Distinct patterns of electrical stimulation of the basolateral amygdala influence pentylenetetrazole seizure outcome

Epileptic seizure suppression: A computational approach for identification and control using real data

Epilepsy affects millions of people worldwide every year and remains an open subject for research. Current development on this field has focused on obtaining computational models to better understand its triggering mechanisms, attain realistic descriptions and study seizure suppression. Controllers have been successfully applied to mitigate epileptiform activity in dynamic models written in state-space notation, whose applicability is, however, restricted to signatures that are accurately described by them. Alternatively, autoregressive modeling (AR), a typical data-driven tool related to system identification (SI), can be directly applied to signals to generate more realistic models, and since it is inherently convertible into state-space representation, it can thus be used for the artificial reconstruction and attenuation of seizures as well. Considering this, the first objective of this work is to propose an SI approach using AR models to describe real epileptiform activity. The second objective is to provide a strategy for reconstructing and mitigating such activity artificially, considering non-hybrid and hybrid controllers - designed from ictal and interictal events, respectively. The results show that AR models of relatively low order represent epileptiform activities fairly well and both controllers are effective in attenuating the undesired activity while simultaneously driving the signal to an interictal condition. These findings may lead to customized models based on each signal, brain region or patient, from which it is possible to better define shape, frequency and duration of external stimuli that are necessary to attenuate seizures.

On temporal scale-free non-periodic stimulation and its mechanisms as an infinite improbability drive of the brain's functional connectogram

Rationalized development of electrical stimulation (ES) therapy is of paramount importance. Not only it will foster new techniques and technologies with increased levels of safety, efficacy, and efficiency, but it will also facilitate the translation from basic research to clinical practice. For such endeavor, design of new technologies must dialogue with state-of-the-art neuroscientific knowledge. By its turn, neuroscience is transitioning-a movement started a couple of decades earlier-into adopting a new conceptual framework for brain architecture, in which time and thus temporal patterns plays a central role in the neuronal representation of sampled data from the world. This article discusses how neuroscience has evolved to understand the importance of brain rhythms in the overall functional architecture of the nervous system and, consequently, that neuromodulation research should embrace this new conceptual framework. Based on such support, we revisit the literature on standard (fixed-frequency pulsatile stimuli) and mostly non-standard patterns of ES to put forward our own rationale on how temporally complex stimulation schemes may impact neuromodulation strategies. We then proceed to present a low frequency, on average (thus low energy), scale-free temporally randomized ES pattern for the treatment of experimental epilepsy, devised by our group and termed NPS (Non-periodic Stimulation). The approach has been shown to have robust anticonvulsant effects in different animal models of acute and chronic seizures (displaying dysfunctional hyperexcitable tissue), while also preserving neural function. In our understanding, accumulated mechanistic evidence suggests such a beneficial mechanism of action may be due to the natural-like characteristic of a scale-free temporal pattern that may robustly compete with aberrant epileptiform activity for the recruitment of neural circuits. Delivering temporally patterned or random stimuli within specific phases of the underlying oscillations (i.e., those involved in the communication within and across brain regions) could both potentiate and disrupt the formation of neuronal assemblies with random probability. The usage of infinite improbability drive here is obviously a reference to the "The Hitchhiker's Guide to the Galaxy" comedy science fiction classic, written by Douglas Adams. The parallel is that dynamically driving brain functional connectogram, through neuromodulation, in a manner that would not favor any specific neuronal assembly and/or circuit, could re-stabilize a system that is transitioning to fall under the control of a single attractor. We conclude by discussing future avenues of investigation and their potentially disruptive impact on neurotechnology, with a particular interest in NPS implications in neural plasticity, motor rehabilitation, and its potential for clinical translation.

Estimating the Parameters of the Epileptor Model for Epileptic Seizure Suppression

Epilepsy is one of the most common brain disorders worldwide, affecting millions of people every year. Given the partially successful existing treatments for epileptiform activity suppression, dynamic mathematical models have been proposed with the purpose of better understanding the factors that might trigger an epileptic seizure and how to mitigate it, among which Epileptor stands out, due to its relative simplicity and consistency with experimental observations. Recent studies using this model have provided evidence that establishing a feedback-based control approach is possible. However, for this strategy to work properly, Epileptor's parameters, which describe the dynamic characteristics of a seizure, must be known beforehand. Therefore, this work proposes a methodology for estimating such parameters based on a successive optimization technique. The results show that it is feasible to approximate their values as they converge to reference values based on different initial conditions, which are modeled by an uncertainty factor or noise addition. Also, interictal (healthy) and ictal (ongoing seizure) conditions, as well as time resolution, must be taken into account for an appropriate estimation. At last, integrating such a parameter estimation approach with observers and controllers for purposes of seizure suppression is carried out, which might provide an interesting alternative for seizure suppression in practice in the future.

