contrast, selectively activating MCs was pro-convulsant. Mechanistic in vitro studies using optogenetics further demonstrated the unanticipated ability of MC axons to excite GCs under pathological conditions. These results demonstrate an excitatory and epileptogenic effect of MCs in the DG.

Neurostimulation stabilizes spiking neural networks by disrupting seizure-like oscillatory transitions

An improved understanding of the mechanisms underlying neuromodulatory approaches to mitigate seizure onset is needed to identify clinical targets for the treatment of epilepsy. Using a Wilson–Cowan-motivated network of inhibitory and excitatory populations, we examined the role played by intrinsic and extrinsic stimuli on the network’s predisposition to sudden transitions into oscillatory dynamics, similar to the transition to the seizure state. Our joint computational and mathematical analyses revealed that such stimuli, be they noisy or periodic in nature, exert a stabilizing influence on network responses, disrupting the development of such oscillations. Based on a combination of numerical simulations and mean-field analyses, our results suggest that high variance and/or high frequency stimulation waveforms can prevent multi-stability, a mathematical harbinger of sudden changes in network dynamics. By tuning the neurons’ responses to input, stimuli stabilize network dynamics away from these transitions. Furthermore, our research shows that such stabilization of neural activity occurs through a selective recruitment of inhibitory cells, providing a theoretical undergird for the known key role these cells play in both the healthy and diseased brain. Taken together, these findings provide new vistas on neuromodulatory approaches to stabilize neural microcircuit activity.

How are results of EEG activation procedures associated with patient perception of seizure provocative factors? A single-center cross-sectional pilot study

PURPOSE

The purpose of this study was to examine the relationship between subjectively perceived seizure provocative factors or inhibitors and objectively recorded changes in epileptiform activity (EA) during EEG activation procedures.

MATERIAL AND METHODS

Consenting epilepsy patients (≥18 years old) were asked to complete a questionnaire by indicating whether items on a list provoke, inhibit or have no effect on their seizures. A scalp EEG was recorded afterwards to evaluate baseline epileptiform activity and its change (increase/decrease in frequency) during a set of activation procedures. These included hyperventilation, intermittent photic stimulation (IPS), eye-closing/eye-opening, tasks of reading aloud in a native and a foreign language, solving a Rubik's cube and crossing-out letters. We used correlation and multiple regression analysis to search for associations between the sum of self-reported provocative/inhibiting items and changes in EA.

RESULTS

Of the 90 patients recruited 75 (83.3%) indicated at least one seizure provocative factor. Sleep deprivation, emotional stress, negative emotions and alcohol use were most frequently selected as provoking seizures. Positive feelings, focused thinking, mental calculation and exercising were the most predominant seizure inhibitors. EEG data revealed a weak, but statistically significant correlation with the sum of items in distinct questionnaire groups (0.20 ≤ Spearman's ρ ≤ 0.39). Sensory stimuli (olfactory, gustatory, auditory and visual), cognitive phenomena (thoughts and feelings) and substance use were found to be significantly correlated with EEG results by being self-reported as both provoking and inhibiting seizures. A statistically significant relationship was also found between the increase in EA while reading aloud in a native language and the number of physiological states (sleep deprivation, stress etc.) indicated as provoking seizures (Spearman's ρ = 0.320, P = 0.005). A suitable stepwise multiple regression model was feasible for this finding (F(3, 71) = 7.396, P < 0.001, adjusted R squared = 0.206) with the additional inclusion of EA change during IPS and epilepsy type as explanatory variables.

CONCLUSION

Our pilot study indicates that there is a previously non-explored association between patients' self-perception of seizure provocative/inhibiting factors and objectively recorded changes in epileptiform activity during activation EEGs. Distinct EEG tests might be useful in activating ictogenic networks that are sensitive to indirect influence by hormonal, emotional or diurnally variable factors.

