RNS System Research Articles

Bilateral pulvinar responsive neurostimulation for bilateral multifocal posteriorly dominant drug resistant epilepsy.

To describe four cases of Responsive Neurostimulation (RNS) in the bilateral pulvinar nuclei (PUL) in individuals with drug resistant epilepsy (DRE). This will show that due to widespread PUL connectivity, bilateral PUL RNS may be an option for some individuals with bilateral multifocal epilepsy. This study comprises two centers' experience with bilateral PUL RNS for DRE. Patients treated with bilateral PUL RNS at Westchester Medical Center (Valhalla, NY) and Corewell Health (Grand Rapids, MI) between the years 2019 and 2022 were analyzed and described. Presented here are methods for target selection, device programming, and clinical outcomes. Two patients with Lennox-Gastaut phenotype (aged 13 and 21 years) with posteriorly dominant discharges were implanted with bilateral PUL electrodes. Additionally, two patients (aged 20 and 31 years) with independent left and right occipital bilateral multifocal seizure onsets were implanted with bilateral RNS devices targeting the ipsilateral PUL and ipsilateral occipital cortex. Subclinical and clinical seizures were captured by RNS electrocorticography (ECoG) in all patients. RNS implantation and treatment was well-tolerated without adverse effects in all patients. Relative to baseline, two patients had 25% and 50% reduction in disabling seizures, and two patients had 71% and 100% reduction in disabling seizures. Stimulation paradigms utilized high frequency stimulation in both Lennox-Gastaut phenotype patients. Low frequency (individualized to the terminal ictal frequencies) stimulation was effective in the two bioccipital patients. RNS with electrode placement targeting bilateral PUL is safe, and no adverse effects have been attributable to the pulvinar electrode placement. PUL responsive neurostimulation is potentially effective for patients with bilateral multifocal, posteriorly dominant DRE. Both high and low frequency responsive stimulation are treatment options. Longer follow-up will shed light on the ultimate reduction of seizure burden. We describe four cases where stimulation devices were placed in the Pulvinar area of the thalamus (central sensory area in the brain). This is very unique and different location than where these devices are typically placed. These patients all had great outcomes with marked seizure reduction, demonstrating that this placement is both safe and effective.

Responsive neurostimulation of the frontal lobe for the detection and treatment of seizures in intractable epilepsy due to tuberous sclerosis complex: illustrative case.

Responsive neurostimulation (RNS) is often considered to be a palliative therapy for drug-resistant epilepsy (DRE) and is generally not considered to be a treatment for patients with tuberous sclerosis complex (TSC). Here, the authors present the case of a 24-year-old male with TSC who obtained seizure freedom following RNS device implantation. Prior to RNS device implantation, the patient underwent tuberectomies, subependymal giant cell astrocytoma resection, vagus nerve stimulator placement, and left frontal lobe resection but continued to have frequent seizures. An RNS device was implanted, which initially led to a decrease in seizures, but he continued to have 12 seizures per month. He then underwent lead revision for stimulation via a different electrode. After that lead change, he had no seizures for almost 3 years. In the following 3 years, he had two episodes of breakthrough seizures, both of which occurred with medication weans. Although the patient still requires antiseizure medication, he has had years of seizure freedom with RNS therapy. This study exhibits the potential effectiveness of RNS therapy for patients with TSC and DRE. RNS should be considered for patients with TSC when other therapies have not sufficiently treated their epilepsy. https://thejns.org/doi/10.3171/CASE23411.

