Case report: Nocturnal low-frequency stimulation of the centromedian thalamic nucleus improves sleep quality and seizure control.

Sleep disturbances and drug-resistant seizures significantly impact people with idiopathic generalized epilepsy (IGE). Thalamic deep brain stimulation (DBS) offers potential treatment, but its effect on sleep and seizure control needs clarification. In this study, we combined wearable sleep monitoring with electroencephalogram (EEG) confirmation to investigate the impact of nocturnal centromedian nucleus (CM) DBS parameters in a patient with drug-resistant IGE. We found that high-frequency (125 Hz) CM stimulation during sleep severely disrupted sleep macro architecture and exacerbated seizures. Conversely, switching to low-frequency (10 Hz) stimulation enhanced both sleep quality and seizure control. This study underscores the critical need to personalize DBS settings, tailoring them to individual patients' sleep patterns to maximize therapeutic benefits. While larger-scale trials are needed, our findings pave the way for patient-centric approaches to thalamic neuromodulation, offering a transformative path to improve treatment outcomes and quality of life for those with refractory epilepsy.

Stereoelectroencephalography of the Deep Brain: Basal Ganglia and Thalami.

SUMMARY: Stereoelectroencephalography (SEEG) has emerged as a transformative tool in epilepsy surgery, shedding light on the complex network dynamics involved in focal epilepsy. This review explores the role of SEEG in elucidating the role of deep brain structures, namely the basal ganglia and thalamus, in epilepsy. SEEG advances understanding of their contribution to seizure generation, propagation, and control by permitting precise and minimally invasive sampling of these brain regions. The basal ganglia, comprising the subthalamic nucleus, globus pallidus, substantia nigra, and striatum, have gained recognition for their involvement in both focal and generalized epilepsy. Electrophysiological recordings reveal hyperexcitability and increased synchrony within these structures, reinforcing their role as critical nodes within the epileptic network. Furthermore, low-frequency and high-frequency stimulation of the basal ganglia have demonstrated potential in modulating epileptogenic networks. Concurrently, the thalamus, a key relay center, has garnered prominence in epilepsy research. Disrupted thalamocortical connectivity in focal epilepsy underscores its significance in seizure maintenance. The thalamic subnuclei, including the anterior nucleus, centromedian, and medial pulvinar, present promising neuromodulatory targets, suggesting pathways for personalized epilepsy therapies. The prospect of multithalamic SEEG and thalamic SEEG stimulation trials has the potential to revolutionize epilepsy management, offering tailored solutions for challenging cases. SEEG's ability to unveil the dynamics of deep brain structures in epilepsy promises enhanced and personalized epilepsy care in our new era of precision medicine. Until deep brain SEEG is accepted as a standard of care, a rigorous informed consent process remains paramount for patients for whom such an exploration is proposed.

Reliable detection of generalized convulsive seizures using an off-the-shelf digital watch: A multisite phase 2 study.

OBJECTIVE: The aim of this study was to develop a machine learning algorithm using an off-the-shelf digital watch, the Samsung watch (SM-R800), and evaluate its effectiveness for the detection of generalized convulsive seizures (GCS) in persons with epilepsy. METHODS: This multisite epilepsy monitoring unit (EMU) phase 2 study included 36 adult patients. Each patient wore a Samsung watch that contained accelerometer, gyroscope, and photoplethysmographic sensors. Sixty-eight time and frequency domain features were extracted from the sensor data and were used to train a random forest algorithm. A testing framework was developed that would better reflect the EMU setting, consisting of (1) leave-one-patient-out cross-validation (LOPO CV) on GCS patients, (2) false alarm rate (FAR) testing on nonseizure patients, and (3) "fixed-and-frozen" prospective testing on a prospective patient cohort. Balanced accuracy, precision, sensitivity, and FAR were used to quantify the performance of the algorithm. Seizure onsets and offsets were determined by using video-electroencephalographic (EEG) monitoring. Feature importance was calculated as the mean decrease in Gini impurity during the LOPO CV testing. RESULTS: LOPO CV results showed balanced accuracy of .93 (95% confidence interval [CI] = .8-.98), precision of .68 (95% CI = .46-.85), sensitivity of .87 (95% CI = .62-.96), and FAR of .21/24 h (interquartile range [IQR] = 0-.90). Testing the algorithm on patients without seizure resulted in an FAR of .28/24 h (IQR = 0-.61). During the "fixed-and-frozen" prospective testing, two patients had three GCS, which were detected by the algorithm, while generating an FAR of .25/24 h (IQR = 0-.89). Feature importance showed that heart rate-based features outperformed accelerometer/gyroscope-based features. SIGNIFICANCE: Commercially available wearable digital watches that reliably detect GCS, with minimum false alarm rates, may overcome usage adoption and other limitations of custom-built devices. Contingent on the outcomes of a prospective phase 3 study, such devices have the potential to provide non-EEG-based seizure surveillance and forecasting in the clinical setting.

