Toward rational design of electrical stimulation strategies for epilepsy control

Personalized dynamic network models of the human brain as a future tool for planning and optimizing epilepsy therapy

Epilepsy is a common neurological disorder, with one third of patients not responding to currently available antiepileptic drugs. The proportion of pharmacoresistant epilepsies has remained unchanged for many decades. To cure epilepsy and control seizures requires a paradigm shift in the development of new approaches to epilepsy diagnosis and treatment. Contemporary medicine has benefited from the exponential growth of computational modeling, and the application of network dynamics theory to understanding and treating human brain disorders. In epilepsy, the introduction of these approaches has led to personalized epileptic network modeling that can explore the patient's seizure genesis and predict the functional impact of resection on its individual network's propensity to seize. The application of the dynamic systems approach to neurostimulation therapy of epilepsy allows designing stimulation strategies that consider the patient's seizure dynamics and long-term fluctuations in the stability of their epileptic networks. In this article, we review, in a nontechnical fashion suitable for a broad neuroscientific audience, recent progress in personalized dynamic brain network modeling that is shaping the future approach to the diagnosis and treatment of epilepsy.

Astrocytic-based Controller Shifts Epileptic Activity to the Chaotic State

Introduction

Investigating an effective controller to shift hippocampal epileptic periodicity to normal chaotic behavior will be new hope for epilepsy treatment. Astrocytes nourish and protect neurons and maintain synaptic transmission and network activity. Therefore, this study explored the ameliorating effect of the astrocyte computational model on epileptic periodicity.

Methods

Modified Morris-Lecar equations were used to model the hippocampal CA3 network. Network inhibitory parameters were employed to generate oscillation-induced epileptiform periodicity. The astrocyte controller was based on a functional dynamic mathematical model of brain astrocytic cells.

Results

Results demonstrated that the synchronization of two neural networks shifted the brain's chaotic state to periodicity. Applying an astrocytic controller to the synchronized networks returned the system to the desynchronized chaotic state.

Conclusion

It is concluded that astrocytes are probably a good model for controlling epileptic periodicity. However, more research is needed to delineate this effect.

Highlights

Modeling of CA3 neurons reproduced synchronized periodic epileptiform discharges.An astrocyte mathematical model modulated neuronal network excitability.The astrocyte controller desynchronized neural network periodic oscillations.Application of the astrocyte model restored a chaotic desynchronized state.Results suggest astrocytes may control hypersynchronous epileptiform activity.

Plain Language Summary

This study looked at whether a mathematical model of brain cells called astrocytes could help control seizure activity. Seizures happen when groups of brain cells become overly active and synchronized. Normally, brain cell activity is chaotic and unsynchronized. The researchers modeled a small network of hippocampus brain cells using equations. We adjusted the model to create seizure-like periodic synchronized activity. Then we added a mathematical astrocyte model to try to disrupt this unwanted synchronization. Astrocytes are a type of glial cell in the brain. They help nourish neurons and regulate brain cell communication. The researchers modeled astrocyte activity using equations based on calcium levels. Calcium levels affect how astrocytes communicate with brain cells. When the researchers added the astrocyte model to the seizure-like network activity, it was able to restore chaotic unsynchronized activity. The astrocyte model accomplished this by affecting the excitability of the neuronal network. These results suggest astrocytes could potentially be used to control seizure activity. More research is needed to further test this astrocyte model. Currently, many seizure patients do not respond fully to medication. Astrocyte-based treatments could potentially provide an alternative approach. The findings are notable because they demonstrate a biologically-based method to restore normal chaotic brain activity. Most previous efforts have used electrical stimulation. An astrocyte-based approach could modulate communication between brain cells in a more natural way.

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.

Mimicking CA3 Temporal Dynamics Controls Limbic Ictogenesis

Mesial temporal lobe epilepsy (MTLE) is the most common partial complex epilepsy in adults and the most unresponsive to medications. Electrical deep brain stimulation (DBS) of the hippocampus has proved effective in controlling seizures in epileptic rodents and in drug-refractory MTLE patients. However, current DBS paradigms implement arbitrary fixed-frequency or patterned stimuli, disregarding the temporal profile of brain electrical activity. The latter, herein included hippocampal spontaneous firing, has been shown to follow lognormal temporal dynamics. Here, we present a novel paradigm to devise DBS protocols based on stimulation patterns fashioned as a surrogate brain signal. We focus on the interictal activity originating in the hippocampal subfield CA3, which has been shown to be anti-ictogenic. Using 4-aminopyridine-treated hippocampus-cortex slices coupled to microelectrode array, we pursue three specific aims: (1) address whether lognormal temporal dynamics can describe the CA3-driven interictal pattern, (2) explore the possibility of restoring the non-seizing state by mimicking the temporal dynamics of this anti-ictogenic pattern with electrical stimulation, and (3) compare the performance of the CA3-surrogate against periodic stimulation. We show that the CA3-driven interictal activity follows lognormal temporal dynamics. Further, electrical stimulation fashioned as a surrogate interictal pattern exhibits similar efficacy but uses less pulses than periodic stimulation. Our results support the possibility of mimicking the temporal dynamics of relevant brain signals as a straightforward DBS strategy to ameliorate drug-refractory epilepsy. Further, they herald a paradigm shift in neuromodulation, wherein a compromised brain signal can be recreated by the appropriate stimuli distribution to bypass trial-and-error studies and attain physiologically meaningful DBS operating modes.