Seizure forecasting with ultra long-term EEG signals

ObjectiveThe apparent randomness of seizure occurrence affects greatly the quality of life of persons with epilepsy. Since seizures are often phase-locked to multidien cycles of interictal epileptiform activity, a recent forecasting scheme, exploiting RNS data, is capable of forecasting seizures days in advance. MethodsWe tested the use of a bandpass filter to capture the universal mid-term dynamics enabling both patient-specific and cross-patient forecasting. In a retrospective study, we explored the feasibility of the scheme on three long-term recordings obtained by the NeuroPace RNS System, the NeuroVista intracranial, and the UNEEG subcutaneous devices, respectively. ResultsBetter-than-chance forecasting was observed in 15 (83 %) of 18 patients, and in 16 (89 %) patients for daily and hourly forecast, respectively. Meaningful forecast up to 30 days could be achieved in 4 (22 %) patients for hourly forecast frequency. The cross-patient performance decreased only marginally and was patient-wise strongly correlated with the patient-specific one. Comparable performance was obtained for NeuroVista and UNEEG data sets. SignificanceThe feasibility of cross-patient forecasting supports the universal importance of mid-term dynamics for seizure forecasting, demonstrates promising inter-subject-applicability of the scheme on ultra long-term EEG recordings, and highlights its huge potential for clinical use.

Transcranial magnetic stimulation and magnetoencephalography are feasible alternatives to invasive methods in optimizing responsive neurostimulation device placement

Responsive neurostimulation (RNS) is a treatment option for patients with refractory epilepsy when surgical resection is not possible due to overlap of the irritative zone and eloquent cortex. Presurgical evaluations for RNS placement typically rely on invasive methods. This study investigated the potential of transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG) to provide key presurgical information non-invasively. We hypothesized that these non-invasive methods may assist in optimizing RNS placement by providing useful information for seizure localization by MEG and eloquent cortex mapping by TMS. A retrospective chart review identified nine patients who underwent RNS placement (mean age = 20.4 years [SD = 5.6], two-thirds were female). Characterization of the irritative zone using MEG was successful in eight of nine patients. Non-invasive mapping of relevant eloquent cortex was attempted in all patients. TMS was successful in eight of nine patients, and MEG was successful in two of six patients. Importantly, patients mapped with non-invasive modalities experienced an average seizure reduction of 77 % at their most recent clinic visit, compared to 75 % seizure reduction in those with invasive evaluations, indicating appropriate RNS placement. These data demonstrate that TMS and MEG can provide key information for RNS and may be feasible alternatives to invasive methods for assisting in decision making regarding RNS placement. Non-invasive methods for determining RNS placement have a high rate of success when data from multiple non-invasive modalities converge and can inform more accurate placement of intracranial electrodes prior to RNS placement or mitigate their need.

Bilateral centromedian nucleus of thalamus responsive neurostimulation for pediatric-onset drug-resistant epilepsy.

Neuromodulation therapies offer an efficacious treatment alternative for patients with drug-resistant epilepsy (DRE), particularly those unlikely to benefit from surgical resection. Here we present our retrospective single-center case series of patients with pediatric-onset DRE who underwent responsive neurostimulation (RNS) depth electrode implantation targeting the bilateral centromedian nucleus (CM) of the thalamus between October 2020 and October 2022. Sixteen patients were identified; seizure outcomes, programming parameters, and complications at follow-up were reviewed. The median age at implantation was 13 years (range 3.6-22). Six patients (38%) were younger than 12 years of age at the time of implantation. Ictal electroencephalography (EEG) patterns during patients' most disabling seizures were reliably detected. Ten patients (62%) achieved 50% or greater reduction in seizure frequency at a median 1.3 years (range 0.6-2.6) of follow-up. Eight patients (50%) experienced sensorimotor side effects, and three patients (19%) had superficial pocket infection, prompting the removal of the RNS device. Side effects of stimulation were experienced mostly in monopolar-cathodal configuration and alleviated with programming change to bipolar configuration or low-frequency stimulation. Closed-loop neurostimulation using RNS targeting bilateral CM is a feasible and useful therapy for patients with pediatric-onset DRE.

State-dependent effects of responsive neurostimulation depend on seizure localization.