Persistence of neural function in animals submitted to seizure-suppressing scale-free nonperiodic electrical stimulation applied to the amygdala

Based on the rationale that neural hypersynchronization underlies epileptic phenomena, nonperiodic stimulation (NPS) was designed and successfully tested as an electrical stimulus with robust anticonvulsant action. Considering the scale-free temporal structure of NPS mimics natural-like activity, here we hypothesized its application to the amygdala would induce minor to none impairment of neural function in treated animals. Wistar rats underwent gold-standard behavioral tests such as open field (OF), elevated plus-maze (EPM), novel object recognition, and social interaction test in order to evaluate the functions of base-level anxiety, motor function, episodic memory, and sociability. We also performed daily (8 days, 6 h per day) electrophysiological recordings (local field potential/LFP and electromyography) to assess global forebrain dynamics and the sleep-wake cycle architecture and integrity. All animals displayed an increased proportion of time exploring new objects, spent more time in the closed arms of the EPM and in the periphery of the OF arena, with similar numbers of crossing between quadrants and no significant changes of social behaviors. In the sleep-wake cycle electrophysiology experiments, we found no differences regarding duration and proportion of sleep stages and the number of transitions between stages. Finally, the power spectrum of LFP recordings and neurodynamics were also unaltered. We concluded that NPS did not impair neural functions evaluated and thus, it may be safe for clinical studies. Additionally, results corroborate the notion that NPS may exert an on-demand only desynchronization effect by efficiently competing with epileptiform activity for the physiological and healthy recruitment of neural circuitry. Considering the very dynamical nature of circuit activation and functional activity underlying neural function in general (including cognition, processing of emotion, memory acquisition, and sensorimotor integration) and its corruption leading to disorder, such mechanism of action may have important implications in the investigation of neuropsychological phenomena and also in the development of rehabilitation neurotechnology.

Survival analysis of nonperiodic stimulation (NPS) performance

Electrical Stimulation (ES) of the nervous system is a promising alternative to treat refractory epilepsy. Recent developments in the area have led to a novel method involving a non-standard form of electrical stimulation with randomized inter-pulse intervals called non-periodic stimulation (NPS). Although it is an interesting approach, there is limited statistical proof to confirm its effectiveness. Therefore this brief communication presents a survival analysis of a pre-clinical trial to assess the significance of NPS therapy. The experiment comprised four groups of rats that have been compared: two with and two without NPS treatment. ES was applied bilaterally to the amygdala in animals subjected to the pentylenetetrazole continuous infusion (10 mg/ml/min) model, myoclonic or tonic-clonic generalized seizures were triggered. The Kaplan-Meier estimator was used to develop survival functions and the Logrank test was carried out to check the differences among groups. The first comparison was made between two groups of rats that developed generalized tonic-clonic seizures (GTC groups), those who received NPS treatment took longer to develop epileptic seizures. The logrank test proved statistical difference due to reaching a p-value of 7%. The second comparison was performed between two groups of rats that developed myoclonic seizures (MYO groups), and once again better survival probabilities were observed for the NPS group. The Logrank test revealed a p-value of 0.5% thereof. Thus, a survival analysis of NPS treatment proved effectiveness against seizures by promoting an anticonvulsant effect. By comparing the groups selected for this study, it was found that the NPS treatment yielded better results, mainly against myoclonic seizures.

Epilepsy as a dynamical system, a most needed paradigm shift in epileptology

The idea of the epileptic brain being highly excitable and facilitated to synchronic activity has guided pharmacological treatment since the early twentieth century. Although tackling epilepsy's seizure-prone feature, by tonically modifying overall circuit excitability and/or connectivity, the last 50 years of drug development has not seen a substantial improvement in seizure suppression of refractory epilepsies. This review presents a new conceptual framework for epilepsy in which the temporal dynamics of the disease plays a more critical role in both its understanding and therapeutic strategies. The repetitive epileptiform pattern (characteristic during ictal activity) and other well-defined electrographic signatures (i.e., present during the interictal period) are discussed in terms of the sequential activation of the circuit motifs. Lessons learned from the physiological activation of neural circuitry are used to further corroborate the argument and explore the transition from proper function to a state of instability. Furthermore, the review explores how interfering in the temporally dependent abnormal connectivity between circuits may work as a therapeutic approach. We also review the use of probing stimulation to access network connectivity and evaluate its power to determine transitional states of the dynamical system as it moves towards regions of instability, especially when conventional electrographic monitoring is proven inefficient. Unorthodox cases, with little or no scalp electrographic correlate, in which ictogenic circuitry and/or seizure spread is temporally restricted to neurovegetative, cognitive, and motivational areas are shown as possible explanations for sudden death in epilepsy (SUDEP) and other psychiatric comorbidities. In short, this review presents a paradigm shift in the way that we address the disease and is aimed to encourage debate rather than narrow the rationale epilepsy is currently engaged in. This article is part of the Special Issue "NEWroscience 2018".

Nonperiodic stimulation for the treatment of refractory epilepsy: Applications, mechanisms, and novel insights

Electrical stimulation of the central nervous system is a promising alternative for the treatment of pharmacoresistant epilepsy. Successful clinical and experimental stimulation is most usually carried out as continuous trains of current or voltage pulses fired at rates of 100 Hz or above, since lower frequencies yield controversial results. On the other hand, stimulation frequency should be as low as possible, in order to maximize implant safety and battery efficiency. Moreover, the development of stimulation approaches has been largely empirical in general, while they should be engineered with the neurobiology of epilepsy in mind if a more robust, efficient, efficacious, and safe application is intended. In an attempt to reconcile evidence of therapeutic effect with the understanding of the underpinnings of epilepsy, our group has developed a nonstandard form of low-frequency stimulation with randomized interpulse intervals termed nonperiodic stimulation (NPS). The rationale was that an irregular temporal pattern would impair neural hypersynchronization, which is a hallmark of epilepsy. In this review, we start by briefly revisiting the literature on the molecular, cellular, and network level mechanisms of epileptic phenomena in order to highlight this often-overlooked emergent property of cardinal importance in the pathophysiology of the disease. We then review our own studies on the efficacy of NPS against acute and chronic experimental seizures and also on the anatomical and physiological mechanism of the method, paying special attention to the hypothesis that the lack of temporal regularity induces desynchronization. We also put forward a novel insight regarding the temporal structure of NPS that may better encompass the set of findings published by the group: the fact that intervals between stimulation pulses have a distribution that follows a power law and thus may induce natural-like activity that would compete with epileptiform discharge for the recruitment of networks. We end our discussion by mentioning ongoing research and future projects of our lab.

