Electrocorticographic events from long-term ambulatory brain recordings can potentially supplement seizure diaries

Responsive neurostimulation as a therapy for epilepsy following new-onset refractory status epilepticus: Case series and review of the literature

OBJECTIVE

To report clinical outcomes of patients who presented with new-onset refractory status epilepticus (NORSE), developed drug-resistant epilepsy (DRE), and were treated with responsive neurostimulation (RNS).

METHODS

We performed a retrospective review of patients implanted with RNS at our institution and identified three who originally presented with NORSE. Through chart review, we retrieved objective and subjective information related to their presentation, workup, and outcomes including patient-reported seizure frequency. We reviewed electrocorticography (ECoG) data to estimate seizure burden at 3, 6, 12, and 24 months following RNS implantation. We performed a review of literature concerning neurostimulation in NORSE.

RESULTS

Use of RNS to treat DRE following NORSE was associated with reduced seizure burden and informed care by differentiating epileptic from non-epileptic events.

CONCLUSIONS

Our single-center experience of three cases suggests that RNS is a safe and potentially effective treatment for DRE following NORSE.

SIGNIFICANCE

This article reports outcomes of the largest case series of NORSE patients treated with RNS. Since patients with NORSE are at high risk of adverse neuropsychiatric and cognitive sequelae beyond seizures, a unique strength of RNS over other surgical options is the ability to distinguish ictal or peri-ictal from non-epileptic events.

Circadian changes in aperiodic activity are correlated with seizure reduction in patients with mesial temporal lobe epilepsy treated with responsive neurostimulation

OBJECTIVES

Responsive neurostimulation (RNS) is an established therapy for drug-resistant epilepsy that delivers direct electrical brain stimulation in response to detected epileptiform activity. However, despite an overall reduction in seizure frequency, clinical outcomes are variable, and few patients become seizure-free. The aim of this retrospective study was to evaluate aperiodic electrophysiological activity, associated with excitation/inhibition balance, as a novel electrographic biomarker of seizure reduction to aid early prognostication of the clinical response to RNS.

METHODS

We identified patients with intractable mesial temporal lobe epilepsy who were implanted with the RNS System between 2015 and 2021 at the University of Utah. We parameterized the neural power spectra from intracranial RNS System recordings during the first 3 months following implantation into aperiodic and periodic components. We then correlated circadian changes in aperiodic and periodic parameters of baseline neural recordings with seizure reduction at the most recent follow-up.

RESULTS

Seizure reduction was correlated significantly with a patient's average change in the day/night aperiodic exponent (r = .50, p = .016, n = 23 patients) and oscillatory alpha power (r = .45, p = .042, n = 23 patients) across patients for baseline neural recordings. The aperiodic exponent reached its maximum during nighttime hours (12 a.m. to 6 a.m.) for most responders (i.e., patients with at least a 50% reduction in seizures).

SIGNIFICANCE

These findings suggest that circadian modulation of baseline broadband activity is a biomarker of response to RNS early during therapy. This marker has the potential to identify patients who are likely to respond to mesial temporal RNS. Furthermore, we propose that less day/night modulation of the aperiodic exponent may be related to dysfunction in excitation/inhibition balance and its interconnected role in epilepsy, sleep, and memory.

Insights From Chronic ECoG by RNS

SUMMARY

The NeuroPace responsive neurostimulation system (RNS) has revolutionized the care of patients suffering from focal epilepsy since its approval in 2014. One major advantage of this device is its innate ability to gather long-term electrocorticographic (ECoG) data that the device uses in its novel closed-loop treatment paradigm. Beyond the standard stimulation treatments, which have been demonstrated to be safe and well-tolerated, the data collected by the RNS provide valuable information, such as the long-term circadian and ultradian variations that affect seizure risk, obtained under naturalistic conditions. Additionally, these data inform future surgical procedures, supplementing clinically reported seizures by patients, assessing the response to newly added anti-seizure medications, helping to forecast the risk of future seizures, and understanding the mechanisms of certain long-term outcomes in patients with postsurgical epilepsy. By leveraging these data, the delivery of high-quality clinical care for patients with epilepsy can only be enhanced. Finally, these data open significant avenues of research, including machine learning and artificial intelligence algorithms, which may also translate to improved outcomes in patients who struggle with recurrent seizures.