Brain-responsive neurostimulation is firmly ensconced among treatment options for drug-resistant focal epilepsy, but over a quarter of patients treated with the RNS System do not experience meaningful seizure reduction. Initial titration of RNS therapy is typically similar for all patients, raising the possibility that treatment response might be enhanced by consideration of patient-specific variables. Indeed, small, single-center studies have yielded preliminary evidence that RNS System effectiveness depends on the brain state during which stimulation is applied. The generalizability of these findings remains unclear, however, and it is unknown whether state-dependent effects of responsive neurostimulation are also stratified by location of the seizure onset zone where stimulation is delivered. We aimed to determine whether state-dependent effects of the RNS System are evident in the large, diverse, multi-center cohort of RNS System clinical trial participants and to test whether these effects differ between mesiotemporal and neocortical epilepsies. Eighty-one of 256 patients who were treated with the RNS System across 31 centers during clinical trials met criteria for inclusion in this retrospective study. Risk states were defined in relation to phases of daily and multi-day cycles of interictal epileptiform activity that are thought to determine seizure likelihood. We found that the probabilities of risk state transitions depended on the stimulation parameter being changed, the starting seizure risk state, and the stimulated brain region. Changes in two commonly adjusted stimulation parameters, charge density and stimulation frequency, produced opposite effects on risk state transitions depending on seizure localization. Greater variance in acute risk state transitions was explained by state-dependent responsive neurostimulation for bipolar stimulation for neocortical epilepsies and for monopolar stimulation for mesiotemporal epilepsies. Variability in effectiveness of RNS System therapy across individuals may relate, at least partly, to the fact that current treatment paradigms do not account fully for fluctuations in brain states or locations of simulation sites. State-dependence of electrical brain stimulation may inform development of next-generation closed-loop devices that can detect changes in brain state and deliver adaptive, localization-specific patterns of stimulation to maximize therapeutic effects.

Robot-assisted, CT-guided placement of responsive neurostimulator system with bilateral centromedian thalamus depth electrodes for multifocal intractable epilepsy.

The responsive neurostimulator system has become increasingly popular in the surgical management of refractory epilepsy, with targeting of various thalamic nuclei showing promising results in select patients. A 42-year-old female presented for evaluation of refractory epilepsy consisting of generalized tonic-clonic and focal seizures with preserved awareness. Phase I and II monitoring suggested multifocal bilateral epilepsy with bilateral frontal onset, and the patient underwent robot-guided bilateral centromedian thalamic placement of the RNS System. In this operative video, the authors share their institutional experience and protocol utilizing the ExcelsiusGPS robot in the placement of the RNS System in the thalamus. The video can be found here: https://stream.cadmore.media/r10.3171/2024.4.FOCVID243.

Responsive neurostimulation of thalamic nuclei for regional and multifocal drug-resistant epilepsy in children and young adults.

Responsive neurostimulation (RNS) is a US FDA-approved form of neuromodulation to treat patients with focal-onset drug-resistant epilepsy (DRE) who are ineligible for or whose condition is refractory to resection. However, the FDA approval only extends to use in patients with one or two epileptogenic foci. Recent literature has shown possible efficacy of thalamic RNS in patients with Lennox-Gastaut syndrome and multifocal epilepsy. The authors hypothesized that RNS of thalamic nuclei may be effective in seizure reduction for patients with multifocal or regionalized-onset DRE. The authors performed a retrospective chart review of all patients who had an RNS device managed at Texas Children's Hospital between July 2016 and September 2023, with at least one active electrode in the thalamic nuclei and ≥ 12 months of postimplantation follow-up. Information conveyed by the patient or their caregiver provided data on the change in the clinical seizure frequency, quality of life (QOL), and seizure severity between the preimplantation baseline visit and the last office visit (LOV). Thirteen patients (ages 8-24 years) were identified with active RNS leads in thalamic nuclei (11 centromedian and 2 anterior nucleus). At LOV, 46% of patients reported 50%-100% clinical seizure reduction (classified as responders), 15% reported 25%-49% reduction, and 38% reported < 25% reduction or no change. Additionally, 42% of patients reported subjective improvement in QOL and 58% reported improved seizure severity. Patients with focal cortical dysplasia (FCD) responded strongly: 3 of 5 (60%) reported ≥ 80% reduction in seizure burden and improvement in seizure severity and QOL. Patients with multifocal epilepsy and bilateral thalamocortical leads also did well, with all 3 reporting ≥ 50% reduction in seizures. RNS of thalamic nuclei shows promising results in reducing seizure burden for patients with multifocal or regional-onset DRE, particularly in a bilateral thalamocortical configuration or when addressing an underlying FCD.