Case Report: Prolonged Effects of Short-Term Transcranial Magnetic Stimulation on EEG Biomarkers, Spectral Power, and Seizure Frequency

Transcranial magnetic stimulation (TMS) is a non-invasive modality of focal brain stimulation in which a fluctuating magnetic field induces electrical currents within the cortex. It remains unclear to what extent TMS alters EEG biomarkers and how EEG biomarkers may guide treatment of focal epilepsy. We present a case of a 48-year-old man with focal epilepsy, refractory to multiple medication trials, who experienced a dramatic reduction in seizures after targeting the area of seizure onset within the left parietal-occipital region with low-frequency repetitive TMS (rTMS). Prior to treatment, he experienced focal seizures that impacted cognition including apraxia at least 50-60 times daily. MRI of the brain showed a large focal cortical dysplasia with contrast enhancement involving the left occipital-parietal junction. Stimulation for 5 consecutive days was well-tolerated and associated with a day-by-day reduction in seizure frequency. In addition, he was monitored with continuous video EEG, which showed continued and progressive changes in spectral power (decreased broadband power and increased infraslow delta activity) and a gradual reduction in seizure frequency and duration. One month after initial treatment, 2-day ambulatory EEG demonstrated seizure-freedom and MRI showed resolution of focal contrast enhancement. He continues to receive 2-3 days of rTMS every 2-4 months. He was seizure-free for 6 months, and at last follow-up of 17 months was experiencing auras approximately every 2 weeks without progression to disabling seizures. This case demonstrates that rTMS can be a well-tolerated and effective means of controlling medication-refractory seizures, and that EEG biomarkers change gradually in a fashion in association with seizure frequency. TMS influences cortical excitability, is a promising non-invasive means of treating focal epilepsy, and has measurable electrophysiologic effects.

Optogenetic stimulus-triggered acquisition of seizure resistance

Unlike an electrical circuit, the hardware of the brain is susceptible to change. Repeated electrical brain stimulation mimics epileptogenesis. After such "kindling" process, a moderate stimulus would become sufficient in triggering a severe seizure. Here, we report that optogenetic neuronal stimulation can also convert the rat brain to a hyperexcitable state. However, continued stimulation once again converted the brain to a state that was strongly resistant to seizure induction. Histochemical examinations showed that moderate astrocyte activation was coincident with resilience acquisition. Administration of an adenosine A1 receptor antagonist instantly reverted the brain back to a hyperexcitable state, suggesting that hyperexcitability was suppressed by adenosine. Furthermore, an increase in basal adenosine was confirmed using in vivo microdialysis. Daily neuron-to-astrocyte signaling likely prompted a homeostatic increase in the endogenous actions of adenosine. Our data suggest that a certain stimulation paradigm could convert the brain circuit resilient to epilepsy without exogenous drug administration.

A Mixed Filtering Approach for Real-Time Seizure State Tracking Using Multi-Channel Electroencephalography Data

Real-time continuous tracking of seizure state is necessary to develop feedback neuromodulation therapy that can prevent or terminate a seizure early. Due to its high temporal resolution, high scalp coverage, and non-invasive applicability, electroencephalography (EEG) is a good candidate for seizure tracking. In this research, we make multiple seizure state estimations using a mixed-filter and multiple channels found over the entire sensor space; then by applying a Kalman filter, we produce a single seizure state estimation made up of these individual estimations. Using a modified wrapper feature selection, we determine two optimal features of mixed data type, one continuous and one binary analyzing all available channels. These features are used in a state-space framework to model the continuous hidden seizure state. Expectation maximization is performed offline on the training and validation data sets to estimate unknown parameters. The seizure state estimation process is performed for multiple channels, and the seizure state estimation is derived using a square-root Kalman filter. A second expectation maximization step is utilized to estimate the unknown square-root Kalman filter parameters. This method is tested in a real-time applicable way for seizure state estimation. Applying this approach, we obtain a single seizure state estimation with quantitative information about the likelihood of a seizure occurring, which we call seizure probability. Our results on the experimental data (CHB-MIT EEG database) validate the proposed estimation method and we achieve an average accuracy, sensitivity, and specificity of 92.7%, 92.8%, and 93.4%, respectively. The potential applications of this seizure estimation model are for closed-loop neuromodulation and long-term quantitative analysis of seizure treatment efficacy.

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.

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.

Controllability of Networks of Multiple Coupled Neural Populations: An Analytical Method for Neuromodulation's Feasibility

Neuromodulation plays a vital role in the prevention and treatment of neurological and psychiatric disorders. Neuromodulation's feasibility is a long-standing issue because it provides the necessity for neuromodulation to realize the desired purpose. A controllability analysis of neural dynamics is necessary to ensure neuromodulation's feasibility. Here, we present such a theoretical method by using the concept of controllability from the control theory that neuromodulation's feasibility can be studied smoothly. Firstly, networks of multiple coupled neural populations with different topologies are established to mathematically model complicated neural dynamics. Secondly, an analytical method composed of a linearization method, the Kalman controllable rank condition and a controllability index is applied to analyze the controllability of the established network models. Finally, the relationship between network dynamics or topological characteristic parameters and controllability is studied by using the analytical method. The proposed method provides a new idea for the study of neuromodulation's feasibility, and the results are expected to guide us to better modulate neurodynamics by optimizing network dynamics and network topology.