Utility of Chronic Intracranial Electroencephalography in Responsive Neurostimulation Therapy

Responsive neurostimulation (RNS) therapy is an effective treatment for reducing seizures in some patients with focal epilepsy. Utilizing a chronically implanted device, RNS involves monitoring brain activity signals for user-defined patterns of seizure activity and delivering electrical stimulation in response. Devices store chronic data including counts of detected activity patterns and brief recordings of intracranial electroencephalography signals. Data platforms for reviewing stored chronic data retrospectively may be used to evaluate therapy performance and to fine-tune detection and stimulation settings. New frontiers in RNS research can leverage raw chronic data to reverse engineer neurostimulation mechanisms and improve therapy effectiveness.

Effects of season, daytime, sex, and stress on the incidence, latency, frequency, severity, and duration of neonatal seizures in a rat model of birth asphyxia

Neonatal seizures are common in newborn infants after birth asphyxia. They occur more frequently in male than female neonates, but it is not known whether sex also affects seizure severity or duration. Furthermore, although stress and diurnal, ultradian, circadian, or multidien cycles are known to affect epileptic seizures in adults, their potential impact on neonatal seizures is not understood. This prompted us to examine the effects of season, daytime, sex, and stress on neonatal seizures in a rat model of birth asphyxia. Seizures monitored in 176 rat pups exposed to asphyxia on 40 experimental days performed over 3 years were evaluated. All rat pups exhibited seizures when exposed to asphyxia at postnatal day 11 (P11), which in terms of cortical development corresponds to term human babies. A first examination of these data indicated a seasonal variation, with the highest seizure severity in the spring. Sex and daytime did not affect seizure characteristics. However, when rat pups were subdivided into animals that were exposed to acute (short-term) stress after asphyxia (restraint and i.p. injection of vehicle) and animals that were not exposed to this stress, the seizures in stress-exposed rats were more severe but less frequent. Acute stress induced an increase in hippocampal microglia density in sham-exposed rat pups, which may have an additive effect on microglia activation induced by asphyxia. When seasonal data were separately analyzed for stress-exposed vs. non-stress-exposed rat pups, no significant seasonal variation was observed. This study illustrates that without a detailed analysis of all factors, the data would have erroneously indicated significant seasonal variability in the severity of neonatal seizures. Instead, the study demonstrates that even mild, short-lasting postnatal stress has a profound effect on asphyxia-induced seizures, most likely by increasing the activity of the hypothalamic-pituitary-adrenal axis. It will be interesting to examine how postnatal stress affects the treatment and adverse outcomes of birth asphyxia and neonatal seizures in the rat model used here.

Resting-state background features demonstrate multidien cycles in long-term EEG device recordings

Background

Longitudinal EEG recorded by implanted devices is critical for understanding and managing epilepsy. Recent research reports patient-specific, multi-day cycles in device-detected epileptiform events that coincide with increased likelihood of clinical seizures. Understanding these cycles could elucidate mechanisms generating seizures and advance drug and neurostimulation therapies.

Objective/Hypothesis

We hypothesize that seizure-correlated cycles are present in background neural activity, independent of interictal epileptiform spikes, and that neurostimulation may disrupt these cycles.

Methods

We analyzed regularly-recorded seizure-free data epochs from 20 patients implanted with a responsive neurostimulation (RNS) device for at least 1.5 years, to explore the relationship between cycles in device-detected interictal epileptiform activity (dIEA), clinician-validated interictal spikes, background EEG features, and neurostimulation.

Results

Background EEG features tracked the cycle phase of dIEA in all patients (AUC: 0.63 [0.56 - 0.67]) with a greater effect size compared to clinically annotated spike rate alone (AUC: 0.55 [0.53-0.61], p < 0.01). After accounting for circadian variation and spike rate, we observed significant population trends in elevated theta and beta band power and theta and alpha connectivity features at the cycle peaks (sign test, p < 0.05). In the period directly after stimulation we observe a decreased association between cycle phase and EEG features compared to background recordings (AUC: 0.58 [0.55-0.64]).

Conclusions

Our findings suggest that seizure-correlated dIEA cycles are not solely due to epileptiform discharges but are associated with background measures of brain state; and that neurostimulation may disrupt these cycles. These results may help elucidate mechanisms underlying seizure generation, provide new biomarkers for seizure risk, and facilitate monitoring, treating, and managing epilepsy with implantable devices.