Interneuron Desynchronization Precedes Seizures in a Mouse Model of Dravet Syndrome

Recurrent seizures, which define epilepsy, are transient abnormalities in the electrical activity of the brain. The mechanistic basis of seizure initiation, and the contribution of defined neuronal subtypes to seizure pathophysiology, remains poorly understood. We performed in vivo two-photon calcium imaging in neocortex during temperature-induced seizures in male and female Dravet syndrome (Scn1a+/-) mice, a neurodevelopmental disorder with prominent temperature-sensitive epilepsy. Mean activity of both putative principal cells and parvalbumin-positive interneurons (PV-INs) was higher in Scn1a+/- relative to wild-type controls during quiet wakefulness at baseline and at elevated core body temperature. However, wild-type PV-INs showed a progressive synchronization in response to temperature elevation that was absent in PV-INs from Scn1a+/- mice. Hence, PV-IN activity remains intact interictally in Scn1a+/- mice, yet exhibits decreased synchrony immediately before seizure onset. We suggest that impaired PV-IN synchronization may contribute to the transition to the ictal state during temperature-induced seizures in Dravet syndrome.SIGNIFICANCE STATEMENT Epilepsy is a common neurological disorder defined by recurrent, unprovoked seizures. However, basic mechanisms of seizure initiation and propagation remain poorly understood. We performed in vivo two-photon calcium imaging in an experimental model of Dravet syndrome (Scn1a+/- mice)-a severe neurodevelopmental disorder defined by temperature-sensitive, treatment-resistant epilepsy-and record activity of putative excitatory neurons and parvalbumin-positive GABAergic neocortical interneurons (PV-INs) during naturalistic seizures induced by increased core body temperature. PV-IN activity was higher in Scn1a+/- relative to wild-type controls during quiet wakefulness. However, wild-type PV-INs showed progressive synchronization in response to temperature elevation that was absent in PV-INs from Scn1a+/- mice before seizure onset. Hence, impaired PV-IN synchronization may contribute to transition to seizure in Dravet syndrome.

Goldilocks Zone of Ictal Onset: Partially Recovered Synapses Provide the Kindling to Fuel Ictal Activity

A Proposed Mechanism for Spontaneous Transitions Between Interictal and Ictal Activity

Jacob T, Lillis KP, Wang Z, Swiercz W, Rahmati N, Staley KJ. J Neurosci. 2019;39(3):557-575. doi:10.1523/JNEUROSCI.0719-17.2018. Epub 2018 Nov 16. PMID: 30446533

Epileptic networks are characterized by 2 outputs: brief interictal spikes and rarer, more prolonged seizures. Although either output state is readily modeled in silico and induced experimentally, the transition mechanisms are unknown, in part because no models exhibit both output states spontaneously. In silico, small-world neural networks were built using single-compartment neurons whose physiological parameters were derived from dual whole-cell recordings of pyramidal cells in organotypic hippocampal slice cultures that were generating spontaneous seizure-like activity. In silico, neurons were connected by abundant local synapses and rare long-distance synapses. Activity-dependent synaptic depression and gradual recovery delimited synchronous activity. Full synaptic recovery engendered interictal population spikes that spread via long-distance synapses. When synaptic recovery was incomplete, postsynaptic neurons required coincident activation of multiple presynaptic terminals to reach firing threshold. Only local connections were sufficiently dense to spread activity under these conditions. This coalesced network activity into traveling waves whose velocity varied with synaptic recovery. Seizures were comprised of sustained traveling waves that were similar to those recorded during experimental and human neocortical seizures. Sustained traveling waves occurred only when wave velocity, network dimensions, and the rate of synaptic recovery enabled wave reentry into previously depressed areas at precisely ictogenic levels of synaptic recovery. Wide-field, cellular resolution GCamP7b calcium imaging demonstrated similar initial patterns of activation in the hippocampus, although the anatomical distribution of traveling waves of synaptic activation was altered by the pattern of synaptic connectivity in the organotypic hippocampal cultures.