Ictal Central Apnea Is Predictive of Mesial Temporal Seizure Onset: An Intracranial Investigation.

OBJECTIVE: Ictal central apnea (ICA) is a semiological sign of focal epilepsy, associated with temporal and frontal lobe seizures. In this study, using qualitative and quantitative approaches, we aimed to assess the localizational value of ICA. We also aimed to compare ICA clinical utility in relation to other seizure semiological features of focal epilepsy. METHODS: We analyzed seizures in patients with medically refractory focal epilepsy undergoing intracranial stereotactic electroencephalographic (SEEG) evaluations with simultaneous multimodal cardiorespiratory monitoring. A total of 179 seizures in 72 patients with reliable artifact-free respiratory signal were analyzed. RESULTS: ICA was seen in 55 of 179 (30.7%) seizures. Presence of ICA predicted a mesial temporal seizure onset compared to those without ICA (odds ratio = 3.8, 95% confidence interval = 1.3-11.6, p = 0.01). ICA specificity was 0.82. ICA onset was correlated with increased high-frequency broadband gamma (60-150Hz) activity in specific mesial or basal temporal regions, including amygdala, hippocampus, and fusiform and lingual gyri. Based on our results, ICA has an almost 4-fold greater association with mesial temporal seizure onset zones compared to those without ICA and is highly specific for mesial temporal seizure onset zones. As evidence of symptomatogenic areas, onset-synchronous increase in high gamma activity in mesial or basal temporal structures was seen in early onset ICA, likely representing anatomical substrates for ICA generation. INTERPRETATION: ICA recognition may help anatomoelectroclinical localization of clinical seizure onset to specific mesial and basal temporal brain regions, and the inclusion of these regions in SEEG evaluations may help accurately pinpoint seizure onset zones for resection. ANN NEUROL 2024;95:998-1008.

The value of additional electrodes when stereo-electroencephalography is inconclusive.

OBJECTIVE: Stereo-electroencephalography (SEEG) is the preferred method for intracranial localization of the seizure-onset zone (SOZ) in drug-resistant focal epilepsy. Occasionally SEEG evaluation fails to confirm the pre-implantation hypothesis. This leads to a decision tree regarding whether the addition of SEEG electrodes (two-step SEEG - 2sSEEG) or placement of subdural electrodes (SDEs) after SEEG (SEEG2SDE) would help. There is a dearth of literature encompassing this scenario, and here we aimed to characterize outcomes following unplanned two-step intracranial EEG (iEEG). METHODS: All 225 adult SEEG cases over 8 years at our institution were reviewed to extract patient data and outcomes following a two-step evaluation. Three raters independently quantified benefits of additional intracranial electrodes. The relationship between two-step iEEG benefit and clinical outcome was then analyzed. RESULTS: Fourteen patients underwent 2sSEEG and nine underwent SEEG2SDE. In the former cohort, the second SEEG procedure was performed for these reasons-precise localization of the SOZ (36%); defining margins of eloquent cortex (21%); and broadening coverage in the setting of non-localizable seizure onsets (43% of cases). Sixty-four percent of 2sSEEG cases were consistently deemed beneficial (Light's κ = 0.80). 2sSEEG performed for the first two indications was much more beneficial than when onsets were not localizable (100% vs 17%, p = .02). In the SEEG2SDE cohort, SDEs identified the SOZ and enabled delineation of margins relative to eloquent cortex in all cases. SIGNIFICANCE: The two-step iEEG is useful if the initial evaluation is broadly concordant with the original electroclinical hypothesis, where it can clarify onset zones or delineate safe surgical margins; however, it provides minimal benefit when the implantation hypothesis is erroneous, and we recommend that 2sSEEG not be generally utilized in such cases. SDE implantation after SEEG minimizes the need for SDEs and is helpful in delineating surgical boundaries relative to ictal-onset zones and eloquent cortex.