Antiepileptic Effects of a Novel Non-invasive Neuromodulation Treatment in a Subject With Early-Onset Epileptic Encephalopathy: Case Report With 20 Sessions of HD-tDCS Intervention

The current clinical investigation examined high-definition transcranial direct current stimulation (HD-tDCS) as a focal, non-invasive, anti-epileptic treatment in a child with early-onset epileptic encephalopathy. We investigated the clinical impact of repetitive (20 daily sessions) cathode-centered 4 × 1 HD-tDCS (1 mA, 20 min, 4 mm ring radius) over the dominant seizure-generating cortical zone in a 40-month-old child suffering from a severe neonatal epileptic syndrome known as Ohtahara syndrome (OS). Seizures and epileptiform activity were monitored and quantified using video-EEG over multiple days of baseline, intervention, and post-intervention periods. Primary outcome measures were changes in seizure frequency and duration on the last day of intervention versus the last baseline day, preceding the intervention. In particular, we examined changes in tonic spasms, tonic-myoclonic seizures (TM-S), and myoclonic seizures from baseline to post-intervention. A trend in TM-S frequency was observed indicating a reduction of 73% in TM-S frequency, which was non-significant [t(4) = 2.05, p = 0.1], and denoted a clinically significant change. Myoclonic seizure (M-S) frequency was significantly reduced [t(4) = 3.83, p = 0.019] by 68.42%, compared to baseline, and indicated a significant clinical change as well. A 73% decrease in interictal epileptic discharges (IEDs) frequency was also observed immediately after the intervention period, compared to IED frequency at 3 days prior to intervention. Post-intervention seizure-related peak delta desynchronization was reduced by 57%. Our findings represent a case-specific significant clinical response, reduction in IED, and change in seizure-related delta activity following the application of HD-tDCS. The clinical outcomes, as noted in the current study, encourage the further investigation of this focal, non-invasive neuromodulation procedure in other severe electroclinical syndromes (e.g., West syndrome) and in larger pediatric populations diagnosed with early-onset epileptic encephalopathy. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT02960347, protocol ID: Meiron 2013-4.

Low-Frequency Electrical Stimulation Reduces the Impairment in Synaptic Plasticity Following Epileptiform Activity in Rat Hippocampal Slices through α1, But Not α2, Adrenergic Receptors

Low frequency stimulation (LFS) has anticonvulsant effect and may restore the ability of long-term potentiation (LTP) to the epileptic brain. The mechanisms of LFS have not been completely determined. Here, we showed that LTP induction was impaired following in vitro epileptiform activity (EA) in hippocampal slices, but application of LFS prevented this impairment. Then, we investigated the involvement of α-adrenergic receptors in this effect of LFS. EA was induced by increasing the extracellular K⁺ concentration to 12 mM and EPSPs were recorded from CA1 neurons in whole cell configuration. EA increased EPSP amplitude from 6.9 ± 0.7 mV to 9.6 ± 0.6 mV. For LTP induction, the Schaffer collaterals were stimulated by high frequency stimulation (HFS; two trains of 100 pulses, 100 Hz at the interval of 20 s). The application of HFS resulted in 40.9 ± 2.3% increase in the amplitude of EPSPs. However, following EA, HFS could not produce any significant changes in EPSP amplitude. Administration of LFS (1 Hz, 900 pulses) to Schaffer collaterals at the beginning of EA restored LTP induction to the hippocampal slices and HFS increased the EPSPs amplitude up to 41.7 ± 3.1% of baseline. When slices were perfused by prazosin (α₁-adrenergic receptor antagonist; 10 μM) before and during LFS application, LFS improvement on LTP induction was reduced significantly. Perfusion of slices by yohimbine (α₂-adrenergic receptor antagonist; 5 μM) had no effect on LFS action. Therefore, it may be concluded that following epileptiform activity, LFS can improve the impairment of LTP generation through α₁, but not α₂, adrenergic receptor activity.

Role of GABAB receptors in proepileptic and antiepileptic effects of an applied electric field in rat hippocampus in vitro

The mechanisms underlying antiepileptic effects of deep brain stimulation (DBS) are complex and poorly understood. Studies on the effects of applied electric fields on epileptic nervous tissue could enable future advances in DBS treatments. Applied electric fields are known to inhibit or enhance epileptic activity in vitro through direct effects on local neurons, but it is unclear whether trans-synaptic effects participate in such actions. The present study investigates, in an epileptic brain slice model, the influence of GABA_B receptor activation on excitatory and suppressive effects of a short-duration (10 ms) electric field in rat hippocampus. The results show that perfusion of the GABA_B receptor antagonist, CGP 55845 (2 μM), could abolish applied-field induced suppression of orthodromic-stimulus evoked epileptiform afterdischarge activity in the CA1 region. GABA_B receptor blockade was associated with an enhanced excitatory (proepileptic) effect of the applied field. However, the suppressive effect, observed in isolation using weak field stimuli, was left unchanged. The G-protein-activated inwardly rectifying K⁺ channel (GIRK) antagonist, tertiapin (30-50 nM), mimicked the effects of CGP 55845. The results suggest that the applied field activate (elements of) local interneurons to release GABA onto GABA_B receptors. The resulting activation of postsynaptic GIRK channels inhibits neuronal activity thereby dampening the direct stimulatory effect of the applied field. The study indicates that local-stimulus induced GABA_B receptor activation can serve a protective role under antiepileptic paradigms by preventing electrical stimulation from causing hyperexcitation.

Neurophysiological effects of continuous cortical stimulation in epilepsy - Spike and spontaneous ECoG activity

OBJECTIVE

The effect of continuous subthreshold cortical stimulation (CSCS) over the seizure onset zone (SOZ) in epilepsy was analyzed to delineate the affected physiological processes.

METHOD

ECoG data was recorded over SOZ and adjacent regions in patients (n = 7) with refractory-epilepsy. Data was reviewed before and during 2 Hz cortical electrical stimulation. Group differences were estimated using ANOVA and correlation with Pearson's r.