GABAA Receptor Activity Suppresses the Transition from Inter-ictal to Ictal Epileptiform Discharges in Juvenile Mouse Hippocampus

Exploring the transition from inter-ictal to ictal epileptiform discharges (IDs) and how GABA_A receptor-mediated action affects the onset of IDs will enrich our understanding of epileptogenesis and epilepsy treatment. We used Mg²⁺-free artificial cerebrospinal fluid (ACSF) to induce epileptiform discharges in juvenile mouse hippocampal slices and used a micro-electrode array to record the discharges. After the slices were exposed to Mg²⁺-free ACSF for 10 min-20 min, synchronous recurrent seizure-like events were recorded across the slices, and each event evolved from inter-ictal epileptiform discharges (IIDs) to pre-ictal epileptiform discharges (PIDs), and then to IDs. During the transition from IIDs to PIDs, the duration of discharges increased and the inter-discharge interval decreased. After adding 3 μmol/L of the GABA_A receptor agonist muscimol, PIDs and IDs disappeared, and IIDs remained. Further, the application of 10 μmol/L muscimol abolished all the epileptiform discharges. When the GABA_A receptor antagonist bicuculline was applied at 10 μmol/L, IIDs and PIDs disappeared, and IDs remained at decreased intervals. These results indicated that there are dynamic changes in the hippocampal network preceding the onset of IDs, and GABA_A receptor activity suppresses the transition from IIDs to IDs in juvenile mouse hippocampus.

Increased gyrification and aberrant adult neurogenesis of the dentate gyrus in adult rats

A remarkable example of maladaptive plasticity is the development of epilepsy after a brain insult or injury to a normal animal or human. A structure that is considered central to the development of this type of epilepsy is the dentate gyrus (DG), because it is normally a relatively inhibited structure and its quiescence is thought to reduce hippocampal seizure activity. This characteristic of the DG is also considered to be important for normal hippocampal-dependent cognitive functions. It has been suggested that the brain insults which cause epilepsy do so because they cause the DG to be more easily activated. One type of brain insult that is commonly used is induction of severe seizures (status epilepticus; SE) by systemic injection of a convulsant drug. Here we describe an alteration in the DG after this type of experimental SE that may contribute to chronic seizures that has not been described before: large folds or gyri that develop in the DG by 1 month after SE. Large gyri appeared to increase network excitability because epileptiform discharges recorded in hippocampal slices after SE were longer in duration when recorded inside gyri relative to locations outside gyri. Large gyri may also increase excitability because immature adult-born neurons accumulated at the base of gyri with time after SE, and previous studies have suggested that abnormalities in adult-born DG neurons promote seizures after SE. In summary, large gyri after SE are a common finding in adult rats, show increased excitability, and are associated with the development of an abnormal spatial distribution of adult-born neurons. Together these alterations may contribute to chronic seizures and associated cognitive comorbidities after SE.

Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model

Pharmacoresistant epilepsy is a chronic neurological condition in which a basal brain hyperexcitability results in paroxysmal hypersynchronous neuronal discharges. Human temporal lobe epilepsy has been associated with dysfunction or loss of the potassium-chloride cotransporter KCC2 in a subset of pyramidal cells in the subiculum, a key structure generating epileptic activities. KCC2 regulates intraneuronal chloride and extracellular potassium levels by extruding both ions. Absence of effective KCC2 may alter the dynamics of chloride and potassium levels during repeated activation of GABAergic synapses due to interneuron activity. In turn, such GABAergic stress may itself affect Cl- regulation. Such changes in ionic homeostasis may switch GABAergic signaling from inhibitory to excitatory in affected pyramidal cells and also increase neuronal excitability. Possibly these changes contribute to periodic bursting in pyramidal cells, an essential component in the onset of ictal epileptic events. We tested this hypothesis with a computational model of a subicular network with realistic connectivity. The pyramidal cell model explicitly incorporated the cotransporter KCC2 and its effects on the internal/external chloride and potassium levels. Our network model suggested the loss of KCC2 in a critical number of pyramidal cells increased external potassium and intracellular chloride concentrations leading to seizure-like field potential oscillations. These oscillations included transient discharges leading to ictal-like field events with frequency spectra as in vitro Restoration of KCC2 function suppressed seizure activity and thus may present a useful therapeutic option. These simulations therefore suggest that reduced KCC2 cotransporter activity alone may underlie the generation of ictal discharges.

SIGNIFICANCE STATEMENT

Ion regulation in the brain is a major determinant of neural excitability. Intracellular chloride in neurons, a partial determinant of the resting potential and the inhibitory reversal potentials, is regulated together with extracellular potassium via kation chloride cotransporters. During temporal lobe epilepsy, the homeostatic regulation of intracellular chloride is impaired in pyramidal cells, yet how this dysregulation may lead to seizures has not been explored. Using a realistic neural network model describing ion mechanisms, we show that chloride homeostasis pathology provokes seizure activity analogous to recordings from epileptogenic brain tissue. We show that there is a critical percentage of pathological cells required for seizure initiation. Our model predicts that restoration of the chloride homeostasis in pyramidal cells could be a viable antiepileptic strategy.