Seizure Cycles under Pharmacotherapy.

This study was undertaken to determine the effects of antiseizure medications (ASMs) on multidien (multiday) cycles of interictal epileptiform activity (IEA) and seizures and evaluate their potential clinical significance. We retrospectively analyzed up to 10 years of data from 88 of the 256 total adults with pharmacoresistant focal epilepsy who participated in the clinical trials of the RNS System, an intracranial device that keeps records of IEA counts. Following adjunctive ASM trials, we evaluated changes over months in (1) rates of self-reported disabling seizures and (2) multidien IEA cycle strength (spectral power for periodicity between 4 and 40 days). We used a survival analysis and the receiver operating characteristics to assess changes in IEA as a predictor of seizure control. Among 56 (33.3%) of the 168 adjunctive ASM trials suitable for analysis, ASM introduction was followed by an average 50 to 70% decrease in multidien IEA cycle strength and a concomitant 50 to 70% decrease in relative seizure rate for up to 12 months. Individuals with a ≥50% decrease in IEA cycle strength in the first 3 months of an ASM trial had a higher probability of remaining seizure responders (≥50% seizure rate reduction, p < 10-7) or super-responders (≥90%, p < 10-8) over the next 12 months. In this large cohort, a decrease in multidien IEA cycle strength following initiation of an adjunctive ASM correlated with seizure control for up to 12 months, suggesting that fluctuations in IEA mirror "disease activity" in pharmacoresistant focal epilepsy and may have clinical utility as a biomarker to predict treatment response. ANN NEUROL 2024;95:743-753.

Magnetoencephalography (MEG) Data Processing in Epilepsy Patients with Implanted Responsive Neurostimulation (RNS) Devices.

Drug-resistant epilepsy (DRE) is often treated with surgery or neuromodulation. Specifically, responsive neurostimulation (RNS) is a widely used therapy that is programmed to detect abnormal brain activity and intervene with tailored stimulation. Despite the success of RNS, some patients require further interventions. However, having an RNS device in situ is a hindrance to the performance of neuroimaging techniques. Magnetoencephalography (MEG), a non-invasive neurophysiologic and functional imaging technique, aids epilepsy assessment and surgery planning. MEG performed post-RNS is complicated by signal distortions. This study proposes an independent component analysis (ICA)-based approach to enhance MEG signal quality, facilitating improved assessment for epilepsy patients with implanted RNS devices. Three epilepsy patients, two with RNS implants and one without, underwent MEG scans. Preprocessing included temporal signal space separation (tSSS) and an automated ICA-based approach with MNE-Python. Power spectral density (PSD) and signal-to-noise ratio (SNR) were analyzed, and MEG dipole analysis was conducted using single equivalent current dipole (SECD) modeling. The ICA-based noise removal preprocessing method substantially improved the signal-to-noise ratio (SNR) for MEG data from epilepsy patients with implanted RNS devices. Qualitative assessment confirmed enhanced signal readability and improved MEG dipole analysis. ICA-based processing markedly enhanced MEG data quality in RNS patients, emphasizing its clinical relevance.

Safety & feasibility of responsive neurostimulation in children with refractory epilepsy: A single-center experience