RESULTS

CSCS reduced background ECoG power at SOZ (p < 0.05), increased spectral coherence (p < 0.05) and reduced spike rate (p < 0.01) over all recorded sites. Spectral power and coherence (p < 0.01) correlated with spike rate at SOZ but not with each other at any location. Spike morphology correlated with spike-rate over all recorded sites (p < 0.0001) and with spectral power and coherence at SOZ (p < 0.01).

CONCLUSION

This study shows changes in cortical electrophysiology during CSCS over the SOZ where spike rate reduction correlated with two independent electrophysiological parameters, background power and coherence. These results suggest the possibility of a causal relationship between spectral power, coherence and interictal spikes which may be related to seizure rate.

SIGNIFICANCE

Improved understanding of the effect of electrical stimulation on epileptic tissue could suggest improvements in stimulation paradigms to reduce seizure frequency.

Mesoscopic neuron population modeling of normal/epileptic brain dynamics

Simulations of EEG data provide the understanding of how the limbic system exhibits normal and abnormal states of the electrical activity of the brain. While brain activity exhibits a type of homeostasis of excitatory and inhibitory mesoscopic neuron behavior, abnormal neural firings found in the seizure state exhibits brain instability due to runaway oscillatory entrained neural behavior. We utilize a model of mesoscopic brain activity, the KIV model, where each network represents the areas of the limbic system, i.e., hippocampus, sensory cortex, and the amygdala. Our model initially demonstrates oscillatory entrained neural behavior as the epileptogenesis, and then by increasing the external weights that join the three networks that represent the areas of the limbic system, seizure activity entrains the entire system. By introducing an external signal into the model, simulating external electrical titration therapy, the modeled seizure behavior can be 'rebalanced' back to its normal state.

High-Definition transcranial direct current stimulation in early onset epileptic encephalopathy: a case study

PRIMARY OBJECTIVE

Early onset epileptic encephalopathy is characterized by high daily seizure-frequency, multifocal epileptic discharges, severe psychomotor retardation, and death at infancy. Currently, there are no effective treatments to alleviate seizure frequency and high-voltage epileptic discharges in these catastrophic epilepsy cases. The current study examined the safety and feasibility of High-Definition transcranial direct current stimulation (HD-tDCS) in reducing epileptiform activity in a 30-month-old child suffering from early onset epileptic encephalopathy.

DESIGN AND METHODS

HD-tDCS was administered over 10 intervention days spanning two weeks including pre- and post-intervention video-EEG monitoring.

RESULTS

There were no serious adverse events or side effects related to the HD-tDCS intervention. Frequency of clinical seizures was not significantly reduced. However, interictal sharp wave amplitudes were significantly lower during the post-intervention period versus baseline. Vital signs and blood biochemistry remained stable throughout the entire study.

CONCLUSIONS

These exploratory findings support the safety and feasibility of 4 × 1 HD-tDCS in early onset epileptic encephalopathy and provide the first evidence of HD-tDCS effects on paroxysmal EEG features in electroclinical cases under the age of 36 months. Extending HD-tDCS treatment may enhance electrographic findings and clinical effects.

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.

Principal dynamic mode analysis of neural mass model for the identification of epileptic states

The detection of epileptic seizures in Electroencephalography (EEG) signals is significant for the diagnosis and treatment of epilepsy. In this paper, in order to obtain characteristics of various epileptiform EEGs that may differentiate different states of epilepsy, the concept of Principal Dynamic Modes (PDMs) was incorporated to an autoregressive model framework. First, the neural mass model was used to simulate the required intracerebral EEG signals of various epileptiform activities. Then, the PDMs estimated from the nonlinear autoregressive Volterra models, as well as the corresponding Associated Nonlinear Functions (ANFs), were used for the modeling of epileptic EEGs. The efficient PDM modeling approach provided physiological interpretation of the system. Results revealed that the ANFs of the 1st and 2nd PDMs for the auto-regressive input exhibited evident differences among different states of epilepsy, where the ANFs of the sustained spikes' activity encountered at seizure onset or during a seizure were the most differentiable from that of the normal state. Therefore, the ANFs may be characteristics for the classification of normal and seizure states in the clinical detection of seizures and thus provide assistance for the diagnosis of epilepsy.

Animal models of transcranial direct current stimulation: Methods and mechanisms

The objective of this review is to summarize the contribution of animal research using direct current stimulation (DCS) to our understanding of the physiological effects of transcranial direct current stimulation (tDCS). We comprehensively address experimental methodology in animal studies, broadly classified as: (1) transcranial stimulation; (2) direct cortical stimulation in vivo and (3) in vitro models. In each case advantages and disadvantages for translational research are discussed including dose translation and the overarching "quasi-uniform" assumption, which underpins translational relevance in all animal models of tDCS. Terminology such as anode, cathode, inward current, outward current, current density, electric field, and uniform are defined. Though we put key animal experiments spanning decades in perspective, our goal is not simply an exhaustive cataloging of relevant animal studies, but rather to put them in context of ongoing efforts to improve tDCS. Cellular targets, including excitatory neuronal somas, dendrites, axons, interneurons, glial cells, and endothelial cells are considered. We emphasize neurons are always depolarized and hyperpolarized such that effects of DCS on neuronal excitability can only be evaluated within subcellular regions of the neuron. Findings from animal studies on the effects of DCS on plasticity (LTP/LTD) and network oscillations are reviewed extensively. Any endogenous phenomena dependent on membrane potential changes are, in theory, susceptible to modulation by DCS. The relevance of morphological changes (galvanotropy) to tDCS is also considered, as we suggest microscopic migration of axon terminals or dendritic spines may be relevant during tDCS. A majority of clinical studies using tDCS employ a simplistic dose strategy where excitability is singularly increased or decreased under the anode and cathode, respectively. We discuss how this strategy, itself based on classic animal studies, cannot account for the complexity of normal and pathological brain function, and how recent studies have already indicated more sophisticated approaches are necessary. One tDCS theory regarding "functional targeting" suggests the specificity of tDCS effects are possible by modulating ongoing function (plasticity). Use of animal models of disease are summarized including pain, movement disorders, stroke, and epilepsy.