Responsive Neurostimulation of the Anterior Thalamic Nuclei in Refractory Genetic Generalized Epilepsy: A Case Series

Genetic generalized epilepsies (GGEs) are thought to represent disorders of thalamocortical networks. There are currently no well-established non-pharmacologic treatment options for patients with drug-resistant GGE. NeuroPace's Responsive Neurostimulation (RNS) System was approved by the United States Food and Drug Administration to treat focal seizures with up to two ictal foci. We report on three adults with drug-resistant GGE who were treated with thalamic RNS. Given the severity of their epilepsies and the potential ictogenic role of the thalamus in the pathophysiology of GGE, the RNS System was palliatively implanted with leads in the bilateral anterior thalamic nuclei (ANT) of these patients. The ANT was selected because it was demonstrated to be a safe target. We retrospectively evaluated metrics including seizure frequency over 18-32 months. One patient required explantation due to infection. The other two patients were clinical responders. By the end of the observation period reported here, one patient was seizure-free for over 9 months. All three self-reported an improved quality of life. The clinical response observed in these patients provides 'proof-of-principle' that GGE may be treatable with responsive thalamic stimulation. Our results support proceeding to a larger study investigating the efficacy and safety of thalamic RNS in drug-resistant GGE.

Practical considerations in epilepsy neurostimulation

Neuromodulation is a key therapeutic tool for clinicians managing patients with drug-resistant epilepsy. Multiple devices are available with long-term follow-up and real-world experience. The aim of this review is to give a practical summary of available neuromodulation techniques to guide the selection of modalities, focusing on patient selection for devices, common approaches and techniques for initiation of programming, and outpatient management issues. Vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (DBS-ANT), and responsive neurostimulation (RNS) are all supported by randomized controlled trials that show safety and a significant impact on seizure reduction, as well as a suggestion of reduction in the risk of sudden unexplained death in epilepsy (SUDEP). Significant seizure reductions are observed after 3 months for DBS, RNS, and VNS in randomized controlled trials, and efficacy appears to improve with time out to 7 to 10 years of follow-up for all modalities, albeit in uncontrolled follow-up or retrospective studies. A significant number of patients experience seizure-free intervals of 6 months or more with all three modalities. Number and location of epileptogenic foci are important factors affecting efficacy, and together with comorbidities such as severe mood or sleep disorders, may influence the choice of modality. Programming has evolved-DBS is typically initiated at lower current/voltage than used in the pivotal trial, whereas target charge density is lower with RNS, however generalizable optimal parameters are yet to be defined. Noninvasive brain stimulation is an emerging stimulation modality, although it is currently not used widely. In summary, clinical practice has evolved from those established in pivotal trials. Guidance is now available for clinicians who wish to expand their approach, and choice of neuromodulation technique may be tailored to individual patients based on their epilepsy characteristics, risk tolerance, and preferences.

Patient-specific structural connectivity informs outcomes of responsive neurostimulation for temporal lobe epilepsy

OBJECTIVE

Responsive neurostimulation is an effective therapy for patients with refractory mesial temporal lobe epilepsy. However, clinical outcomes are variable, few patients become seizure-free, and the optimal stimulation location is currently undefined. The aim of this study was to quantify responsive neurostimulation in the mesial temporal lobe, identify stimulation-dependent networks associated with seizure reduction, and determine if stimulation location or stimulation-dependent networks inform outcomes.

METHODS

We modeled patient-specific volumes of tissue activated and created probabilistic stimulation maps of local regions of stimulation across a retrospective cohort of 22 patients with mesial temporal lobe epilepsy. We then mapped the network stimulation effects by seeding tractography from the volume of tissue activated with both patient-specific and normative diffusion-weighted imaging. We identified networks associated with seizure reduction across patients using the patient-specific tractography maps and then predicted seizure reduction across the cohort.

RESULTS

Patient-specific stimulation-dependent connectivity was correlated with responsive neurostimulation effectiveness after cross-validation (p = .03); however, normative connectivity derived from healthy subjects was not (p = .44). Increased connectivity from the volume of tissue activated to the medial prefrontal cortex, cingulate cortex, and precuneus was associated with greater seizure reduction.