Functional Brain Dysfunction in Patients with Benign Childhood Epilepsy as Revealed by Graph Theory

There is growing evidence that brain networks are altered in epileptic subjects. In this study, we investigated the functional connectivity and brain network properties of benign childhood epilepsy with centrotemporal spikes using graph theory. Benign childhood epilepsy with centrotemporal spikes is the most common form of idiopathic epilepsy in young children under the age of 16 years. High-density EEG data were recorded from patients and controls in resting state with eyes closed. Data were preprocessed and spike and spike-free segments were selected for analysis. Phase locking value was calculated for all paired combinations of channels and for five frequency bands (δ, θ, α, β₁ and β₂). We computed the degree and small-world parameters—clustering coefficient (C) and path length (L)—and compared the two patient conditions to controls. A higher degree at epileptic zones during interictal epileptic spikes (IES) was observed in all frequency bands. Both patient conditions reduced connection at the occipital and right frontal regions close to the epileptic zone in the α band. The “small-world” features (high C and short L) were deviated in patients compared to controls. A changed from an ordered network in the δ band to a more randomly organized network in the α band was observed in patients compared to healthy controls. These findings show that the benign epileptic brain network is disrupted not only at the epileptic zone, but also in other brain regions especially frontal regions.

Neural Connectivity in Epilepsy as Measured by Granger Causality

Epilepsy is a chronic neurological disorder characterized by repeated seizures or excessive electrical discharges in a group of brain cells. Prevalence rates include about 50 million people worldwide and 10% of all people have at least one seizure at one time in their lives. Connectivity models of epilepsy serve to provide a deeper understanding of the processes that control and regulate seizure activity. These models have received initial support and have included measures of EEG, MEG, and MRI connectivity. Preliminary findings have shown regions of increased connectivity in the immediate regions surrounding the seizure foci and associated low connectivity in nearby regions and pathways. There is also early evidence to suggest that these patterns change during ictal events and that these changes may even by related to the occurrence or triggering of seizure events. We present data showing how Granger causality can be used with EEG data to measure connectivity across brain regions involved in ictal events and their resolution. We have provided two case examples as a demonstration of how to obtain and interpret such data. EEG data of ictal events are processed, converted to independent components and their dipole localizations, and these are used to measure causality and connectivity between these locations. Both examples have shown hypercoupling near the seizure foci and low causality across nearby and associated neuronal pathways. This technique also allows us to track how these measures change over time and during the ictal and post-ictal periods. Areas for further research into this technique, its application to epilepsy, and the formation of more effective therapeutic interventions are recommended.

Focus on desynchronization rather than excitability: a new strategy for intraencephalic electrical stimulation

Epilepsy is a severely debilitating brain disease, often associated with premature death, which has an urgent need for alternative methods of treatment. In fact, roughly 25% of patients with epilepsy do not have seizures satisfactorily controlled by pharmacological treatment, and 30% of these patients with treatment-refractory seizures are not even eligible for ablative surgery. Epilepsy is most readily identifiable by its seizures and/or paroxysmal events, mostly viewed as spontaneously recurrent and unpredictable, which are caused by stereotyped changes in neurological function associated with hyperexcitability and hypersynchronicity of the underlying neural networks. Treatment has strongly been based on the fixed goal of depressing neuronal activity, working under the veiled assumption that hyperexcitability would lead to synchronous neuronal activity and, therefore, to seizure. Over the last 20-30 years, the emergence of electrical (ES) of deep brain structures, a practicable option for treating patients with otherwise untreatable seizures, has broadened our understanding of anticonvulsant mechanisms that conceptually differ from those of pharmacological treatment. Conversely, the research on ES therapy applied to epilepsy is contributing significantly to untwine the phenomena of excitation from that of synchronization as potential target mechanisms for abolishing seizures and predicting paroxysmal events. This paper is, thus, an addendum to other reviews on the subject of ES therapy in epilepsy which focuses on the desynchronization effect ES has on epileptogenic neural networks rather than its effect on overall brain excitability.