Safety of Transcranial Direct Current Stimulation: Evidence Based Update 2016

This review updates and consolidates evidence on the safety of transcranial Direct Current Stimulation (tDCS). Safety is here operationally defined by, and limited to, the absence of evidence for a Serious Adverse Effect, the criteria for which are rigorously defined. This review adopts an evidence-based approach, based on an aggregation of experience from human trials, taking care not to confuse speculation on potential hazards or lack of data to refute such speculation with evidence for risk. Safety data from animal tests for tissue damage are reviewed with systematic consideration of translation to humans. Arbitrary safety considerations are avoided. Computational models are used to relate dose to brain exposure in humans and animals. We review relevant dose-response curves and dose metrics (e.g. current, duration, current density, charge, charge density) for meaningful safety standards. Special consideration is given to theoretically vulnerable populations including children and the elderly, subjects with mood disorders, epilepsy, stroke, implants, and home users. Evidence from relevant animal models indicates that brain injury by Direct Current Stimulation (DCS) occurs at predicted brain current densities (6.3-13 A/m(2)) that are over an order of magnitude above those produced by conventional tDCS. To date, the use of conventional tDCS protocols in human trials (≤40 min, ≤4 milliamperes, ≤7.2 Coulombs) has not produced any reports of a Serious Adverse Effect or irreversible injury across over 33,200 sessions and 1000 subjects with repeated sessions. This includes a wide variety of subjects, including persons from potentially vulnerable populations.

Epileptogenic zone localization and seizure control in coupled neural mass models

Exact localization of the epileptogenic zone (EZ) is the first priority for ensuring epilepsy treatments and reducing side effects. The results of traditional visual methods for localizing the origin of seizures are far from satisfactory in some cases. Signal processing methods could extract substantial information that may complement visual inspection of EEG signals. In this study, EZ localization is changed into a driver identification problem, and a nonlinear interdependence measure, the weighted rank interdependence, is proposed and used as a driver indicator because it can detect coupling information, especially directionality, from EEG signals. A proportional integral derivative (PID) controller is then explored, using simulations, to establish its suitability for seizure control. The seizure control we propose rests on identifying the EZ using nonlinear interdependence measures of directed functional connectivity. Two directionally coupled neural mass models are employed for simulation investigation. Two parameters can adjust the sensitivity and completeness of the weighted rank interdependence for different applications, and their effect is discussed in the context of neural mass models. Simulation results demonstrate that use of the weighted rank interdependence for EZ identification can be applied to different EZ types, and the approach achieves an overall identification rate of 98.84 % for several EZ types. Simulations also indicate that PID control can effectively regulate synchronization between neural masses.

Suppression of seizures based on the multi-coupled neural mass model

Epilepsy is one of the most common serious neurological disorders, which affects approximately 1% of population in the world. In order to effectively control the seizures, we propose a novel control methodology, which combines the feedback linearization control (FLC) with the underlying mechanism of epilepsy, to achieve the suppression of seizures. The three coupled neural mass model is constructed to study the property of the electroencephalographs (EEGs). Meanwhile, with the model we research on the propagation of epileptiform waves and the synchronization of populations, which are taken as the foundation of our control method. Results show that the proposed approach not only yields excellent performances in clamping the pathological spiking patterns to the reference signals derived under the normal state but also achieves the normalization of the pathological parameter, where the parameters are estimated from EEGs with Unscented Kalman Filter. The specific contribution of this paper is to treat the epilepsy from its pathogenesis with the FLC, which provides critical theoretical basis for the clinical treatment of neurological disorders.

Modeling sequence and quasi-uniform assumption in computational neurostimulation

Computational neurostimulation aims to develop mathematical constructs that link the application of neuromodulation with changes in behavior and cognition. This process is critical but daunting for technical challenges and scientific unknowns. The overarching goal of this review is to address how this complex task can be made tractable. We describe a framework of sequential modeling steps to achieve this: (1) current flow models, (2) cell polarization models, (3) network and information processing models, and (4) models of the neuroscientific correlates of behavior. Each step is explained with a specific emphasis on the assumptions underpinning underlying sequential implementation. We explain the further implementation of the quasi-uniform assumption to overcome technical limitations and unknowns. We specifically focus on examples in electrical stimulation, such as transcranial direct current stimulation. Our approach and conclusions are broadly applied to immediate and ongoing efforts to deploy computational neurostimulation.

Seizure reduction through interneuron-mediated entrainment using low frequency optical stimulation

Low frequency electrical stimulation (LFS) can reduce neural excitability and suppress seizures in animals and patients with epilepsy. However the therapeutic outcome could benefit from the determination of the cell types involved in seizure suppression. We used optogenetic techniques to investigate the role of interneurons in LFS (1Hz) in the epileptogenic hippocampus. Optical low frequency stimulation (oLFS) was first used to activate the cation channel channelrhodopsin-2 (ChR2) in the Thy1-ChR2 transgenic mouse that expresses ChR2 in both excitatory and inhibitory neurons. We found that oLFS could effectively reduce epileptiform activity in the hippocampus through the activation of GAD-expressing hippocampal interneurons. This was confirmed using the VGAT-ChR2 transgenic mouse, allowing for selective optical activation of only GABA interneurons. Activating hippocampal interneurons through oLFS was found to cause entrainment of neural activity similar to electrical stimulation, but through a GABAA-mediated mechanism. These results confirm the robustness of the LFS paradigm and indicate that GABA interneurons play an unexpected role of shaping inter-ictal activity to decrease neural excitability in the hippocampus.