SIGNIFICANCE

Overall, our results suggest that the therapeutic effect of responsive neurostimulation may be mediated by specific networks connected to the volume of tissue activated. In addition, patient-specific tractography was required to identify structural networks correlated with outcomes. It is therefore likely that altered connectivity in patients with epilepsy may be associated with the therapeutic effect and that utilizing patient-specific imaging could be important for future studies. The structural networks identified here may be utilized to target stimulation in the mesial temporal lobe and to improve seizure reduction for patients treated with responsive neurostimulation.

Seizure control during the COVID-19 pandemic: Correlating Responsive Neurostimulation System data with patient reports

Objective

To understand the impact of the Coronavirus Disease-2019 (COVID-19) pandemic on seizure frequency in persons with epilepsy with a Responsive Neurostimulation (RNS) system implanted.

Methods

Weekly long episode counts (LEC) were used as a proxy for seizures for six months pre-COVID-19 and during the COVID-19 period. Telephone surveys and chart reviews were conducted to assess patient mental health during the pandemic. The change in LEC between the two time periods was correlated to reported stressors.

Results

Twenty patients were included. Comparing the pre-COVID-19 period to the COVID-19 period, we found that only 5 (25%) patients had increased seizures, which was positively correlated with change in anti-seizure medications (ASM, p = 0.03) and bitemporal seizures (p = 0.03). Increased seizures were not correlated to anxiety (p = 1.00), depression (p = 0.58), and sleep disturbances (p = 1.00). The correlation between RNS-detected and patient-reported seizures was poor (p = 0.32).

Conclusions

Most of our patients did not have an increase in seizures following the COVID-19 pandemic. Changes in ASM and bitemporal seizures were positively correlated to increased LEC. There was no correlation between pandemic-related stress and seizures in those found to have increased seizures.

Significance

This is the first study correlating RNS-derived objective LECs with patient self-reports and potential seizure risk factors during the COVID-19 pandemic.

Forecasting Seizure Clusters from Chronic Ambulatory Electrocorticography

Seizure clusters are seizures that occur in rapid succession during periods of heightened seizure risk and are associated with substantial morbidity and sudden unexpected death in epilepsy. The objective of this feasibility study is to evaluate the performance of a novel seizure cluster forecasting algorithm. Chronic ambulatory electrocorticography recorded over an average of 38 months in 10 subjects with drug-resistant epilepsies was analyzed pseudoprospectively by dividing data into training (first 85%) and validation periods. For each subject, the probability of seizure clustering, derived from the Kolmogorov-Smirnov statistic using a novel algorithm, was forecasted in the validation period using individualized autoregressive models that were optimized from training data. The primary outcome of this study was the mean absolute scaled error (MASE) of 1-day horizon forecasts. From 10 subjects, 394±142 (mean±SD) ECoG-based seizure events were extracted for analysis, representing a span of 38±27 months of recording. MASE across all subjects were 0.74±0.09, 0.78±0.09, and 0.83±0.07 at 0.5-, 1-, and 2-day horizons. The feasibility study demonstrates that seizure clusters are quasiperiodic and can be forecasted to clinically meaningful horizons. Pending validation in larger cohorts, the forecasting approach described herein may herald chronotherapy during imminent heightened seizure vulnerability.

Dogs as a Natural Animal Model of Epilepsy

Epilepsy is a common neurological disease in both humans and domestic dogs, making dogs an ideal translational model of epilepsy. In both species, epilepsy is a complex brain disease characterized by an enduring predisposition to generate spontaneous recurrent epileptic seizures. Furthermore, as in humans, status epilepticus is one of the more common neurological emergencies in dogs with epilepsy. In both species, epilepsy is not a single disease but a group of disorders characterized by a broad array of clinical signs, age of onset, and underlying causes. Brain imaging suggests that the limbic system, including the hippocampus and cingulate gyrus, is often affected in canine epilepsy, which could explain the high incidence of comorbid behavioral problems such as anxiety and cognitive alterations. Resistance to antiseizure medications is a significant problem in both canine and human epilepsy, so dogs can be used to study mechanisms of drug resistance and develop novel therapeutic strategies to benefit both species. Importantly, dogs are large enough to accommodate intracranial EEG and responsive neurostimulation devices designed for humans. Studies in epileptic dogs with such devices have reported ictal and interictal events that are remarkably similar to those occurring in human epilepsy. Continuous (24/7) EEG recordings in a select group of epileptic dogs for >1 year have provided a rich dataset of unprecedented length for studying seizure periodicities and developing new methods for seizure forecasting. The data presented in this review substantiate that canine epilepsy is an excellent translational model for several facets of epilepsy research. Furthermore, several techniques of inducing seizures in laboratory dogs are discussed as related to therapeutic advances. Importantly, the development of vagus nerve stimulation as a novel therapy for drug-resistant epilepsy in people was based on a series of studies in dogs with induced seizures. Dogs with naturally occurring or induced seizures provide excellent large-animal models to bridge the translational gap between rodents and humans in the development of novel therapies. Furthermore, because the dog is not only a preclinical species for human medicine but also a potential patient and pet, research on this species serves both veterinary and human medicine.