Hypothesizing the body's genius to trigger and self-organize its healing: 25 years using a standardized neurophysics therapy

We aim for this contribution to operate bi-directionally, both as a "bedside to bench" reverse-translational fractal physiological hypothesis and as a methodological innovation to inform clinical practice. In 25 years using gym equipment therapeutically in non-research settings, the standardized therapy is consistently observed to trigger universal responses of micro to macro waves of system transition dynamics in the human nervous system. These are associated with observably desirable impacts on disorders, injuries, diseases, and athletic performance. Requisite conditions are therapeutic coaching, erect posture, extremely slow movements in mild resistance exercises, and executive control over arousal and attention. To motivate research into the physiological improvements and in validation studies, we integrate from across disciplines to hypothesize explanations for the relationships among the methods, the system dynamics, and evident results. Key hypotheses include: (1) Correctly-directed system efforts may reverse a system's heretofore misdirected efforts, restoring healthier neurophysiology. (2) The enhanced information processing accompanying good posture is an essential initial condition. (3) Behaviors accompanying exercises performed with few degrees of freedom amplify information processing, triggering destabilization and transition dynamics. (4) Executive control over arousal and attention is essential to release system constraints, amplifying and complexifying information. (5) The dynamics create necessary and in many cases evidently sufficient conditions for the body to resolve or improve its own conditions within often short time periods. Literature indicates how the human system possesses material self-awareness. A broad explanation for the nature and effects of the therapy appears rooted in the cascading recursions of the systems' dynamics, which appear to trigger health-fostering self-reorganizing processes when this therapy provides catalytic initial conditions.

Altered resting state brain dynamics in temporal lobe epilepsy can be observed in spectral power, functional connectivity and graph theory metrics

Despite a wealth of EEG epilepsy data that accumulated for over half a century, our ability to understand brain dynamics associated with epilepsy remains limited. Using EEG data from 15 controls and 9 left temporal lobe epilepsy (LTLE) patients, in this study we characterize how the dynamics of the healthy brain differ from the "dynamically balanced" state of the brain of epilepsy patients treated with anti-epileptic drugs in the context of resting state. We show that such differences can be observed in band power, synchronization and network measures, as well as deviations from the small world network (SWN) architecture of the healthy brain. The θ (4-7 Hz) and high α (10-13 Hz) bands showed the biggest deviations from healthy controls across various measures. In particular, patients demonstrated significantly higher power and synchronization than controls in the θ band, but lower synchronization and power in the high α band. Furthermore, differences between controls and patients in graph theory metrics revealed deviations from a SWN architecture. In the θ band epilepsy patients showed deviations toward an orderly network, while in the high α band they deviated toward a random network. These findings show that, despite the focal nature of LTLE, the epileptic brain differs in its global network characteristics from the healthy brain. To our knowledge, this is the only study to encompass power, connectivity and graph theory metrics to investigate the reorganization of resting state functional networks in LTLE patients.

Epileptic neuronal networks: methods of identification and clinical relevance

The main objective of this paper is to examine evidence for the concept that epileptic activity should be envisaged in terms of functional connectivity and dynamics of neuronal networks. Basic concepts regarding structure and dynamics of neuronal networks are briefly described. Particular attention is given to approaches that are derived, or related, to the concept of causality, as formulated by Granger. Linear and non-linear methodologies aiming at characterizing the dynamics of neuronal networks applied to EEG/MEG and combined EEG/fMRI signals in epilepsy are critically reviewed. The relevance of functional dynamical analysis of neuronal networks with respect to clinical queries in focal cortical dysplasias, temporal lobe epilepsies, and "generalized" epilepsies is emphasized. In the light of the concepts of epileptic neuronal networks, and recent experimental findings, the dichotomic classification in focal and generalized epilepsy is re-evaluated. It is proposed that so-called "generalized epilepsies," such as absence seizures, are actually fast spreading epilepsies, the onset of which can be tracked down to particular neuronal networks using appropriate network analysis. Finally new approaches to delineate epileptogenic networks are discussed.