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

Neuronal networks and energy bursts in epilepsy

Epilepsy can be defined as the abnormal activities of neurons. The occurrence, propagation and termination of epileptic seizures rely on the networks of neuronal cells that are connected through both synaptic- and non-synaptic interactions. These complicated interactions contain the modified functions of normal neurons and glias as well as the mediation of excitatory and inhibitory mechanisms with feedback homeostasis. Numerous spread patterns are detected in disparate networks of ictal activities. The cortical-thalamic-cortical loop is present during a general spike wave seizure. The thalamic reticular nucleus (nRT) is the major inhibitory input traversing the region, and the dentate gyrus (DG) controls CA3 excitability. The imbalance between γ-aminobutyric acid (GABA)-ergic inhibition and glutamatergic excitation is the main disorder in epilepsy. Adjustable negative feedback that mediates both inhibitory and excitatory components affects neuronal networks through neurotransmission fluctuation, receptor and transmitter signaling, and through concomitant influences on ion concentrations and field effects. Within a limited dynamic range, neurons slowly adapt to input levels and have a high sensitivity to synaptic changes. The stability of the adapting network depends on the ratio of the adaptation rates of both the excitatory and inhibitory populations. Thus, therapeutic strategies with multiple effects on seizures are required for the treatment of epilepsy, and the therapeutic functions on networks are reviewed here. Based on the high-energy burst theory of epileptic activity, we propose a potential antiepileptic therapeutic strategy to transfer the high energy and extra electricity out of the foci.

Closed-loop optical neural stimulation based on a 32-channel low-noise recording system with online spike sorting

OBJECTIVE

Closed-loop operation of neuro-electronic systems is desirable for both scientific and clinical (neuroprosthesis) applications. Integrating optical stimulation with recording capability further enhances the selectivity of neural stimulation. We have developed a system enabling the local delivery of optical stimuli and the simultaneous electrical measuring of the neural activities in a closed-loop approach.

APPROACH

The signal analysis is performed online through the implementation of a template matching algorithm. The system performance is demonstrated with the recorded data and in awake rats.

MAIN RESULTS

Specifically, the neural activities are simultaneously recorded, detected, classified online (through spike sorting) from 32 channels, and used to trigger a light emitting diode light source using generated TTL signals.

SIGNIFICANCE

A total processing time of 8 ms is achieved, suitable for optogenetic studies of brain mechanisms online.

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.

Controlling seizure-like events by perturbing ion concentration dynamics with periodic stimulation

We investigate the effects of adding periodic stimulation to a generic, conductance-based neuron model that includes ion concentration dynamics of sodium and potassium. Under conditions of high extracellular potassium, the model exhibits repeating, spontaneous, seizure-like bursting events associated with slow modulation of the ion concentrations local to the neuron. We show that for a range of parameter values, depolarizing and hyperpolarizing periodic stimulation pulses (including frequencies lower than 4 Hz) can stop the spontaneous bursting by interacting with the ion concentration dynamics. Stimulation can also control the magnitude of evoked responses to modeled physiological inputs. We develop an understanding of the nonlinear dynamics of this system by a timescale separation procedure that identifies effective nullclines in the ion concentration parameter space. Our results suggest that the manipulation of ion concentration dynamics via external or endogenous stimulation may play an important role in neuronal excitability, seizure dynamics, and control.

Long-lasting hyperpolarization underlies seizure reduction by low frequency deep brain electrical stimulation

Mesial temporal lobe epilepsy (MTLE) is a common medically refractory neurological disease. Deep brain electrical stimulation (DBS) of grey matter has been used for MTLE with limited success. However, stimulation of a white matter tract connecting the hippocampi, the ventral hippocampal commissure (VHC), with low frequencies that simulate interictal discharges has shown promising results, with seizure reduction greater than 98% in bilateral hippocampi during stimulation and greater than 50% seizure reduction in bilateral hippocampi after treatment. A major hurdle to the implementation and optimization of this treatment is that the mechanisms of seizure reduction by low frequency electrical stimulation (LFS) are not known. The goal of this study is to understand how commissural fibre tract stimulation reduces bilateral hippocampal epileptic activity in an in vitro slice preparation containing bilateral hippocampi connected by the VHC. It is our hypothesis that electrical stimuli induce hyperpolarization lasting hundreds of milliseconds following each pulse which reduces spontaneous epileptic activity during each inter-stimulus interval (ISI). Stimulus-induced long-lasting-hyperpolarization (LLH) can be mediated by GABA(B) inhibitory post-synaptic potentials (IPSPs) or slow after-hyperpolarization (sAHP). To test the role of LLH in effective bilateral seizure reduction by fibre tract stimulation, we measured stimulus-induced hyperpolarization during LFS of the VHC using electrophysiology techniques. Antagonism of the GABA(B) IPSP and/or sAHP diminished stimulus-induced hyperpolarization concurrently with LFS efficacy (greater than 50% reduction). Blocking both the GABA(B) IPSP and sAHP simultaneously eliminated the effect of electrical stimulation on seizure reduction entirely. These data show that LFS of the VHC is an effective protocol for bilateral hippocampal seizure reduction and that its efficacy relies on the induction of long-lasting hyperpolarization mediated through GABA(B) IPSPs and sAHP. Based on this study, optimization of the timing of LFS and LFS-induced-LLH may lead to improved outcomes from DBS treatments for human epilepsy.