Adjust Neuronal Reactions to Pulses of High-Frequency Stimulation with Designed Inter-Pulse-Intervals in Rat Hippocampus In Vivo

Sequences of electrical pulses have been applied in the brain to treat certain disorders. In recent years, altering inter-pulse-interval (IPI) regularly or irregularly in real time has emerged as a promising way to modulate the stimulation effects. However, algorithms to design IPI sequences are lacking. This study proposed a novel strategy to design pulse sequences with varying IPI based on immediate neuronal reactions. Firstly, to establish the correlationship between the neuronal reactions with varying IPIs, high-frequency stimulations with varying IPI in the range of 5–10 ms were applied at the alveus of the hippocampal CA1 region of anesthetized rats in vivo. Antidromically-evoked population spikes (APS) following each IPI were recorded and used as a biomarker to evaluate neuronal reactions to each pulse. A linear mapping model was established to estimate the varied APS amplitudes by the two preceding IPIs. Secondly, the mapping model was used to derive an algorithm for designing an IPI sequence that would be applied for generating a desired neuronal reaction pre-defined by a particular APS distribution. Finally, examples of stimulations with different IPI sequences designed by the algorithm were verified by rat experiments. The results showed that the designed IPI sequences were able to reproduce the desired APS responses of different distributions in the hippocampal stimulations. The novel algorithm of IPI design provides a potential way to obtain various stimulation effects for brain stimulation therapies.

Amygdala Low-Frequency Stimulation Reduces Pathological Phase-Amplitude Coupling in the Pilocarpine Model of Epilepsy

Temporal-lobe epilepsy (TLE) is the most common type of drug-resistant epilepsy and warrants the development of new therapies, such as deep-brain stimulation (DBS). DBS was applied to different brain regions for patients with epilepsy; however, the mechanisms of action are not fully understood. Therefore, we tried to characterize the effect of amygdala DBS on hippocampal electrical activity in the lithium-pilocarpine model in male Wistar rats. After status epilepticus (SE) induction, seizure patterns were determined based on continuous video recordings. Recording electrodes were inserted in the left and right hippocampus and a stimulating electrode in the left basolateral amygdala of both Pilo and age-matched control rats 10 weeks after SE. Daily stimulation protocol consisted of 4 × 50 s stimulation trains (4-Hz, regular interpulse interval) for 10 days. The hippocampal electroencephalogram was analyzed offline: interictal epileptiform discharge (IED) frequency, spectral analysis, and phase-amplitude coupling (PAC) between delta band and higher frequencies were measured. We found that the seizure rate and duration decreased (by 23% and 26.5%) and the decrease in seizure rate correlated negatively with the IED frequency. PAC was elevated in epileptic animals and DBS reduced the pathologically increased PAC and increased the average theta power (25.9% ± 1.1 vs. 30.3% ± 1.1; p < 0.01). Increasing theta power and reducing the PAC could be two possible mechanisms by which DBS may exhibit its antiepileptic effect in TLE; moreover, they could be used to monitor effectiveness of stimulation.

The Endocannabinoid System Activation as a Neural Network Desynchronizing Mediator for Seizure Suppression

The understanding that hyper-excitability and hyper-synchronism in epilepsy are indissociably bound by a cause-consequence relation has only recently been challenged. Thus, therapeutic strategies for seizure suppression have often aimed at inhibiting excitatory circuits and/or activating inhibitory ones. However, new approaches that aim to desynchronize networks or compromise abnormal coupling between adjacent neural circuitry have been proven effective, even at the cost of enhancing local neuronal activation. Although most of these novel perspectives targeting circuitry desynchronization and network coupling have been implemented by non-pharmacological devices, we argue that there may be endogenous neurochemical systems that act primarily in the desynchronization component of network behavior rather than dampening excitability of individual neurons. This review explores the endocannabinoid system as one such possible pharmacological landmark for mimicking a form of "on-demand" desynchronization analogous to those proposed by deep brain stimulation in the treatment of epilepsy. This essay discusses the evidence supporting the role of the endocannabinoid system in modulating the synchronization and/or coupling of distinct local neural circuitry; which presents obvious implications on the physiological setting of proper sensory-motor integration. Accordingly, the process of ictogenesis involves pathological circuit coupling that could be avoided, or at least have its spread throughout the containment of other areas, if such endogenous mechanisms of control could be activated or potentiated by pharmacological intervention. In addition, we will discuss evidence that supports not only a weaker role played on neuronal excitability but the potential of the endocannabinoid system strengthening its modulatory effect, only when circuitry coupling surpasses a level of activation.

An Efficient Approach to Define the Input Stimuli to Suppress Epileptic Seizures Described by the Epileptor Model

Epilepsy affects about 70 million people in the world. Every year, approximately 2.4 million people are diagnosed with epilepsy, two-thirds of them will not know the etiology of their disease, and 1% of these individuals will decease as a consequence of it. Due to the inherent complexity of predicting and explaining it, the mathematical model Epileptor was recently developed to reproduce seizure-like events, also providing insights to improve the understanding of the neural dynamics in the interictal and ictal periods, although the physics behind each parameter and variable of the model is not fully established in the literature. This paper introduces an approach to design a feedback-based controller for suppressing epileptic seizures described by Epileptor. Our work establishes how the nonlinear dynamics of this disorder can be written in terms of a combination of linear sub-models employing an exact solution. Additionally, we show how a feedback control gain can be computed to suppress seizures, as well as how specific shapes applied as input stimuli for this purpose can be obtained. The practical application of the approach is discussed and the results show that the proposed technique is promising for developing controllers in this field.