ObjectivesResponsive neurostimulation (RNS) is a relatively recent addition to the epilepsy surgery armory, gaining FDA approval in 2013 for use in adults with intractable focal epilepsy. Data for the use of RNS system in patients less than 18 years of age is limited. We aim to determine the safety and feasibility of RNS in children with refractory epilepsy. MethodsA retrospective chart review was conducted for all patients who underwent RNS implantation at an urban tertiary children's hospital. Demographics of the patients were obtained, including age at the time of implant, MRI findings, seizure onset zone identification, and RNS targets. ResultsOut of a fourteen patient cohort, one patient had a post-operative complication of infection at surgical site requiring explantation. Thirteen out of 14 patients had immediate post-operative head imaging that was negative for hemorrhage, infarction, or skull fracture; one patient did not undergo head imaging. No patients reported a worsening clinical seizure frequency at a 6-month follow up visit. In the subset of patients who were implanted with RNS and did not undergo concurrent resections, there was a statistically significant reduction in the average number of long episodes at the most recent visit when compared to the 1-month post-operative visit (p = 0.0268). ConclusionsRNS is a feasible and safe option for children as young as six years with refractory epilepsy when appropriate seizure focus identification has been performed with stereo CT and stereo EEG evaluations, and can be used in conjunction with other surgical epilepsy treatment modalities. Two canister RNS placement is achievable for patients with a broad epileptogenic network or multifocal seizure onset zones.

Myasthenia gravis in a pediatric patient with Lennox-Gastaut syndrome following responsive neurostimulation device implantation: illustrative case.

Myasthenia gravis (MG) is an autoimmune disorder in which the postsynaptic acetylcholine receptor of the neuromuscular junction is destroyed by autoantibodies. The authors report a case of MG in a pediatric patient who also suffered from Lennox-Gastaut syndrome (LGS) and is one of a limited number of pediatric patients who have undergone placement of a responsive neurostimulation (RNS) device (NeuroPace). A 17-year-old female underwent placement of an RNS device for drug-resistant epilepsy in the setting of LGS. Five months after device placement, the patient began experiencing intermittent slurred speech, fatigue, and muscle weakness. Initially, the symptoms were attributed to increased seizure activity and/or medication side effects. However, despite changing medications and RNS settings, no improvements occurred. Her antiacetylcholine receptor antibodies measured 62.50 nmol/L, consistent with a diagnosis of MG. The patient was then prescribed pyridostigmine and underwent a thymectomy, which alleviated most of her symptoms. The authors share the cautionary tale of a case of MG in a pediatric patient who was treated with RNS for intractable epilepsy associated with LGS. Although slurred speech, fatigue, muscle weakness, and other symptoms might stem from increased seizure activity and/or medication side effects, they could also be due to MG development.

36 Impact of Neuropsychological Performance and Anxiety on Meditation in Drug Resistant Epilepsy (DRE) Patients Implanted with a Responsive Neurostimulation (RNS) Device

Objective:Responsive neurostimulation (RNS) is a surgical intervention to reduce the frequency of seizures as an adjunctive therapy for patients with drug-resistant epilepsy (DRE). Presurgical neuropsychological evaluations capture symptoms of anxiety and depression, which occur in higher rates within the epilepsy population than in the general population; however, the effects of mood are commonly overlooked or underappreciated in the conceptualization of cognitive functioning and overall quality of life. Previous studies have shown the effects of attentional control and executive functioning on engagement in meditative states. The present study examines pre and post-meditation self-reported anxiety symptoms and the electrophysiological changes captured intracranially during meditation sessions in patients implanted with an RNS device. This study seeks to utilize presurgical neuropsychological evaluations to explore relationships between cognitive profiles and meditative state changes, and reductions in anxiety.Participants and Methods:This study presents a series of 10 patients who underwent RNS device implantation for the treatment of DRE at Mount Sinai Hospital. All patients had at least one contact in the basolateral amygdala. Prior to surgical implantation of the RNS device, all patients completed a comprehensive neuropsychological evaluation based on the NIH Common Data Elements Battery for Epilepsy Patients. Patients in this study completed a 17-and 22-minute meditation protocol based on loving-kindness and Focal Awareness (FA) meditation. Control points and mind-wandering phases were utilized to distinguish the meditative portion of the study during intracranial recordings. All patients completed a pre- and post-meditation questionnaire adapted from the PROMIS Anxiety Short Form as well as self-ratings on meditation depth and satisfaction.Results:Presurgical neuropsychological evaluation of patients showed elevated levels of anxiety on the BAI (M = 18.14, SD = 12.03) and depression on the BDI-II (M = 15.57, SD = 6.92). Neuropsychological findings localized to frontal or frontotemporal deficits in 80% of the patients were captured in this study. Regarding lateralization, 50% of patients presented with bilateral weakness on neuropsychological evaluation, with the rest showing unilateral profiles. A negative correlation was observed between patient responses on pre-meditation anxiety measures and self-reported depth of engagement in meditation, r = -0.65, p = .043. When all meditation sessions were evaluated, patients displayed a reduction in anxiety levels pre- and post- meditation, t = 2.3, p = .03.Conclusions:Present findings suggest a reduction in anxiety symptoms following completion of a meditation paradigm. Additionally, a relationship between anxiety and depth of engagement in meditation was identified. During each meditation session, electrocorticography data was collected and analyzed. Given the high comorbidities of anxiety and depression as well as cognitive symptoms common for individuals with epilepsy, a systems-based approach may enhance conceptualization of neuropsychological and neuropsychiatric evaluations, which may have a significant clinical impact. Evaluation of neuropsychological profiles, meditation effects, and anxiety in this population may support cross-discipline understanding of cognitive and psychiatric profiles to better inform treatment recommendations.