The effects of responsive and scheduled subicular high frequency stimulation in the intra-hippocampal kainic acid seizure model

BACKGROUND

Responsive stimulation is a promising and newly emerging treatment for refractory temporal lobe epilepsy in which current is delivered to target areas following seizure occurrence.

OBJECTIVE

We compared responsive and scheduled subicular high frequency stimulation (HFS) with a sham control group on acute seizures and seizure sensitivity two weeks later. We also investigated the role of status epilepticus (SE) on efficacy of both types of stimulation.

METHOD

Adult Wistar rats received kainic acid (KA) injections intrahippocampally until they reached Stage V (Racine scale) on Day 1. Responsive, scheduled or sham HFS (125 Hz, 100 μs) was delivered in three groups while EEG was recorded. All rats received KA injections again on Day 15 to measure the excitability of animals to KA, again with EEG monitoring.

RESULTS

All rats reached Stage V and 60% reached SE on Day 1. Focal seizures were suppressed in both stimulated groups (the scheduled group was slightly more effective) on both days in only non-SE rats. Similar stimulation effects were found on generalized seizures but mainly on Day 15.

CONCLUSION

Both types of subicular HFS suppressed focal and generalized seizures, albeit differently. Scheduled stimulation seemed a bit more effective, and the amount of stimulation might be a factor that influences the differences between the stimulated groups. Beneficial effects of HFS were restricted to non-SE rats and HFS did not suppress or even worsen seizures in SE rats.

Suppression of epileptiform activity by a single short-duration electric field in rat hippocampus in vitro

The mechanisms behind the therapeutic effects of electrical stimulation of the brain in epilepsy and other disorders are poorly understood. Previous studies in vitro have shown that uniform electric fields can suppress epileptiform activity through a direct polarizing effect on neuronal membranes. Such an effect depends on continuous DC stimulation with unbalanced charge. Here we describe a suppressive effect of a brief (10 ms) DC field on stimulus-evoked epileptiform activity in rat hippocampal brain slices exposed to Cs+ (3.5 mM). This effect was independent of field polarity, was uncorrelated to changes in synchronized population activity, and persisted during blockade of synaptic transmission with Cd2+ (500 μM). Antagonists of A1, P2X, or P2Y receptors were without effect. The suppressive effect depended on the alignment of the external field with the somato-dendritic axis of CA1 pyramidal cells; however, temporal coincidence with the epileptiform activity was not essential, as suppression was detectable for up to 1 s after the field. Pyramidal cells, recorded during epileptiform activity, showed decreased discharge duration and truncation of depolarizing plateau potentials in response to field application. In the absence of hyperactivity, the applied field was followed by slow membrane potential changes, accompanied by decreased input resistance and attenuation of the depolarizing afterpotential following action potentials. These effects recovered over a 1-s period. The study suggests that a brief electric field induces a prolonged suppression of epileptiform activity, which can be related to changes in neuronal membrane properties, including attenuation of signals depending on the persisting Na+ current.

Epilepsy

Noninvasive brain stimulation, particularly transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), are emerging as realistic tools for seizure control. Numerous open-label trials and a few recent randomized controlled trials suggest the capacity of both techniques to suppress seizures. Additionally, specialized TMS protocols aimed to map cortical function and to measure cortical excitability may have realistic roles as diagnostic tools in epilepsy. As the prevalence of drug-resistant epilepsy has not changed in recent years, TMS and tDCS offer noninvasive and nonpharmacological options to improve control of intractable seizures.

Fiber tract stimulation can reduce epileptiform activity in an in-vitro bilateral hippocampal slice preparation

Mesial temporal lobe epilepsy (MTLE) is a common medically refractory neurological disease that has been treated with electrical stimulation of gray matter with limited success. However, stimulation of a white matter tract connecting the hippocampi could maximize treatment efficacy and extent. We tested low-frequency stimulation (LFS) of a novel target that enables simultaneous targeting of bilateral hippocampi: the ventral hippocampal commissure (VHC) with a novel in-vitro slice preparation containing bilateral hippocampi connected by the VHC. The goal of this study is to understand the role of hippocampal interplay in seizure propagation and reduction by commissural fiber tract stimulation. LFS is applied to the VHC as extracellular and intracellular recording techniques are combined with signal processing to estimate several metrics of epilepsy including: (1) total time occupied by seizure activity (%); (2) seizure duration (s); (3) seizures per minute (#); and (4) power in the ictal (V(2)Hz(-1)); as well as (5) interictal spectra (V(2)Hz(-1)). Bilateral epileptiform activity in this preparation is highly correlated between hippocampi. Application of LFS to the VHC reduces all metrics of epilepsy during treatment in an amplitude and frequency dependent manner. This study lends several insights into the mechanisms of bilateral seizure reduction by LFS of the VHC, including that depolarization blocking, LTD/LTP and GABA(A) are not involved. Importantly, enhanced post-stimulation 1-Hz spiking correlates with long-lasting seizure reduction and both are heightened by targeting bilateral hippocampi via the VHC. Therefore, stimulating bilateral hippocampi via a single electrode in the VHC may provide an effective MTLE treatment.