Owner's Perception of Seizure Detection Devices in Idiopathic Epileptic Dogs

Accurate knowledge of seizure frequency is key to optimising treatment. New methods for detecting epileptic seizures are currently investigated in humans, which rely on changes in biomarkers, also called seizure detection devices. Critical to device development, is understanding user needs and requirements. No information on this subject has been published in veterinary medicine. Many dog health collars are currently on the market, but none has proved to be a promising seizure detector. An online survey was created and consisted of 27 open, closed, and scaled questions divided over two parts: part one focused on general questions related to signalment and seizure semiology, the second part focused specifically on the use of seizure detection devices. Two hundred and thirty-one participants caring for a dog with idiopathic epilepsy, were included in the study. Open questions were coded using descriptive coding by two of the authors independently. Data was analysed using descriptive statistics and binary logistic regression. Our results showed that the unpredictability of seizures plays a major part in the management of canine epilepsy and dog owners have a strong desire to know when a seizure occurs. Nearly all dog owners made changes in their daily life, mainly focusing on intensifying supervision. Owners believed seizure detection devices would improve their dog's seizure management, including a better accuracy of seizure frequency and the ability to administer emergency drugs more readily. Owners that were already keeping track of their dog's seizures were 4.2 times more likely to show confidence in using seizure detection devices to manage their pet's seizures, highlighting the need for better monitoring systems. Our results show that there is a receptive market for wearable technology as a new management strategy in canine epilepsy and this topic should be further explored.

Seizure documentation in people living with epilepsy

Seizure documentation is an essential component of epilepsy management. Not all persons with epilepsy choose to document their seizures, but many view the practice as essential to managing their disease. While seizure documentation is a valuable aspect of patient care, clinicians and patients must remain aware that seizure underreport and overreport commonly occur due to lack of seizure awareness. Additionally, in rare cases, persons with epilepsy may intentionally conceal their seizures from clinicians. The continued development of electronic seizure diaries and epilepsy self-management software provides patients with new and expanding options for seizure documentation and disease management. In order for these tools to be utilized most effectively, patient input must be central to their development. Given the limitations of seizure documentation, the development of accurate, non-invasive seizure detection devices is crucial for accurate seizure monitoring.

Chronic electroencephalography in epilepsy with a responsive neurostimulation device: current status and future prospects

INTRODUCTION

Implanted neurostimulation devices are gaining traction as therapeutic options for people with certain forms of drug-resistant focal epilepsy. Some of these devices enable chronic electroencephalography (cEEG), which offers views of the dynamics of brain activity in epilepsy over unprecedented time horizons.

AREAS COVERED

This review focuses on clinical insights and basic neuroscience discoveries enabled by analyses of cEEG from an exemplar device, the NeuroPace RNS® System. Applications of RNS cEEG covered here include counting and lateralizing seizures, quantifying medication response, characterizing spells, forecasting seizures, and exploring mechanisms of cognition. Limitations of the RNS System are discussed in the context of next-generation devices in development.

EXPERT OPINION

The wide temporal lens of cEEG helps capture the dynamism of epilepsy, revealing phenomena that cannot be appreciated with short duration recordings. The RNS System is a vanguard device whose diagnostic utility rivals its therapeutic benefits, but emerging minimally invasive devices, including those with subscalp recording electrodes, promise to be more applicable within a broad population of people with epilepsy. Epileptology is on the precipice of a paradigm shift in which cEEG is a standard part of diagnostic evaluations and clinical management is predicated on quantitative observations integrated over long timescales.

Effects of anterior thalamic nuclei stimulation on hippocampal activity: Chronic recording in a patient with drug-resistant focal epilepsy

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Devices for RNS and thalamic DBS were implanted in a single person with epilepsy.