Advancing the frontiers of thalamic neuromodulation: A review of emerging targets and paradigms.

The thalamus is a key structure that plays a crucial role in initiating and propagating seizures. Recent advancements in neuroimaging and neurophysiology have identified the thalamus as a promising target for neuromodulation in drug-resistant epilepsies. This review article presents the latest innovations in thalamic targets and neuromodulation paradigms being explored in pilot or pivotal clinical trials. Multifocal temporal plus or posterior quadrant epilepsies are evaluated with pulvinar thalamus neuromodulation, while centromedian thalamus is explored in generalized epilepsies and Lennox Gastaut syndrome. Multinodal thalamocortical neuromodulation with novel stimulation paradigms such as long bursting or low-frequency stimulation is being investigated to quench the epileptic network excitability. Beyond seizure control, thalamic neuromodulation to restore consciousness is being studied. This review highlights the promising potential of thalamic neuromodulation in epilepsy treatment, offering hope to patients who have not responded to conventional medical therapies. However, it also emphasizes the need for larger randomized controlled trials and personalized stimulation paradigms to improve patient outcomes further.

Pulvinar neuromodulation for seizure monitoring and network modulation in temporal plus epilepsy.

Deep brain stimulation (DBS) is a promising treatment for drug-refractory epilepsies (DRE) when targeting the anterior nuclei of thalamus (ANT). However, targeting other thalamic nuclei, such as the pulvinar, shows therapeutic promise. Our pioneering case study presents the application of ambulatory seizure monitoring using spectral fingerprinting (12.15-17.15 Hz) recorded through Medtronic Percept DBS implanted bilaterally in the medial pulvinar thalami. This technology offers unprecedented opportunities for real-time monitoring of seizure burden and thalamocortical network modulation for effective seizure reduction in patients with bilateral mesial temporal and temporal plus epilepsies that are not suitable for resection.

Stimulation-induced respiratory enhancement in corticothalamic regions.

OBJECTIVE: We aimed to identify corticothalamic areas and electrical stimulation paradigms that optimally enhance breathing. METHODS: Twenty-nine patients with medically intractable epilepsy were prospectively recruited in an epilepsy monitoring unit while undergoing stereoelectroencephalographic evaluation. Direct electrical stimulation in cortical and thalamic regions was carried out using low (<1 Hz) and high (≥10 Hz) frequencies, and low (<5 mA) and high (≥5 mA) current intensities, with pulse width of .1 ms. Electrocardiography, arterial oxygen saturation (SpO2 ), end-tidal carbon dioxide (ETCO2 ), oronasal airflow, and abdominal and thoracic plethysmography were monitored continuously during stimulations. Airflow signal was used to estimate breathing rate, tidal volume, and minute ventilation (MV) changes during stimulation, compared to baseline. RESULTS: Electrical stimulation increased MV in the amygdala, anterior cingulate, anterior insula, temporal pole, and thalamus, with an average increase in MV of 20.8% ± 28.9% (range = 0.2%-165.6%) in 19 patients. MV changes were associated with SpO2 and ETCO2 changes (p < .001). Effects on respiration were parameter and site dependent. Within amygdala, low-frequency stimulation of the medial region produced 78.49% greater MV change (p < .001) compared to high-frequency stimulation. Longer stimulation produced greater MV changes (an increase of 4.47% in MV for every additional 10 s, p = .04). SIGNIFICANCE: Stimulation of amygdala, anterior cingulate gyrus, anterior insula, temporal pole, and thalamus, using certain stimulation paradigms, enhances respiration. Among tested paradigms, low-frequency, low-intensity, long-duration stimulation of the medial amygdala is the most effective breathing enhancement stimulation strategy. Such approaches may pave the way for the future development of neuromodulatory techniques that aid rescue from seizure-related apnea, potentially as a targeted sudden unexpected death in epilepsy prevention method.

Safety and efficacy of bihemispheric sampling via transmidline stereoelectroencephalography.