Long-term outcomes after responsive neurostimulation for treatment of refractory epilepsy: a single-center experience of 100 cases.

Despite antiepileptic drugs, more than 30% of people with epilepsy continue to have seizures. Patients with such drug-resistant epilepsy (DRE) may undergo invasive treatment such as resection, laser ablation of the epileptogenic focus, or vagus nerve stimulation, but many are not candidates for epilepsy surgery or fail to respond to such interventions. Responsive neurostimulation (RNS) provides a neuromodulatory option. In this study, the authors present a single-center experience with the use of RNS over the last 5 years to provide long-term control of seizures in patients with DRE with at least 1 year of follow-up. The authors performed a retrospective analysis of a prospectively collected single-center database of consecutive DRE patients who underwent RNS system implantation from September 2015 to December 2020. Patients were followed-up postoperatively to evaluate seizure freedom and complications. One hundred patients underwent RNS placement. Seven patients developed infections: 2 responded to intravenous antibiotic therapy, 3 required partial removal and salvaging of the system, and 2 required complete removal of the RNS device. No postoperative tract hemorrhages, strokes, device migrations, or malfunctions were documented in this cohort. The average follow-up period was 26.3 months (range 1-5.2 years). In terms of seizure reduction, 8 patients had 0%-24% improvement, 14 had 25%-49% improvement, 29 experienced 50%-74% improvement, 30 had 75%-99% improvement, and 19 achieved seizure freedom. RNS showed significantly better outcomes over time: patients with more than 3 years of RNS therapy had 1.8 higher odds of achieving 75% or more seizure reduction (95% CI 1.07-3.09, p = 0.02). Also, patients who had undergone resective or ablative surgery prior to RNS implantation had 8.25 higher odds of experiencing 50% or more seizure reduction (95% CI 1.05-65.1, p = 0.04). Responsive neurostimulator implantation achieved 50% or more seizure reduction in approximately 80% of patients. Even in patients who did not achieve seizure freedom, significant improvement in seizure duration, severity, or postictal state was reported in more than 68% of cases. Infection (7%) was the most common complication. Patients with prior resective or ablative procedures and those who had been treated with RNS for more than 3 years achieved better outcomes.

Multiple approaches to Convert RNS to Decimal Numbers

Improving the performance and speed of encryption algorithms is an important issue in cryptography. One of these improvements is the use of the RNS system. In the research, the RNS system and how to retrieve numbers from the RNS system to WNS weight number system or (decimal number) where discussed in several ways, and after performing multiplication operations, giving illustrative examples and making comparisons between methods.

Expert and deep learning model identification of iEEG seizures and seizure onset times.