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RNS electrocorticography enabled characterization of acute and chronic DBS effects.

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DBS caused acute, phasic, frequency-dependent responses in hippocampus and cortex.

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DBS modulated functional connectivity and suppressed epileptiform activity over time.

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Chronic electrocorticography elucidates progressive effects of thalamic stimulation.

Implanted neurostimulation devices are gaining traction as palliative treatment options for certain forms of drug-resistant epilepsy, but clinical utility of these devices is hindered by incomplete mechanistic understanding of their therapeutic effects. Approved devices for anterior thalamic nuclei deep brain stimulation (ANT DBS) are thought to work at a network level, but limited sensing capability precludes characterization of neurophysiological effects outside the thalamus. Here, we describe a patient with drug-resistant temporal lobe epilepsy who was implanted with a responsive neurostimulation device (RNS System), involving hippocampal and ipsilateral temporal neocortical leads, and subsequently received ANT DBS. Over 1.5 years, RNS System electrocorticography enabled multiscale characterization of neurophysiological effects of thalamic stimulation. In brain regions sampled by the RNS System, ANT DBS produced acute, phasic, frequency-dependent responses, including suppression of hippocampal low frequency local field potentials. ANT DBS modulated functional connectivity between hippocampus and neocortex. Finally, ANT DBS progressively suppressed hippocampal epileptiform activity in relation to the extent of hippocampal theta suppression, which informs stimulation parameter selection for ANT DBS. Taken together, this unique clinical scenario, involving hippocampal recordings of unprecedented chronicity alongside ANT DBS, sheds light on the therapeutic mechanism of thalamic stimulation and highlights capabilities needed in next-generation devices.

Long-term brain network reorganization predicts responsive neurostimulation outcomes for focal epilepsy

Responsive neurostimulation (RNS) devices, able to detect imminent seizures and to rapidly deliver electrical stimulation to the brain, are effective in reducing seizures in some patients with focal epilepsy. However, therapeutic response to RNS is often slow, is highly variable, and defies prognostication based on clinical factors. A prevailing view holds that RNS efficacy is primarily mediated by acute seizure termination; yet, stimulations greatly outnumber seizures and occur mostly in the interictal state, suggesting chronic modulation of brain networks that generate seizures. Here, using years-long intracranial neural recordings collected during RNS therapy, we found that patients with the greatest therapeutic benefit undergo progressive, frequency-dependent reorganization of interictal functional connectivity. The extent of this reorganization scales directly with seizure reduction and emerges within the first year of RNS treatment, enabling potential early prediction of therapeutic response. Our findings reveal a mechanism for RNS that involves network plasticity and may inform development of next-generation devices for epilepsy.

A Primer on Hyperdimensional Computing for iEEG Seizure Detection

A central challenge in today's care of epilepsy patients is that the disease dynamics are severely under-sampled in the currently typical setting with appointment-based clinical and electroencephalographic examinations. Implantable devices to monitor electrical brain signals and to detect epileptic seizures may significantly improve this situation and may inform personalized treatment on an unprecedented scale. These implantable devices should be optimized for energy efficiency and compact design. Energy efficiency will ease their maintenance by reducing the time of recharging, or by increasing the lifetime of their batteries. Biological nervous systems use an extremely small amount of energy for information processing. In recent years, a number of methods, often collectively referred to as brain-inspired computing, have also been developed to improve computation in non-biological hardware. Here, we give an overview of one of these methods, which has in particular been inspired by the very size of brains' circuits and termed hyperdimensional computing. Using a tutorial style, we set out to explain the key concepts of hyperdimensional computing including very high-dimensional binary vectors, the operations used to combine and manipulate these vectors, and the crucial characteristics of the mathematical space they inhabit. We then demonstrate step-by-step how hyperdimensional computing can be used to detect epileptic seizures from intracranial electroencephalogram (EEG) recordings with high energy efficiency, high specificity, and high sensitivity. We conclude by describing potential future clinical applications of hyperdimensional computing for the analysis of EEG and non-EEG digital biomarkers.

