Evolution of interictal activity in models of mesial temporal lobe epilepsy.

Interictal activity and seizures are the hallmarks of focal epileptic disorders (which include mesial temporal lobe epilepsy, MTLE) in humans and in animal models. Interictal activity, which is recorded with cortical and intracerebral EEG recordings, comprises spikes, sharp waves and high-frequency oscillations, and has been used in clinical practice to identify the epileptic zone. However, its relation with seizures remains debated. Moreover, it is unclear whether specific EEG changes in interictal activity occur during the time preceding the appearance of spontaneous seizures. This period, which is termed "latent", has been studied in rodent models of MTLE in which spontaneous seizures start to occur following an initial insult (most often a status epilepticus induced by convulsive drugs such as kainic acid or pilocarpine) and may mirror epileptogenesis, i.e., the process leading the brain to develop an enduring predisposition to seizure generation. Here, we will address this topic by reviewing experimental studies performed in MTLE models. Specifically, we will review data highlighting the dynamic changes in interictal spiking activity and high-frequency oscillations occurring during the latent period, and how optogenetic stimulation of specific cell populations can modulate them in the pilocarpine model. These findings indicate that interictal activity: (i) is heterogeneous in its EEG patterns and thus, presumably, in its underlying neuronal mechanisms; and (ii) can pinpoint to the epileptogenic processes occurring in focal epileptic disorders in animal models and, perhaps, in epileptic patients.

Network-motif delay differential analysis of brain activity during seizures.

Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions.

Quantifying seizure termination patterns reveals limited pathways to seizure end.

OBJECTIVE: Despite their possible importance in the design of novel neuromodulatory approaches and in understanding status epilepticus, the dynamics and mechanisms of seizure termination are not well studied. We examined intracranial recordings from patients with epilepsy to differentiate seizure termination patterns and investigated whether these patterns are indicative of different underlying mechanisms. METHODS: Seizures were classified into one of two termination patterns: (a) those that end simultaneously across the brain (synchronous), and (b) those whose termination is piecemeal across the cortex (asynchronous). Both types ended with either a burst suppression pattern, or continuous seizure activity. These patterns were quantified and compared using burst suppression ratio, absolute energy, and network connectivity. RESULTS: Seizures with electrographic generalization showed burst suppression patterns in 90% of cases, compared with only 60% of seizures which remained focal. Interestingly, we found similar absolute energy and burst suppression ratios in seizures with synchronous and asynchronous termination, while seizures with continuous seizure activity were found to be different from seizures with burst suppression, showing lower energy during seizure and lower burst suppression ratio at the start and end of seizure. Finally, network density was observed to increase with seizure progression, with significantly lower densities in seizures with continuous seizure activity compared to seizures with burst suppression. SIGNIFICANCE: Based on this spatiotemporal classification scheme, we suggest that there are a limited number of seizure termination patterns and dynamics. If this bears out, it would imply that the number of mechanisms underlying seizure termination is also constrained. Seizures with different termination patterns exhibit different dynamics even before their start. This may provide useful clues about how seizures may be managed, which in turn may lead to more targeted modes of therapy for seizure control.

Interictal oscillations and focal epileptic disorders.

Neuronal network oscillations represent a main feature of the brain activity recorded in the EEG under normal and pathological conditions such as epilepsy. Specific oscillations occur between seizures in patients and in animal models of focal epilepsy, and thus, they are termed interictal. According to their shape and intrinsic signal frequency, interictal oscillations are classified as spikes and high-frequency oscillations (HFOs). Interictal spikes are recorded in the 'wideband' EEG signal and consist of large-amplitude events that usually last less than 1 s; HFOs, in contrast, are extracted by amplifying the appropriately filtered EEG signal and are usually categorized as ripples (80-200 Hz) and fast ripples (250-500 Hz). Interictal spikes and HFOs are used in clinical practice to localize the seizure onset zone in focal epileptic disorders, which is fundamental for performing successful surgical interventions in epileptic patients not responding to anti-epileptic drug therapy. Both types of interictal oscillations have been widely studied in animal models of focal epilepsy to identify the mechanisms underlying their generation as well as to establish their role in ictogenesis and epileptogenesis. In this review, we will address the cellular mechanisms underlying the generation of interictal spikes and HFOs in animal models of epileptiform synchronization and of focal epilepsy. Moreover, we will highlight in vitro and in vivo evidence indicating that these interictal oscillations mirror specific, dynamic changes in neuronal network excitability causing seizure generation (i.e. ictogenesis) and leading to a chronic epileptic condition (i.e. epileptogenesis).