The Appearance Order of Varying Intervals Introduces Extra Modulation Effects on Neuronal Firing Through Non-linear Dynamics of Sodium Channels During High-Frequency Stimulations

Electrical pulse stimulation in the brain has shown success in treating several brain disorders with constant pulse frequency or constant inter-pulse interval (IPI). Varying IPI may offer a variety of novel stimulation paradigms and may extend the clinical applications. However, a lack of understanding of neuronal responses to varying IPI limits its informed applications. In this study, to investigate the effects of varying IPI, we performed both rat experiments and computational modeling by applying high-frequency stimulation (HFS) to efferent axon fibers of hippocampal pyramidal cells. Antidromically evoked population spikes (PSs) were used to evaluate the neuronal responses to pulse stimulations with different IPI patterns including constant IPI, gradually varying IPI, and randomly varying IPI. All the varying IPI sequences were uniformly distributed in the same interval range of 10 to 5 ms (i.e., 100 to 200 Hz). The experimental results showed that the mean correlation coefficient of PS amplitudes to the lengths of preceding IPI during HFS with random IPI (0.72 ± 0.04, n = 7 rats) was significantly smaller than the corresponding correlation coefficient during HFS with gradual IPI (0.92 ± 0.03, n = 7 rats, P < 0.001, t-test). The PS amplitudes induced by the random IPI covered a wider range, over twice as much as that induced by the gradual IPI, indicating additional effects induced by merely changing the appearance order of IPI. The computational modeling reproduced these experimental results and provided insights into these modulatory effects through the mechanism of non-linear dynamics of sodium channels and potassium accumulation in the narrow peri-axonal space. The simulation results showed that the HFS-induced increase of extracellular potassium ([K⁺] _o ) elevated the membrane potential of axons, delayed the recovery course of sodium channels that were repeatedly activated and inactivated during HFS, and resulted in intermittent neuronal firing. Because of non-linear membrane dynamics, random IPI recruited more neurons to fire together following specific sub-sequences of pulses than gradual IPI, thereby widening the range of PS amplitudes. In conclusion, the study demonstrated novel HFS effects of neuronal modulation induced by merely changing the appearance order of the same group of IPI of pulses, which may inform the development of new stimulation patterns to meet different demands for treating various brain diseases.

Temporally irregular electrical stimulation to the epileptogenic focus delays epileptogenesis in rats

BACKGROUND

Variation in the temporal patterns of electrical pulses in stimulation trains has opened a new field of opportunity for the treatment of neurological disorders, such as pharmacoresistant temporal lobe epilepsy. Whether this novel type of stimulation affects epileptogenesis remains to be investigated.

OBJECTIVE

The purpose of this study was to analyze the effects of temporally irregular deep brain stimulation on kindling-induced epileptogenesis in rats.

METHODS

Temporally irregular deep brain stimulation was delivered at different times with respect to the kindling stimulation. Behavioral and electrographic changes on kindling acquisition were compared with a control group and a temporally regular deep brain stimulation-treated group. The propagation of epileptiform activity was analyzed with wavelet cross-correlation analysis, and interictal epileptiform discharge ratios were obtained.

RESULTS

Temporally irregular deep brain stimulation delivered in the epileptogenic focus during the interictal period shortened the daily afterdischarge duration, slowed the progression of seizure stages, diminished the generalized seizure duration and interfered with the propagation of epileptiform activity from the seizure onset zone to the ipsi- and contralateral motor cortex. We also found a negative correlation between seizure severity and interictal epileptiform discharges in rats stimulated with temporally irregular deep brain stimulation.

CONCLUSION

These results provide evidence that temporally irregular deep brain stimulation interferes with the establishment of epilepsy by delaying epileptogenesis by almost twice as long in kindling animals. Thus, temporally irregular deep brain stimulation could be a preventive approach against epilepsy.

Bistable Firing Pattern in a Neural Network Model

Excessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronization originating from a pattern of desynchronized spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures.

Deep brain stimulation probing performance is enhanced by pairing stimulus with epileptic seizure

The unpredictability of spontaneous and recurrent seizures significantly impairs the quality of life of patients with epilepsy. Probing neural network excitability with deep brain electrical stimulation (DBS) has shown promising results predicting pathological shifts in brain states. This work presents a proof-of-principal that active electroencephalographic (EEG) probing, as a seizure predictive tool, is enhanced by pairing DBS and the electrographic seizure itself. The ictogenic model used consisted of inducing seizures by continuous intravenous infusion of pentylenetetrazol (PTZ - 2.5 mg/ml/min) while a probing DBS was delivered to the thalamus (TH) or amygdaloid complex to detect changes prior to seizure onset. Cortical electrophysiological recordings were performed before, during, and after PTZ infusion. Thalamic DBS probing, but not amygdaloid, was able to predict seizure onset without any observable proconvulsant effects. However, previously pairing amygdaloid DBS and epileptic polyspike discharges (day-1) elicited distinct preictal cortically recorded evoked response (CRER) (day-2) when compared with control groups that received the same amount of electrical pulses at different moments of the ictogenic progress at day-1. In conclusion, our results have demonstrated that the pairing strategy potentiated the detection of an altered brain state prior to the seizure onset. The EEG probing enhancement method opens many possibilities for both diagnosis and treatment of epilepsy.