Patient-detectable responsive neurostimulation as a seizure warning system

Many people with epilepsy are not aware of their seizures or do not have reliable auras. The responsive neurostimulation system (RNS) delivers stimulation triggered by intracranial epileptiform activity. If an epileptiform pattern continues, the RNS repeats stimulation up to five times per event. The RNS can cause acute stimulation-related symptoms that can be avoided by reducing stimulation. Because each of the five therapies can be programmed independently, it may be possible to program the latter therapies to induce a seizure warning. The goal of this study was to determine what proportion of patients could have tolerable symptoms safely elicited by stimulation, ultimately for the purpose of subjective seizure recognition. Of 18 patients, 12 (67%) had induced symptoms, which were tolerable in 11. Phosphenes were most common. We also present one patient in whom the fifth therapy was set to induce a symptom for early recognition and treatment of clusters of focal impaired awareness seizures, which were previously unrecognized and had led to days of disabling cognitive impairment. This protocol prevented disabling clusters successfully for several years. The findings suggest the RNS can provide a seizure warning, potentially improving safety and quality of life, and leading to prevention of clinical seizures or clusters in select patients.

Mood and quality of life in patients treated with brain-responsive neurostimulation: The value of earlier intervention

OBJECTIVE

To establish whether earlier treatment using direct brain-responsive neurostimulation for medically intractable focal-onset seizures is associated with better mood and Quality of Life (QoL) compared to later treatment intervention.

METHODS

Data were retrospectively analyzed from prospective clinical trials of a direct brain-responsive neurostimulator (RNS® System) for treatment of adults with medically intractable focal-onset epilepsy. Participants completed the Quality of Life in Epilepsy Inventory (QOLIE-31) yearly through 9 years of follow-up and the Beck Depression Inventory-II (BDI-II) through 2 years of follow-up. Changes in each assessment after treatment with responsive neurostimulation were calculated for patients who began treatment within 10 years of seizure onset (early) and those who began treatment 20 years or more after seizure onset (late).

RESULTS

The median duration of epilepsy was 18.3 years at enrollment. At 9 years, both the early (N = 51) and late (N = 109) treatment groups experienced similar and significant reductions in the frequency of disabling seizures (73.4% and 77.8%, respectively). The early treatment patients had significant improvements in QoL and mood. However, the late treatment patients not only failed to show these improvements but also declined in the emotional QoL subscale.

CONCLUSIONS

Patients treated with brain-responsive neurostimulation earlier in the course of their epilepsy show significant improvements in multiple domains of QoL and mood that are not observed in patients treated later in the course of their epilepsy despite similar efficacy in seizure reduction. Even with similar and substantial reductions in seizure frequency, the comorbidities of uncontrolled epilepsy may be less responsive to treatment when too many years have passed. The results of this study suggest that, as with resective and ablative surgery, treatment with brain-responsive neurostimulation should be delivered as early as possible in the course of medically resistant epilepsy to maximize the opportunity for improvements in mood and QoL.

Proceedings of the Sleep and Epilepsy Workshop: Section 1 Decreasing Seizures-Improving Sleep and Seizures, Themes for Future Research

Epileptic seizures, sleep, and circadian timing share bilateral interactions, but concerted work to characterize these interactions and to leverage them to the advantage of patients with epilepsy remains in beginning stages. To further the field, a multidisciplinary group of sleep physicians, epileptologists, circadian timing experts, and others met to outline the state of the art, gaps of knowledge, and suggest ways forward in clinical, translational, and basic research. A multidisciplinary panel of experts discussed these interactions, centered on whether improvements in sleep or circadian rhythms improve decrease seizure frequency. In addition, education about sleep was lacking in among patients, their families, and physicians, and that focus on education was an extremely important "low hanging fruit" to harvest. Improvements in monitoring technology, experimental designs sensitive to the rigor required to dissect sleep versus circadian influences, and clinical trials in seizure reduction with sleep improvements were appropriate.

Acute effects of brain-responsive neurostimulation in drug-resistant partial onset epilepsy

OBJECTIVE

Understanding the acute effects of responsive stimulation (AERS) based on intracranial EEG (iEEG) recordings in ambulatory patients with drug-resistant partial epilepsy, and correlating these with changes in clinical seizure frequency, may help clinicians more efficiently optimize responsive stimulation settings.

METHODS

In patients implanted with the NeuroPace® RNS® System, acute changes in iEEG spectral power following active and sham stimulation periods were quantified and compared within individual iEEG channels. Additionally, acute stimulation-induced acute iEEG changes were compared within iEEG channels before and after patients experienced substantial reductions in clinical seizure frequency.