OBJECTIVE: Stereoelectroencephalography (SEEG) is designed to target distributed cortical networks responsible for electroclinical seizure syndrome and to enable localization of the site of seizure onset in patients with intractable epilepsy. When the preimplantation hypothesis invokes the bilateral mesial frontal lobes, sampling of several deep-seated cortical sites in both hemispheres is required. In this study, the authors have demonstrated the feasibility of sampling bihemispheric areas with intentional implantation of an SEEG electrode crossing the midline (SECM) for sampling the cortex on both sides of the interhemispheric fissure. METHODS: An analysis of 231 consecutive SEEG procedures over 8 years was used to identify instances of bihemispheric sampling by using the transmidline SEEG technique. RESULTS: The authors identified 53 SEEG cases, with a total of 126 electrodes that crossed the interhemispheric fissure; all were in the frontal lobes. Eighty-three electrodes targeted the cingulate gyrus (18 rostral, 43 anterior, and 22 middle), 31 targeted the posterior orbitofrontal region, 8 sampled the medial prefrontal cortex, and 4 targeted nodular heterotopia around the frontal horns. The ictal onset zone was localized to the frontal lobe in 16 cases. SECM isolated interictal and ictal activity in the contralateral hemisphere in 6 cases and independent bihemispheric seizure activity in 2 cases. No hemorrhagic or infectious complications were noted in any of these cases. CONCLUSIONS: Based on this extensive experience of bihemispheric sampling, the authors concluded that this technique is safe and effective. In this series, SECM showed contralateral interictal and/or ictal epileptiform activity in 8 (15%) cases, and 9 (16%) cases (with unilateral implantation) had sufficient data to discard contralateral involvement, contributing to support of the epileptogenic network. SECM may reduce the number of electrodes used to sample bilateral mesial frontal or orbitofrontal cortices, and such an approach may lower the risk of hemorrhage and costs.

Pro-Ictal State in Human Temporal Lobe Epilepsy.

BACKGROUND: Studies of continuous electroencephalography (EEG) suggest that seizures in individuals with focal-onset epilepsies preferentially occur during periods of heightened risk, typified by pathologic brain activities, termed pro-ictal states; however, the presence of (pathologic) pro-ictal states among a plethora of otherwise physiologic (e.g., sleep­wake cycle) states has not been established. METHODS: We studied a prospective, consecutive series of 15 patients with temporal lobe epilepsy who underwent limbic thalamic recordings in addition to routine (cortical) intracranial EEG for seizure localization. For each participant, pro-ictal (45 minutes before seizure onset) and interictal (4 hours removed from all seizures) EEG segments were divided into 10-minute, nonoverlapping windows, which were randomly distributed into training and validation cohorts in a 1:1 ratio. A deep neural classifier was applied to distinguish pro-ictal from interictal brain activities in a patient-specific fashion. RESULTS: We analyzed 1800 patient-hours of continuous thalamocortical EEG. Distinct pro-ictal states were detected in each participant. The median area under the receiver-operating characteristic curve of the classifier was 0.92 (interquartile range, 0.90­0.96). Pro-ictal states were distinguished at least 45 minutes before seizure onset in 13 of 15 participants; in 2 of 15 participants, they were distinguished up to 35 minutes prior. CONCLUSIONS: On the basis of thalamocortical EEG, pro-ictal states ­ pathologic brain activities during periods of heightened seizure risk ­ could be identified in patients with temporal lobe epilepsy and were detected, in our small sample, more than one half hour before seizure onset.

Interictal localization of the epileptogenic zone: Utilizing the observed resonance behavior in the spectral band of surrounding inhibition.

Introduction: The gold standard for identification of the epileptogenic zone (EZ) continues to be the visual inspection of electrographic changes around seizures' onset by experienced electroencephalography (EEG) readers. Development of an epileptogenic focus localization tool that can delineate the EZ from analysis of interictal (seizure-free) periods is still an open question of great significance for improved diagnosis (e.g., presurgical evaluation) and treatment of epilepsy (e.g., surgical outcome). Methods: We developed an EZ interictal localization algorithm (EZILA) based on novel analysis of intracranial EEG (iEEG) using a univariate periodogram-type power measure, a straight-forward ranking approach, a robust dimensional reduction method and a clustering technique. Ten patients with temporal and extra temporal lobe epilepsies, and matching the inclusion criteria of having iEEG recordings at the epilepsy monitoring unit (EMU) and being Engel Class I ≥12 months post-surgery, were recruited in this study. Results: In a nested k-fold cross validation statistical framework, EZILA assigned the highest score to iEEG channels within the EZ in all patients (10/10) during the first hour of the iEEG recordings and up to their first typical clinical seizure in the EMU (i.e., early interictal period). To further validate EZILA's performance, data from two new (Engel Class I) patients were analyzed in a double-blinded fashion; the EZILA successfully localized iEEG channels within the EZ from interictal iEEG in both patients. Discussion: Out of the sampled brain regions, iEEG channels in the EZ were most frequently and maximally active in seizure-free (interictal) periods across patients in specific narrow gamma frequency band (∼60-80 Hz), which we have termed focal frequency band (FFB). These findings are consistent with the hypothesis that the EZ may interictally be regulated (controlled) by surrounding inhibitory neurons with resonance characteristics within this narrow gamma band.