Axonal Stimulations With a Higher Frequency Generate More Randomness in Neuronal Firing Rather Than Increase Firing Rates in Rat Hippocampus

Deep brain stimulation (DBS) has been used for treating many brain disorders. Clinical applications of DBS commonly require high-frequency stimulations (HFS, ∼100 Hz) of electrical pulses to obtain therapeutic efficacy. It is not clear whether the electrical energy of HFS functions other than generating firing of action potentials in neuronal elements. To address the question, we investigated the reactions of downstream neurons to pulse sequences with a frequency in the range 50-200 Hz at afferent axon fibers in the hippocampal CA1 region of anesthetized rats. The results show that the mean rates of neuronal firing induced by axonal HFS were similar even for an up to fourfold difference (200:50) in the number and thereby in the energy of electrical pulses delivered. However, HFS with a higher pulse frequency (100 or 200 Hz) generated more randomness in the firing pattern of neurons than a lower pulse frequency (50 Hz), which were quantitatively evaluated by the significant changes of two indexes, namely, the peak coefficients and the duty ratios of excitatory phase of neuronal firing, induced by different frequencies (50-200 Hz). The findings indicate that a large portion of the HFS energy might function to generate a desynchronization effect through a possible mechanism of intermittent depolarization block of neuronal membranes. The present study addresses the demand of high frequency for generating HFS-induced desynchronization in neuronal activity, which may play important roles in DBS therapy.

The epileptic amygdala: Toward the development of a neural prosthesis by temporally coded electrical stimulation

Many patients with epilepsy do not obtain proper control of their seizures through conventional treatment. We review aspects of the pathophysiology underlying epileptic phenomena, with a special interest in the role of the amygdala, stressing the importance of hypersynchronism in both ictogenesis and epileptogenesis. We then review experimental studies on electrical stimulation of mesiotemporal epileptogenic areas, the amygdala included, as a means to treat medically refractory epilepsy. Regular high-frequency stimulation (HFS) commonly has anticonvulsant effects and sparse antiepileptogenic properties. On the other hand, HFS is related to acute and long-term increases in excitability related to direct neuronal activation, long-term potentiation, and kindling, raising concerns regarding its safety and jeopardizing in-depth understanding of its mechanisms. In turn, the safer regular low-frequency stimulation (LFS) has a robust antiepileptogenic effect, but its pro- or anticonvulsant effect seems to vary at random among studies. As an alternative, studies by our group on the development and investigation of temporally unstructured electrical stimulation applied to the amygdala have shown that nonperiodic stimulation (NPS), which is a nonstandard form of LFS, is capable of suppressing both acute and chronic spontaneous seizures. We hypothesize two noncompetitive mechanisms for the therapeutic role of amygdala in NPS, 1) a direct desynchronization of epileptic circuitry in the forebrain and brainstem and 2) an indirect desynchronization/inhibition through nucleus accumbens activation. We conclude by reintroducing the idea that hypersynchronism, rather than hyperexcitability, may be the key for epileptic phenomena and epilepsy treatment.

Preventive and Abortive Strategies for Stimulation Based Control of Epilepsy: A Computational Model Study

Epilepsy is a condition in which periods of ongoing normal EEG activity alternate with periods of oscillatory behavior characteristic of epileptic seizures. The dynamics of the transitions between the two states are still unclear. Computational models provide a powerful tool to explore the underlying mechanisms of such transitions, with the purpose of eventually finding therapeutic interventions for this debilitating condition. In this study, the possibility to postpone seizures elicited by a decrease of inhibition is investigated by using external stimulation in a realistic bistable neuronal model consisting of two interconnected neuronal populations representing pyramidal cells and interneurons. In the simulations, seizures are induced by slowly decreasing the conductivity of GABA[Formula: see text] synaptic channels over time. Since the model is bistable, the system will change state from the initial steady state (SS) to the limit cycle (LS) state because of internal noise, when the inhibition falls below a certain threshold. Several state-independent stimulations paradigms are simulated. Their effectiveness is analyzed for various stimulation frequencies and intensities in combination with periodic and random stimulation sequences. The distributions of the time to first seizure in the presence of stimulation are compared with the situation without stimulation. In addition, stimulation protocols targeted to specific subsystems are applied with the objective of counteracting the baseline shift due to decreased inhibition in the system. Furthermore, an analytical model is used to investigate the effects of random noise. The relation between the strength of random noise stimulation, the control parameter of the system and the transitions between steady state and limit cycle are investigated. The study shows that it is possible to postpone epileptic activity by targeted stimulation in a realistic neuronal model featuring bistability and that it is possible to stop seizures by random noise in an analytical model.

Rapid brief feedback intracerebral stimulation based on real-time desynchronization detection preceding seizures stops the generation of convulsive paroxysms

OBJECTIVE

To investigate the abortion of seizure generation using "minimal" intervention in hippocampi using two rat models of human temporal lobe epilepsy.

METHODS

The recording or stimulation electrodes were implanted into both hippocampi (CA1 area). Using the kainic acid (chronic: experiment duration 24 days) and the 4-aminopyridine (acute: experiment duration 2 h) models of paroxysms in rats, a real-time feedback stimulation paradigm was implemented, which triggered a short periodic electrical stimulus (5 Hz for 5 s) upon detecting a seizure precursor. Our seizure precursor detection algorithm relied on the monitoring of the real-time phase synchronization analysis, and detected/anticipated electrographic seizures as early as a few seconds to a few minutes before the behavioral and electrographic seizure onset, with a very low false-positive rate of the detection.