Distinct EEG seizure patterns reflect different seizure generation mechanisms.

Low-voltage fast (LVF)- and hypersynchronous (HYP)-seizure onset patterns can be recognized in the EEG of epileptic animals and patients with temporal lobe epilepsy. Ripples (80-200 Hz) and fast ripples (250-500 Hz) have been linked to each pattern, with ripples predominating during LVF seizures and fast ripples predominating during HYP seizures in the rat pilocarpine model. This evidence led us to hypothesize that these two seizure-onset patterns reflect the contribution of neural networks with distinct transmitter signaling characteristics. Here, we tested this hypothesis by analyzing the seizure activity induced with the K(+) channel blocker 4-aminopyridine (4AP, 4-5 mg/kg ip), which enhances both glutamatergic and GABAergic transmission, or the GABAA receptor antagonist picrotoxin (3-5 mg/kg ip); rats were implanted with electrodes in the hippocampus, the entorhinal cortex, and the subiculum. We found that LVF onset occurred in 82% of 4AP-induced seizures whereas seizures after picrotoxin were always HYP. In addition, high-frequency oscillation analysis revealed that 4AP-induced LVF seizures were associated with higher ripple rates compared with fast ripples (P < 0.05), whereas picrotoxin-induced seizures contained higher rates of fast ripples compared with ripples (P < 0.05). These results support the hypothesis that two distinct patterns of seizure onset result from different pathophysiological mechanisms.

Dynamics of interictal spikes and high-frequency oscillations during epileptogenesis in temporal lobe epilepsy.

Mesial temporal lobe epilepsy (MTLE) is characterized in humans and in animal models by a seizure-free latent phase that follows an initial brain insult; this period is presumably associated to plastic changes in temporal lobe excitability and connectivity. Here, we analyzed the occurrence of interictal spikes and high frequency oscillations (HFOs; ripples: 80-200Hz and fast ripples: 250-500Hz) from 48h before to 96h after the first seizure in the rat pilocarpine model of MTLE. Interictal spikes recorded with depth EEG electrodes from the hippocampus CA3 area and entorhinal cortex (EC) were classified as type 1 (characterized by a spike followed by a wave) or type 2 (characterized by a spike with no wave). We found that: (i) there was a switch in the distribution of both types of interictal spikes before and after the occurrence of the first seizure; during the latent phase both types of interictal spikes predominated in the EC whereas during the chronic phase both types of spikes predominated in CA3; (ii) type 2 spike duration decreased in both regions from the latent to the chronic phase; (iii) type 2 spikes associated to fast ripples occurred at higher rates in EC compared to CA3 during the latent phase while they occurred at similar rates in both regions in the chronic phase; and (iv) rates of fast ripples outside of spikes were higher in EC compared to CA3 during the latent phase. Our findings demonstrate that the transition from the latent to the chronic phase is paralleled by dynamic changes in interictal spike and HFO expression in EC and CA3. We propose that these changes may represent biomarkers of epileptogenicity in MTLE.

The Neurostimulationist will see you now: prescribing direct electrical stimulation therapies for the human brain in epilepsy and beyond.

As the pace of research in implantable neurotechnology increases, it is important to take a step back and see if the promise lives up to our intentions. While direct electrical stimulation applied intracranially has been used for the treatment of various neurological disorders, such as Parkinson's, epilepsy, clinical depression, and Obsessive-compulsive disorder, the effectiveness can be highly variable. One perspective is that the inability to consistently treat these neurological disorders in a standardized way is due to multiple, interlaced factors, including stimulation parameters, location, and differences in underlying network connectivity, leading to a trial-and-error stimulation approach in the clinic. An alternate view, based on a growing knowledge from neural data, is that variability in this input (stimulation) and output (brain response) relationship may be more predictable and amenable to standardization, personalization, and, ultimately, therapeutic implementation. In this review, we assert that the future of human brain neurostimulation, via direct electrical stimulation, rests on deploying standardized, constrained models for easier clinical implementation and informed by intracranial data sets, such that diverse, individualized therapeutic parameters can efficiently produce similar, robust, positive outcomes for many patients closer to a prescriptive model. We address the pathway needed to arrive at this future by addressing three questions, namely: (1) why aren't we already at this prescriptive future?; (2) how do we get there?; (3) how far are we from this Neurostimulationist prescriptive future? We first posit that there are limited and predictable ways, constrained by underlying networks, for direct electrical stimulation to induce changes in the brain based on past literature. We then address how identifying underlying individual structural and functional brain connectivity which shape these standard responses enable targeted and personalized neuromodulation, bolstered through large-scale efforts, including machine learning techniques, to map and reverse engineer these input-output relationships to produce a good outcome and better identify underlying mechanisms. This understanding will not only be a major advance in enabling intelligent and informed design of neuromodulatory therapeutic tools for a wide variety of neurological diseases, but a shift in how we can predictably, and therapeutically, prescribe stimulation treatments the human brain.