A peptide blocking the ADORA1-neurabin interaction is anticonvulsant and inhibits epilepsy in an Alzheimer's model.

Epileptic seizures are common sequelae of stroke, acute brain injury, and chronic neurodegenerative diseases, including Alzheimer's disease (AD), and cannot be effectively controlled in approximately 40% of patients, necessitating the development of novel therapeutic agents. Activation of the A1 receptor (A1R) by endogenous adenosine is an intrinsic mechanism to self-terminate seizures and protect neurons from excitotoxicity. However, targeting A1R for neurological disorders has been hindered by side effects associated with its broad expression outside the nervous system. Here we aim to target the neural-specific A1R/neurabin/regulator of G protein signaling 4 (A1R/neurabin/RGS4) complex that dictates A1R signaling strength and response outcome in the brain. We developed a peptide that blocks the A1R-neurabin interaction to enhance A1R activity. Intracerebroventricular or i.n. administration of this peptide shows marked protection against kainate-induced seizures and neuronal death. Furthermore, in an AD mouse model with spontaneous seizures, nasal delivery of this blocking peptide reduces epileptic spike frequency. Significantly, the anticonvulsant and neuroprotective effects of this peptide are achieved through enhanced A1R function in response to endogenous adenosine in the brain, thus, avoiding side effects associated with A1R activation in peripheral tissues and organs. Our study informs potentially new anti-seizure therapy applicable to epilepsy and other neurological illness with comorbid seizures.

Optimally targeting the centromedian nucleus of the thalamus for generalized epilepsy: A meta-analysis.

BACKGROUND: Deep brain stimulation (DBS) of the centromedian nucleus (CM) is an effective therapeutic option for select patients with generalized epilepsy. However, several studies suggest that success varies with active contact location within the CM and the exact target remains undefined. OBJECTIVE: To quantify the association between active contact location and outcomes across all published series of CM DBS. METHODS: A literature search using PRISMA criteria was performed to identify all studies that reported active contact locations PLUS outcomes following DBS of the CM for epilepsy. Patient, disease, treatment, and outcome data were extracted for statistical analysis. Active contact locations were analyzed on a common reference frame and weighted by percent seizure reduction at last follow-up. RESULTS: From 184 studies that were screened for review, 3 studies comprising 47 patients met criteria for inclusion and were analyzed. At time of surgery, mean duration of epilepsy was 18 years. Pooled rates of atonic, atypical absence, generalized tonic-clonic, myoclonic, and tonic epilepsies were 38%, 74%, 68%, 14%, and 60%, respectively. Indirect targeting was used in all these studies. After a mean follow-up duration of 2.3 years, 87% of patients were deemed to be responders with mean seizure reduction of 73% (95% CI: [64%-81%]). Optimal location of the active contact was found to be at the dorsal border of the CM. CONCLUSIONS: Success following DBS of the CM for epilepsy varies by active contact location, even within the CM. Our findings suggest that stimulation within the dorsal region of the CM improves outcomes. Additional studies are needed to further refine these findings.

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 was 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) electrocorticography-based seizure events were extracted for analysis, representing a span of 38 ± 27 months of recording. MASE across all subjects was .74 ± .09, .78 ± .09, and .83 ± .07 at .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.

Time-Series Generative Adversarial Network Approach of Deep Learning Improves Seizure Detection From the Human Thalamic SEEG.