RESULTS

The baseline mean seizure frequencies were 5.39 seizures per day (chronic) and 13.2 seizures per hour (acute). The phase synchrony analysis detected 88% (434 of 494) of seizures with a mean false alarm of 0.67 per day (chronic) and 83% (86 of 104) of seizures with a mean false alarm of 0.47 per hour (acute). The feedback stimulation reduced the seizure frequencies to 0.41 seizures per day (chronic) and 2.4 seizures per hour (acute). Overall, the feedback stimulation paradigm reduced seizure frequency by a minimum of 80% to a maximum of 100% in 10 rats, with 83% of the animals rendered seizure-free.

SIGNIFICANCE

This approach represents a simple and efficient manner for stopping seizure development. Because of the short on-demand stimuli, few or no associated side effects are expected in clinical application in patients with epilepsy. Abnormal synchrony patterns are common features in epilepsy and other neurologic and psychiatric syndromes; therefore, this type of feedback stimulation paradigm could be a novel therapeutic modality for use in various neurologic and psychiatric disorders.

Triggering Different Brain States Using Asynchronous Serial Communication to the Rat Amygdala

Inputting information to the brain through direct electrical microstimulation must consider how underlying neural networks encode information. One unexplored possibility is that a single electrode delivering temporally coded stimuli, mimicking an asynchronous serial communication port to the brain, can trigger the emergence of different brain states. This work used a discriminative fear-conditioning paradigm in rodents in which 2 temporally coded microstimulation patterns were targeted at the amygdaloid complex. Each stimulus was a binary-coded "word" made up of 10 ms bins, with 1's representing a single pulse stimulus: A-1001111001 and B-1110000111. During 3 consecutive retention tests (i.e., day-word: 1-B; 2-A, and 3-B), only binary-coded words previously paired with a foot-electroshock elicited proper aversive behavior. To determine the neural substrates recruited by the different stimulation patterns, c-Fos expression was evaluated 90 min after the last retention test. Animals conditioned to word-B, after stimulation with word-B, demonstrated increased hypothalamic c-Fos staining. Animals conditioned to word-A, however, showed increased prefrontal c-Fos labeling. In addition, prefrontal-cortex and hypothalamic c-Fos staining for, respectively, word-B- and word-A-conditioned animals, was not different than that of an unpaired control group. Our results suggest that, depending on the valence acquired from previous learning, temporally coded microstimulation activates distinct neural networks and associated behavior.

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.

MULTIPLE OSCILLATORY STATES IN MODELS OF COLLECTIVE NEURONAL DYNAMICS

In our previous studies, we showed that the both realistic and analytical computational models of neural dynamics can display multiple sustained states (attractors) for the same values of model parameters. Some of these states can represent normal activity while other, of oscillatory nature, may represent epileptic types of activity. We also showed that a simplified, analytical model can mimic this type of behavior and can be used instead of the realistic model for large scale simulations. The primary objective of the present work is to further explore the phenomenon of multiple stable states, co-existing in the same operational model, or phase space, in systems consisting of large number of interconnected basic units. As a second goal, we aim to specify the optimal method for state control of the system based on inducing state transitions using appropriate external stimulus. We use here interconnected model units that represent the behavior of neuronal populations as an effective dynamic system. The model unit is an analytical model (S. Kalitzin et al., Epilepsy Behav. 22 (2011) S102–S109) and does not correspond directly to realistic neuronal processes (excitatory–inhibitory synaptic interactions, action potential generation). For certain parameter choices however it displays bistable dynamics imitating the behavior of realistic neural mass models. To analyze the collective behavior of the system we applied phase synchronization analysis (PSA), principal component analysis (PCA) and stability analysis using Lyapunov exponent (LE) estimation. We obtained a large variety of stable states with different dynamic characteristics, oscillatory modes and phase relations between the units. These states can be initiated by appropriate initial conditions; transitions between them can be induced stochastically by fluctuating variables (noise) or by specific inputs. We propose a method for optimal reactive control, allowing forced transitions from one state (attractor) into another.

Temporally unstructured electrical stimulation to the amygdala suppresses behavioral chronic seizures of the pilocarpine animal model

Electrical stimulation applied to the basolateral amygdala in the pentylenetetrazole animal model of seizures may result in either a proconvulsant or an anticonvulsant effect depending on the interpulse intervals used: periodic or nonperiodic, respectively. We tested the effect of this electrical stimulation temporal coding on the spontaneous and recurrent behavioral seizures produced in the chronic phase of the pilocarpine animal model of temporal lobe epilepsy, an experimental protocol that better mimics the human condition. After 45 days of the pilocarpine-induced status epilepticus, male Wistar rats were submitted to a surgical procedure for the implantation of a bipolar electrical stimulation electrode in the right basolateral amygdala and were allowed to recover for seven days. The animals were then placed in a glass box, and their behaviors were recorded daily on DVD for 6h for 4 consecutive days (control period). Spontaneous recurrent behavioral seizures when showed in animals were further recorded for an extra 4-day period (treatment period), under periodic or nonperiodic electrical stimulation. The number, duration, and severity of seizures (according to the modified Racine's scale) during treatment were compared with those during the control period. The nonperiodically stimulated group displayed a significantly reduced total number and duration of seizures. There was no difference between control and treatment periods for the periodically stimulated group. Results corroborate previous findings from our group showing that nonperiodic electrical stimulation has a robust anticonvulsant property. In addition, results from the pilocarpine animal model further strengthen nonperiodic electrical stimulation as a valid therapeutic approach in current medical practice. Our working hypothesis is that temporally unstructured electrical stimulation may wield its effect by desynchronizing neural networks involved in the ictogenic process.