Hundreds of 90-s iEEG records are typically captured from each NeuroPace RNS System patient between clinic visits. While these records provide invaluable information about the patient's electrographic seizure and interictal activity patterns, manually classifying them into electrographic seizure/non-seizure activity, and manually identifying the seizure onset channels and times is an extremely time-consuming process. A convolutional neural network based Electrographic Seizure Classifier (ESC) model was developed in an earlier study. In this study, the classification model is tested against iEEG annotations provided by three expert reviewers board certified in epilepsy. The three experts individually annotated 3,874 iEEG channels from 36, 29, and 35 patients with leads in the mesiotemporal (MTL), neocortical (NEO), and MTL + NEO regions, respectively. The ESC model's seizure/non-seizure classification scores agreed with the three reviewers at 88.7%, 89.6%, and 84.3% which was similar to how reviewers agreed with each other (92.9%-86.4%). On iEEG channels with all 3 experts in agreement (83.2%), the ESC model had an agreement score of 93.2%. Additionally, the ESC model's certainty scores reflected combined reviewer certainty scores. When 0, 1, 2 and 3 (out of 3) reviewers annotated iEEG channels as electrographic seizures, the ESC model's seizure certainty scores were in the range: [0.12-0.19], [0.32-0.42], [0.61-0.70], and [0.92-0.95] respectively. The ESC model was used as a starting-point model for training a second Seizure Onset Detection (SOD) model. For this task, seizure onset times were manually annotated on a relatively small number of iEEG channels (4,859 from 50 patients). Experiments showed that fine-tuning the ESC models with augmented data (30,768 iEEG channels) resulted in a better validation performance (on 20% of the manually annotated data) compared to training with only the original data (3.1s vs 4.4s median absolute error). Similarly, using the ESC model weights as the starting point for fine-tuning instead of other model weight initialization methods provided significant advantage in SOD model validation performance (3.1s vs 4.7s and 3.5s median absolute error). Finally, on iEEG channels where three expert annotations of seizure onset times were within 1.5 s, the SOD model's seizure onset time prediction was within 1.7 s of expert annotation.

Infraclavicular de novo placement of a responsive neurostimulator for a patient with eloquent glioma-associated epilepsy: illustrative case.

The authors present a 50-year-old female with high-grade glioma involving the motor cortex as the cause of her drug-resistant epilepsy (DRE). Responsive neurostimulation (RNS) was chosen for epilepsy treatment. Due to concerns regarding the generator impeding the regular imaging surveillance required for treatment and monitoring of her glioma, surgeons placed the internal pulse generator (IPG) within an infraclavicular chest pocket. Implantation of the RNS device and IPG within the infraclavicular pocket was uneventful. However, both subdural and depth electrodes were used and connected to the IPG, and subdural electrodes are considerably shorter than depth electrodes (37 vs 44 cm). The shorter strip leads presumably generated significant tension, leading to fracture of the leads. Therefore, surgery was repeated using only depth electrodes for more length and less tension. The device has good-quality electrocorticography signals that continue to be used for device programming. The seizure burden was reduced, and quality of life improved for the patient. The RNS system with infraclavicular IPG placement reduced the seizure burden and improved the quality of life of a patient with glioma-associated epilepsy. Surgeons may consider the infraclavicular location as an alternative site for implantation for RNS candidates who require recurrent intracranial magnetic resonance imaging.

Deep net detection and onset prediction of electrographic seizure patterns in responsive neurostimulation.

Managing the progress of drug-resistant epilepsy patients implanted with the Responsive Neurostimulation (RNS) System requires the manual evaluation of hundreds of hours of intracranial recordings. The generation of these large amounts of data and the scarcity of experts' time for evaluation necessitate the development of automatic tools to detect intracranial electroencephalographic (iEEG) seizure patterns (iESPs) with expert-level accuracy. We developed an intelligent system for identifying the presence and onset time of iESPs in iEEG recordings from the RNS device. An iEEG dataset from 24 patients (36 293 recordings) recorded by the RNS System was used for training and evaluating a neural network model (iESPnet). The model was trained to identify the probability of seizure onset at each sample point of the iEEG. The reliability of the net was assessed and compared to baseline methods, including detections made by the device. iESPnet performance was measured using balanced accuracy and the F1 score for iESP detection. The prediction time was assessed via both the error and the mean absolute error. The model was evaluated following a hold-one-out strategy, and then validated in a separate cohort of 26 patients from a different medical center. iESPnet detected the presence of an iESP with a mean accuracy value of 90% and an onset time prediction error of approximately 3.4 s. There was no relationship between electrode location and prediction outcome. Model outputs were well calibrated and unbiased by the RNS detections. Validation on a separate cohort further supported iESPnet applicability in real clinical scenarios. Importantly, RNS device detections were found to be less accurate and delayed in nonresponders; therefore, tools to improve the accuracy of seizure detection are critical for increasing therapeutic efficacy. iESPnet is a reliable and accurate tool with the potential to alleviate the time-consuming manual inspection of iESPs and facilitate the evaluation of therapeutic response in RNS-implanted patients.