RESULTS

Responsive stimulation resulted in a 20.7% relative decrease in spectral power in the 2-4 second window following active stimulation, compared to sham stimulation. On several detection channels, the AERS features changed when clinical outcomes improved but were relatively stable otherwise. AERS change direction associated with clinical improvement was generally consistent within detection channels.

CONCLUSIONS

In this retrospective analysis, patients with drug-resistant partial epilepsy treated with direct brain-responsive neurostimulation showed an acute stimulation related reduction in iEEG spectral power that was associated with reductions in clinical seizure frequency.

SIGNIFICANCE

Identifying favorable stimulation related changes in iEEG activity could help physicians to more rapidly optimize stimulation settings for each patient.

Under-sampling in epilepsy: Limitations of conventional EEG

The cyclical structure of epilepsy was recently (re)-discovered through years-long intracranial electroencephalography (EEG) obtained with implanted devices. In this review, we discuss how new revelations from chronic EEG relate to the practice and interpretation of conventional EEG. We argue for an electrographic definition of seizures and highlight the caveats of counting epileptiform discharges in EEG recordings of short duration. Limitations of conventional EEG have practical implications with regard to titrating anti-seizure medications and allowing patients to drive, and we propose that chronic monitoring of brain activity could greatly improve epilepsy care. An impending paradigm shift in epilepsy will involve using next-generation devices for chronic EEG to leverage known biomarkers of disease state.

Brain-responsive corticothalamic stimulation in the centromedian nucleus for the treatment of regional neocortical epilepsy

OBJECTIVE

The aim of the study was to determine if corticothalamic responsive stimulation targeting the centromedian nucleus of the thalamus (CMT) is a potential treatment for neocortical epilepsies with regional onsets.

METHODS

We assessed efficacy and safety of CMT and neocortical responsive stimulation, detection, and stimulation programming, methods for implantation, and location and patterns of electrographic seizure onset and spread in 7 patients with medically intractable focal seizures with a regional neocortical onset.

RESULTS

The median follow-up duration was 17 months (average: 17 months, range: 8-28 months). The median % reduction in disabling seizures (excludes auras) in the 7 patients was 88% (mean: 80%, range: 55-100%). The median % reduction in all seizure types (disabling + auras) was 73% (mean: 67%, range: 15-94%). There were no adverse events related to implantation of the responsive neurostimulator and leads or related to the delivery of responsive stimulation. Stimulation-related contralateral paresthesias were addressed by adjusting stimulation parameters in the clinic during stimulation testing. Electrographic seizures were detected in the CMT and neocortex in all seven patients. Four patients had simultaneous or near simultaneous seizure onsets in the neocortex and CMT and three had onsets in the neocortex with spread to the CMT.

CONCLUSION

In this small series of patients with medically intractable focal seizures and regional neocortical onset, responsive neurostimulation to the neocortex and CMT improved seizure control and was well tolerated.

SIGNIFICANCE

Responsive corticothalamic neurostimulation of the CMT and neocortex is a potential treatment for patients with regional neocortical epilepsies.

The RNS System: brain-responsive neurostimulation for the treatment of epilepsy

Introduction: Epilepsy affects more than 1% of the US population, and over 30% of adults with epilepsy do not respond to antiseizure medications without life-impacting medication-related side effects. Resection of the seizure focus is not an option for many patients because it would cause unacceptable neurological or cognitive harm. For these patients, neuromodulation has emerged as a nondestructive, effective, and safe alternative. The NeuroPace® RNS® System, the only brain-responsive neurostimulation device, records neural activity from leads placed at one or two seizure foci. When the neurostimulator detects epileptiform activity, as defined for each patient by his or her physician, brief pulses of electrical stimulation are delivered to normalize the activity.Areas covered: This review describes the RNS System, the results of multi-year clinical trials, and the research discoveries enabled by the chronic ambulatory brain data collected by the RNS System.Expert commentary: Brain-responsive neurostimulation could potentially be used to treat any episodic neurological disorder that's accompanied by a neurophysiological biomarker of severity. Combining advanced machine learning approaches with the chronic ambulatory brain data collected by the RNS System could eventually enable automatic fine-tuning of detection and stimulation for each patient, creating a general-purpose neurotechnological platform for precision medicine.