Anticonvulsant effects of N-arachidonoyl-serotonin, a dual fatty acid amide hydrolase enzyme and transient receptor potential vanilloid type-1 (TRPV1) channel blocker, on experimental seizures: the roles of cannabinoid CB1 receptors and TRPV1 channels

Selective blockade of anandamide hydrolysis, through the inhibition of the FAAH enzyme, has anticonvulsant effects, which are mediated by CB1 receptors. Anandamide, however, also activates TRPV1 channels, generally with an opposite outcome on neuronal modulation. Thus, we suggested that the dual FAAH and TRPV1 blockade with N-arachidonoyl-serotonin (AA-5-HT) would be efficacious in inhibiting pentylenetetrazole (PTZ)-induced seizures in mice. We also investigated the contribution of CB1 activation and TRPV1 blockade to the overt effect of AA-5-HT. In the first experiment, injection of AA-5-HT (0.3-3.0 mg/kg) delayed the onset and reduced the duration of PTZ (60 mg)-induced seizures in mice. These effects were reversed by pre-treatment with the CB1 antagonist, AM251 (1.0-3.0 mg/kg). Finally, we observed that administration of the selective TRPV1 antagonist, SB366791 (0.1-1 mg/kg), did not entirely mimic AA-5-HT effects. In conclusion, AA-5-HT alleviates seizures in mice, an effect inhibited by CB1 antagonism, but not completely mimicked by TRPV1 blockage, indicating that the overall effect of AA-5-HT seems to depend mainly on CB1 receptors. This may represent a new strategy for the development of drugs against seizures, epilepsies and related syndromes.

Temporal rearrangement of pre-ictal PTZ induced spike discharges by low frequency electrical stimulation to the amygdaloid complex

BACKGROUND

Epilepsy is a common neurological disease affecting over 40 million people worldwide. The foremost important challenge of epileptologists has been to control and predict the recurrent and spontaneous seizures of epileptic patients. The application of low frequency electrical stimulation (LFS) in deep brain structures has shown promising results in seizure control. However, the use of LFS as a probing strategy for seizure prediction, thus contributing to a closed loop solution, is still poorly explored.

OBJECTIVE

To improve seizure prediction by producing gradually increasing phase-locked pre-ictal electrographical responses, due to the short-term plastic changes in epileptogenic neural networks, thus behaving as a "programmed" surrogate marker.

METHODS

Urethane anesthetized rats were divided into 3 groups: the PTZ-noES group was injected with pentylenetetrazole (PTZ 4 mg/ml/min flow rate) i.v. without electrical stimulation (ES); the ES-noPTZ group received ES (0.5 Hz, 0.1 ms pulse width and 0.6 mA) to the amygdaloid complex and the PTZ + ES group received simultaneously i.v. PTZ infusion and ES. After each condition, electrographical parameters and c-Fos expression of regions of interest were evaluated.

RESULTS

Although the PTZ + ES group had no evident change in the sustained electrographic seizure onset, duration and/or frequency spectrum; c-Fos labeling showed a different expression pattern when compared to the PTZ-noES and ES-noPTZ. Also, PTZ + ES formed a gradually increasing evoked potential; confirming the strong coupling of reverberant neural networks induced by ES - phase locked to stimuli.

CONCLUSION

ES induces a detectable temporal rearrangement of pre-ictal activity, which has suggestive applicability to seizure prediction.

SaBer DBS: a fully programmable, rechargeable, bilateral, charge-balanced preclinical microstimulator for long-term neural stimulation

To effectively study the mechanisms by which deep brain stimulation (DBS) produces its therapeutic benefit and to evaluate new therapeutic indications, it is vital to administer DBS over an extended period of time in awake, freely behaving animals. To date multiple preclinical stimulators have been designed and described. However, these stimulators have failed to incorporate some of the design criteria necessary to provide a system analogous to those used clinically. Here we define these design criteria and propose an improved and complete preclinical DBS system. This system is fully programmable in frequency, pulse-width and current amplitude, has a rechargeable battery and delivers biphasic, charge-balanced output to two independent electrodes. The system has been optimized for either implantation or for use externally via attachment to rodent jackets.

Anatomically dependent anticonvulsant properties of temporally-coded electrical stimulation

In the PTZ animal model of epilepsy, electrical stimulation applied to the amygdaloid complex may result in either pro-convulsive or anticonvulsant effect, depending on the temporal pattern used (i.e. periodic-PS and non-periodic-NPS electrical stimulation). Our hypothesis is that the anatomical target is a determinant factor for the differential effect of temporally-coded patterns on seizure outcome. The threshold dose of PTZ to elicit forelimb clonus and generalized tonic-clonic seizure behavior was measured. The effect of amygdaloid complex PS on forelimb clonus threshold showed a pro-convulsive effect while NPS was anticonvulsant. NPS also significantly increased generalized tonic-clonic threshold; while PS, although at lower threshold levels, did not present statistical significance. Thalamus stimulation did not affect forelimb clonus threshold and showed similar anticonvulsant profiles for both PS and NPS on generalized tonic-clonic threshold. In summary, the anatomical target is a determinant factor on whether temporally-coded ES differentially modulates seizure outcome.