Vasospasm secondary to responsive neurostimulator placement: a previously unreported complication. Illustrative case.

The Responsive Neurostimulation (RNS) system is an implantable device for patients with drug-resistant epilepsy who are not candidates for resection of a seizure focus. As a relatively new therapeutic, the full spectrum of adverse effects has yet to be determined. A literature review revealed no previous reports of cerebral vasospasm following RNS implantation. A 35-year-old man developed severe angiographic and clinical vasospasm following bilateral mesial temporal lobe RNS implantation. He initially presented with concerns for status epilepticus 8 days after implantation. On hospital day 3, a decline in his clinical examination prompted imaging studies that revealed a left middle cerebral artery (MCA) stroke with angiographic evidence of severe vasospasm of the left internal carotid artery (ICA), MCA, anterior cerebral artery (ACA), and right ICA and ACA. Despite improvements in angiographic vasospasm after appropriate treatment, a thrombus developed in the posterior M2 branch, requiring mechanical thrombectomy. Ultimately, the patient was stabilized and discharged to a rehabilitation facility with residual cognitive and motor deficits. Cerebral vasospasm as a cause of ischemic stroke after uneventful RNS implantation is exceedingly rare, yet demands particular attention given the potential for severe consequences and the growing number of patients receiving RNS devices.

Linear feedback control of spreading dynamics in stochastic nonlinear network models: epileptic seizures.

The development of models and approaches for controlling the spreading dynamics of epileptic seizures is an essential step towards new therapies for people with pharmacologically resistant epilepsy. Beyond resective neurosurgery, in which epileptogenic zones (EZs) are the target of surgery, closed-loop control based on intracranial electrical stimulation, applied at the very early stage of seizure evolution, has been the main alternative, e.g. the RNS system from NeuroPace (Mountain View, CA). In this approach the electrical stimulation is delivered to target brain areas after detection of seizure initiation in the EZ. Here, we examined, on model simulations, some of the closed-loop control aspects of the problem. Seizure dynamics and spread are typically modeled with highly nonlinear dynamics on complex brain networks. Despite the nonlinearity and complexity, currently available optimal feedback control approaches are mostly based on linear approximations. Alternative machine learning control approaches might require amounts of data beyond what is commonly available in the intended application. We thus examined how standard linear feedback control approaches perform when applied to nonlinear models of neural dynamics of seizure generation and spread. In particular, we considered patient-specific epileptor network models for seizure onset and spread. The models incorporate network connectivity derived from (diffusion MRI) white-matter tractography, have been shown to capture the qualitative dynamics of epileptic seizures and can be fit to patient data. For control, we considered simple linear quadratic Gaussian (LQG) regulators. The LQG control was based on a discrete-time state-space model derived from the linearization of the patient-specific epileptor network model around a stable fixed point in the regime of preictal dynamics. We show in simulations that LQG regulators acting on the EZ node during the initial seizure period tend to be unstable. The LQG solution for the control law in this case leads to global feedback to the EZ-node actuator. However, if the LQG solution is constrained to depend on only local feedback originating from the EZ node itself, the controller is stable. In this case, we demonstrate that localized LQG can easily terminate the seizure at the early stage and prevent spread. In the context of optimal feedback control based on linear approximations, our results point to the need for investigating in more detail feedback localization and additional relevant control targets beyond epileptogenic zones.