Differential cortical layer engagement during seizure initiation and spread in humans.

Despite decades of research, we still do not understand how spontaneous human seizures start and spread - especially at the level of neuronal microcircuits. In this study, we used laminar arrays of micro-electrodes to simultaneously record the local field potentials and multi-unit neural activities across the six layers of the neocortex during focal seizures in humans. We found that, within the ictal onset zone, the discharges generated during a seizure consisted of current sinks and sources only within the infra-granular and granular layers. Outside of the seizure onset zone, ictal discharges reflected current flow in the supra-granular layers. Interestingly, these patterns of current flow evolved during the course of the seizure - especially outside the seizure onset zone where superficial sinks and sources extended into the deeper layers. Based on these observations, a framework describing cortical-cortical dynamics of seizures is proposed with implications for seizure localization, surgical targeting, and neuromodulation techniques to block the generation and propagation of seizures.

Two seizure-onset types reveal specific patterns of high-frequency oscillations in a model of temporal lobe epilepsy.

High-frequency oscillations (HFOs; 80-500 Hz) are thought to mirror the pathophysiological changes occurring in epileptic brains. However, the distribution of HFOs during seizures remains undefined. Here, we recorded from the hippocampal CA3 subfield, subiculum, entorhinal cortex, and dentate gyrus to quantify the occurrence of ripples (80-200 Hz) and fast ripples (250-500 Hz) during low-voltage fast-onset (LVF) and hypersynchronous-onset (HYP) seizures in the rat pilocarpine model of temporal lobe epilepsy. We discovered in LVF seizures that (1) progression from preictal to ictal activity was characterized in seizure-onset zones by an increase of ripple rates that were higher when compared with fast ripple rates and (2) ripple rates during the ictal period were higher compared with fast ripple rates in seizure-onset zones and later in regions of secondary spread. In contrast, we found in HYP seizures that (1) fast ripple rates increased during the preictal period and were higher compared with ripple rates in both seizure-onset zones and in regions of secondary spread and (2) they were still higher compared with ripple rates in both seizure-onset zones and regions of secondary spread during the ictal period. Our findings demonstrate that ripples and fast ripples show distinct time- and region-specific patterns during LVF and HYP seizures, thus suggesting that they play specific roles in ictogenesis.

Temporal lobe epileptiform activity following systemic administration of 4-aminopyridine in rats.

PURPOSE: The K(+) channel blocker 4-aminopyridine (4AP) induces epileptiform synchronization in brain slices maintained in vitro without interfering with γ-aminobutyric acid (GABA)A receptor-mediated inhibition and, actually, even enhancing it. The hypothesis that similar electrographic epileptiform patterns occur in vivo following systemic 4AP injection was tested here. METHODS: Sprague-Dawley rats (n = 13) were implanted with bipolar electrodes aimed at the hippocampal CA3 region, entorhinal cortex, subiculum, dentate gyrus, and amygdala. They were then injected with a single dose of 4AP (4-5 mg/kg, i.p.), and video-monitoring/electroencephalography (EEG) recordings were performed. KEY FINDINGS: 4AP induced convulsive or nonconvulsive seizures in 12 of 13 rats, along with generalized fascicular twitching, wet-dog shakes, and myoclonic jerks. On EEG, we observed in 7 (58.3%) of 12 animals long-lasting interictal spikes from the subiculum before the occurrence of the first seizure. Once seizures had started, interictal spikes occurred in all areas with no fixed site of origin. Most seizures (41/60, 68.3%) were characterized by a low-voltage fast-activity onset pattern and were convulsive (48/60, 80%). 4AP also induced highly rhythmic theta (6-11 Hz) oscillations in CA3 and entorhinal cortex before seizure occurrence. SIGNIFICANCE: Our study shows that systemic 4AP administration in vivo can enhance theta oscillations and induce slow interictal spikes and low-voltage fast-onset seizures similar to those reported in brain slices. We propose that these effects may reflect, at least in part, enhanced GABAA receptor-mediated inhibition as reported in in vitro studies.