Seizure detection algorithms are often optimized to detect seizures from the epileptogenic cortex. However, in non-localizable epilepsies, the thalamus is frequently targeted for neuromodulation. Developing a reliable seizure detection algorithm from thalamic SEEG may facilitate the translation of closed-loop neuromodulation. Deep learning algorithms promise reliable seizure detectors, but the major impediment is the lack of larger samples of curated ictal thalamic SEEG needed for training classifiers. We aimed to investigate if synthetic data generated by temporal Generative Adversarial Networks (TGAN) can inflate the sample size to improve the performance of a deep learning classifier of ictal and interictal states from limited samples of thalamic SEEG. Thalamic SEEG from 13 patients (84 seizures) was obtained during stereo EEG evaluation for epilepsy surgery. Overall, TGAN generated synthetic data augmented the performance of the bidirectional Long-Short Term Memory (BiLSTM) performance in classifying thalamic ictal and baseline states. Adding synthetic data improved the accuracy of the detection model by 18.5%. Importantly, this approach can be applied to classify electrographic seizure onset patterns or develop patient-specific seizure detectors from implanted neuromodulation devices.

Limbic and paralimbic respiratory modulation: From inhibition to enhancement.

OBJECTIVE: Increased understanding of the role of cortical structures in respiratory control may help the understanding of seizure-induced respiratory dysfunction that leads to sudden unexpected death in epilepsy (SUDEP). The aim of this study was to characterize respiratory responses to electrical stimulation (ES), including inhibition and enhancement of respiration. METHODS: We prospectively recruited 19 consecutive patients with intractable epilepsy undergoing stereotactic electroencephalography (EEG) evaluation from June 2015 to June 2018. Inclusion criteria were patients ≥18 years in whom ES was indicated for clinical mapping of ictal onset or eloquent cortex as part of the presurgical evaluation. ES was carried out at 50 Hz, 0.2 msec, and 1-10 mA current intensity. Common brain regions sampled across all patients were amygdala (AMY), hippocampus (HG), anterior cingulate gyrus (CING), orbitofrontal cortex (OrbF), temporal neocortex (TNC), temporal pole (TP), and entorhinal cortex (ERC). Seven hundred fifty-five stimulations were conducted. Quantitative analysis of breathing signal, that is, changes in breathing rate (BR), depth (TV), and minute ventilation (MV), was carried out during ES using the BreathMetrics breathing waveform analysis toolbox. Electrocardiography, arterial oxygen saturation, end-tidal and transcutaneous carbon dioxide, nasal airflow, and abdominal and thoracic plethysmography were monitored continuously during stimulations. RESULTS: Electrical stimulation of TP and CING (at lower current strengths <3 mA) increased TV and MV. At >7-10 mA, CING decreased TV and MV. On the other hand, decreased TV and MV occurred with stimulation of mesial temporal structures such as AMY and HG. Breathing changes were dependent on stimulation intensity. Lateral temporal, entorhinal, and orbitofrontal cortices did not affect breathing either way. SIGNIFICANCE: These findings suggest that breathing responses other than apnea can be induced by ES. Identification of two regions-the temporal pole and anterior cingulate gyrus-for enhancement of breathing may be important in paving the way to future development of strategies for prevention of SUDEP.

Ictal high-frequency activity in limbic thalamic nuclei varies with electrographic seizure-onset patterns in temporal lobe epilepsy.

OBJECTIVE: To characterize ictal high-frequency activity (HFA, 80-500 Hz) within the limbic thalami and correlate HFA with seizure onset patterns in patients with temporal lobe epilepsy (TLE). METHODS: Patients with TLE undergoing stereoelectroencephalography (SEEG) for presurgical workup were prospectively recruited for electrode implantation in one of the anterior (AN), centromedian (CeM), or mediodorsal (MD) thalamic nuclei. HFA was computed by three complementary methods: (1.) power-spectral density (PSD), (2.) power-law based (i.e., 1/f) regression, and (3.) envelope-based (ENV) power analysis. Electrographic onset patterns in the seizure onset zone were classified in three distinct patterns, including low amplitude fast activity (LAFA). RESULTS: From 11 patients, 44 seizures were analyzed. Ictal HFA was observed in all three thalamic nuclei. HFA was greatest during ictal onset in the AN and MD and greatest during termination in the CeM (P < 0.001). LAFA-onset seizures were associated with earlier peak HFA compared to those with other onset patterns (P = 0.006). CONCLUSIONS: Dynamics of ictal HFA seem to vary by thalamic subnuclei. AN and MD may facilitate seizure propagation while CeM may play a role in termination. LAFA-onset seizures rapidly propagate to the thalamus. SIGNIFICANCE: Characterizing nucleus-specific ictal dynamics of neural activities facilitates precise therapy for epilepsy treatment with closed-loop deep brain stimulation.

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.