CLOSED-LOOP SEIZURE CONTROL WITH VERY HIGH FREQUENCY ELECTRICAL STIMULATION AT SEIZURE ONSET IN THE GAERS MODEL OF ABSENCE EPILEPSY

A closed-loop system for the automated detection and control of epileptic seizures was created and tested in three Genetic Absence Epilepsy Rats from Strasbourg (GAERS) rats. In this preliminary study, a set of four EEG features were used to detect seizures and three different electrical stimulation strategies (standard (130 Hz), very high (500 Hz) and ultra high (1000 Hz)) were delivered to terminate seizures. Seizure durations were significantly shorter with all three stimulation strategies when compared to non-stimulated (control) seizures. We used mean seizure duration of epileptiform discharges persisting beyond the end of electrical stimulation as a measure of stimulus efficacy. When compared to the duration of seizures stimulated in the standard approach (7.0 s ± 10.1), both very high and ultra high frequency stimulation strategies were more effective at shortening seizure durations (1.3 ± 2.2 s and 3.5 ± 6.4 s respectively). Further studies are warranted to further understand the mechanisms by which this therapeutic effect may be conveyed, and which of the novel aspects of the very high and ultra high frequency stimulation strategies may have contributed to the improvement in seizure abatement performance when compared to standard electrical stimulation approaches.

Exploring the tolerability of spatiotemporally complex electrical stimulation paradigms

A modified cortical stimulation model was used to investigate the effects of varying the synchronicity and periodicity of electrical stimuli delivered to multiple pairs of electrodes on seizure initiation. In this model, electrical stimulation of the motor cortex of rats, along four pairs of a microwire electrode array, results in an observable seizure with quantifiable electrographic duration and behavioural severity. Periodic stimuli had a constant inter-stimulus intervals across the two-second stimulus duration, whilst synchronous stimuli consisted of singular biphasic, bipolar pulses delivered to the four pairs of electrodes at precisely the same time for the entire two second stimulation period. In this way four combinations of stimulation were possible; periodic/synchronous (P/S), periodic/asynchronous (P/As), aperiodic/synchronous (Ap/S) and aperiodic/asynchronous (Ap/As). All stimulation types were designed with equal pulse width, current intensity and mean frequency of stimulation (60 Hz), standardizing net charge transfer. It was expected that the periodicity of the stimulus would be the primary determinant of seizure initiation and therefore severity and electrographic duration. However, the results showed that significant differences in both severity and duration only occurred when the synchronicity was altered. For periodic stimuli, synchronous delivery increased median seizure duration from 5 s to 13 s and increased median Racine severity from 1 to 3. In the aperiodic case, synchronous stimulus delivery increased median duration from 5.5 s to 11s and resulted in seizures of median severity 3 vs. 0 in the asynchronous case. These findings may have implications for the design of future neurostimulation waveform designs as higher numbers of electrodes and stimulator output channels become available in next generation implants.

Kainic acid-induced early genes activation and neuronal death in the medial extended amygdala of rats

The medial extended amygdala modulates pheromonal perception, influencing emotional and social behavior. As the amygdala is part of neuronal circuits that are very sensitive to excitability, its neurons are targets of seizures in temporal lobe epilepsy. It has been suggested that the hippocampus is strongly involved this pathology. There is less consistent information, however, on the effects of this disease in the amygdala. The effects of status epilepticus on the medial extended amygdala were analyzed by immunohistochemistry for neural stress and by the amino-cupric-silver technique for neuronal death in rats after kainic acid (KA) administration. Sixty adult Wistar male rats were used. Thirty animals received an injection of KA, and 30 were injected with saline. After 2, 4, 12, 24 and 48 h survival the brains were stained for Fos and FosB and for neuronal death. In the present study we show that KA induces Fos and FosB expression in neurons of the medial extended amygdala after 2, 4-48 h, with time courses that are different between them and from control animals. While Fos-IR peaks at 2-4 h post KA and then decreases, FosB-IR increases in the same period reaching its highest expression at 24-48 h. Moreover, KA injection produced massive neuronal death with a peak at 24 h. This neurodegeneration paralleled FosB-IR protein expression. These findings show that KA produces neuronal stress and activation of early genes and neuronal death in the medial extended amygdala, demonstrating the vulnerability of its neurons to the epileptogenic effects of KA.

Characterisation of cortical activity in response to deep brain stimulation of ventral-lateral nucleus: modelling and experiment

Motivated by its success as a therapeutic treatment in other neurological disorders, most notably Parkinson's disease, Deep Brain Stimulation (DBS) is currently being trialled in a number of patients with drug unresponsive epilepsies. However, the mechanisms by which DBS interferes with neuronal activity linked to the disorder are not well understood. Furthermore, there is a need to identify optimized values of parameters (for example in amplitude/frequency space) of the stimulation protocol with which one aims to achieve the desired outcome. In this paper we characterise the system response to stimulation, to gain an understanding of the role different brain regions play in generating the output observed in EEG. We perform a number of experiments in healthy rats, where the ventral-lateral thalamic nucleus is stimulated using a train of square-waves with different frequency and amplitudes. The response to stimulation in the motor cortex is recorded and the drive-response relationship over frequency/amplitude space is considered. Subsequently, we compare the experimental data with simulations of a mean-field model, finding good agreement between the output of the model and the experimental data--both in the time and frequency domains--when considering a transition to oscillatory activity in the cortex as the frequency of stimulation is increased. Overall, our study suggests that mean-field models can appropriately characterise the stimulus-response relationship of DBS in healthy animals. In this way, it constitutes a first step towards the goal of developing a closed-loop feedback control protocol for suppressing epileptic activity, by adaptively adjusting the stimulation protocol in response to EEG activity.