Inferring evoked brain connectivity through adaptive perturbation

Inference of functional networks-representing the statistical associations between time series recorded from multiple sensors-has found important applications in neuroscience. However, networksexhibiting time-locked activity between physically independent elements can bias functional connectivity estimates employing passive measurements. Here, a perturbative and adaptive method of inferring network connectivity based on measurement and stimulation-so called "evoked network connectivity" is introduced. This procedure, employing a recursive Bayesian update scheme, allows principled network stimulation given a current network estimate inferred from all previous stimulations and recordings. The method decouples stimulus and detector design from network inference and can be suitably applied to a wide range of clinical and basic neuroscience related problems. The proposed method demonstrates improved accuracy compared to network inference based on passive observation of node dynamics and an increased rate of convergence relative to network estimation employing a naïve stimulation strategy.

The effects of acute responsive high frequency stimulation of the subiculum on the intra-hippocampal kainic acid seizure model in rats

The effects of acute responsive high frequency stimulation (HFS) to the subiculum on seizures and interictal spikes were investigated in a semi-acute kainic acid (KA) induced seizure model in rats. Wistar rats (n = 15) were implanted with an electrode-cannula complex in the CA3 area, stimulation and recording electrodes in the subiculum and another recording electrode at the contralateral motor cortex. Two weeks later rats were injected repeatedly with KA (0.05 μg/0.1 μL) for 3 days with an interval of 48 h. HFS (125 Hz, 100 μsec) was delivered to the subiculum at a predetermined intensity range (100-500 μA) in the HFS group (n = 7) when seizures were visually detected, while no stimulation was delivered in the sham control group (n = 8). Various severities of seizures were obtained (Stage I-V) and all rats of both groups reached Stage V (Racine's scale) on Day 1. The HFS group had less focal seizures and a longer inter-focal seizure interval on Day 1. Interictal spike rate was also lower in the HFS group and decreased with injection days. Significant day effects were found for the latency, number of focal seizures, and duration of focal seizures and generalized seizures while differences between groups were no longer present. Responsive HFS did not disrupt ongoing seizures. However, focal seizures and interictal spikes were suppressed by HFS. Such anticonvulsant effects of acute subicular stimulation indicate that the subiculum is involved in seizure generation. The reduction of seizure sensitivity over the injection day reflects an intrinsic anticonvulsant mechanism.

Distributed control in a mean-field cortical network model: implications for seizure suppression

Brain electrical stimulation (BES) has long been suggested as a means of controlling pathological brain activity. In epilepsy, control of a spatially localized source, the seizure focus, may normalize neuronal dynamics. Consequently, most BES research has been directed at controlling small, local, neuronal populations. At a higher level, pathological seizure activity can be viewed as a network event that may begin without a clear spatial focus or in multiple sites and spread rapidly through a distributed cortical network. In this paper, we begin to address the implications of local control in a network scenario. To do so, we explore the efficacy of local BES when deployed over a larger-scale neuronal network, for instance, using a grid of stimulating electrodes on the cortex. By introducing a mean-field model of neuronal interactions we are able to identify limitations in network controllability based on physiological constraints that suggest the need for more nuanced network control strategies.

Histocompatibility and in vivo signal throughput for PEDOT, PEDOP, P3MT, and polycarbazole electrodes

Stimulation and recording of the in vivo electrical activity of neurons are critical functions in contemporary biomedical research and in treatment of patients with neurological disorders. The electrodes presently in use tend to exhibit short effective lifespans due to degradation of signal transmission resulting from the tissue response at the electrode-brain interface, with signal throughput suffering most at the low frequencies relevant for biosignals. To overcome these limitations, new electrode designs to minimize tissue responses, including conducting polymers (CPs) have been explored. Here, we report the short-term histocompatibility and signal throughput results comparing platinum and CP-modified platinum electrodes in a Sprague-Dawley rat model. Two of the polymers tested elicited significantly decreased astrocyte responses relative to platinum. These polymers also showed improved signal throughput at low frequencies and comparable signal-to-noise ratios during targeted intracranial electroencephalograms. These results suggest that CP electrodes may present viable alternatives to the metal electrodes that are currently in use.

Responsive electrical stimulation suppresses epileptic seizures in rats

Background

A responsive electrical stimulation pattern based on our recently developed novel seizure prediction method was designed to suppress the penicillin-induced epileptic seizures.

Methodology

Seizures were induced by Penicillin injection at rat cortex. A responsive electrical stimulation system was triggered prior to seizures predicted with phase synchronisation. Rats with induced seizures were stimulated by the electrical pulses at a responsive or 1 Hz periodic pattern of an open system. The effectiveness of stimulation on seizures suppression was assessed by measuring the average number and duration of seizures per hour.

Results

The prediction algorithm reliably identified seizures in real time and triggered the responsive stimulation. This type of electrical stimulation dramatically suppressed seizure activity and the performance was better than the open stimulation system with fewer and shorter seizures.

Conclusions

A responsive electrical stimulation system triggered by the phase synchronisation prediction is able to significantly suppress seizures.

Significance

Responsive electrical stimulation could achieve superior treatment performance and reduce power consumption and side effects.

A NOVEL ELECTRICAL STIMULATION PARADIGM FOR THE SUPPRESSION OF EPILEPTIFORM ACTIVITY IN ANIN VIVOMODEL OF MESIAL TEMPORAL LOBE STATUS EPILEPTICUS

In this study, we present a novel low-frequency electrical stimulation paradigm for mesial temporal lobe epilepsy (MTLE). The paradigm utilizes the hippocampal commissure as a unique stimulation target to simultaneously influence large portions of the bilateral hippocampal network. When applied to an acute rat model of MTLE, animals that received stimulation exhibited an 88% reduction in the signal power of the bilateral epileptiform activity relative to the control group. In addition, the stimulation entrained the hippocampal network's spontaneous epileptiform activity and disrupted its bilateral synchrony.