Anterior thalamic nucleus local field potentials during focal temporal lobe epileptic seizures.

Objective: To analyze the local field potentials (LFPs) in patients with focal drug-resistant epilepsy (DRE) from the anterior nucleus of the thalamus (ANT) during inter-ictal state and seizure state. Method: ANT stereotactic EEG (SEEG) recordings were studied in four patients with focal temporal lobe epilepsy. SEEG data was classified as inter-ictal and ictal state and sub-categorized into electrographic (ESz), focal aware seizure (FAS), focal with impaired awareness (FIA), or focal to bilateral tonic-clonic seizure (FBTC). LFP was analyzed at 4 Hz, 8 Hz, 16 Hz, 32 Hz, high gamma (100 Hz), and ripples (200 Hz) using spectrogram analysis and a statistical comparison of normalized power spectral density (PSD) averaged during seizures versus pre-ictal baseline segments. Result: The LFP recordings were analyzed for 162 seizures (127 ESz, 23 FAS, 6 FIA, and 6 FBTC). Based on time-frequency data (spectrogram), a broad band of activity, occurring between 2 and 6 Hz and centered at 4 Hz, and thin-band activity occurring specifically at 8 Hz on the frequency spectrogram were observed during the inter-ictal state. Statistically significant changes in LFP-PSD were seen for FAS, FIA, and FBTC. We observed a significant gain in LFP at the lower frequency band during FAS at 4 Hz, FIA, and FBTC at 4, 8, and 16 Hz while also observing increases at higher frequencies during FBTC at 100 and 200 Hz and a decrease during FAS seizures at 32 Hz. In contrast, no significant change in LFP power was seen for electrographic seizures. Interpretation: Our observations from a limited dataset indicate that all clinical seizure types, but not electrographic seizures, caused a change in ANT-LFP based on the magnitude of the associated power spectral density (PSD). Future work will be needed to validate the use of ANT-LFP at these frequencies as accurate measurements of seizure occurrence and severity. This work represents a first step toward understanding ANT thalamic LFP patterns during focal seizures and developing adaptive DBS strategies.

Stereo-Electroencephalography-Recorded Interictal Epileptiform Discharges: Activation Pattern and Its Relationship With Surgical Outcome.

Background Patients with drug-resistant epilepsy commonly undergo stereo-electroencephalography (SEEG) intracranial monitoring for surgical evaluation. Our current practice of defining the epileptogenic zone relies heavily on recognizing the seizure onset zone (SOZ), but the clinical significance of interictal epileptiform discharges (IEDs) is not well established. Methodology We retrospectively identified adult patients who underwent SEEG between January 2019 and May 2022. To study IED activation patterns, we classified IEDs as leading spikes (involved within the SOZ) and distant spikes (outside the SOZ). We calculated each patient's total number of brain subregions generating distant spikes. We correlated them with epilepsy type, duration, and surgical outcome (Engel I: good outcome and Engel II-IV: poor outcome). Results A total of 22 patients were identified during the study period, and 16 underwent surgical intervention (ablation or resection) with one-year post-surgery follow-up. The most common IED morphology was a single spike or sharp followed by periodic spikes or sharps. We found that 87% (n = 19/22) of leading spikes were activated during the first 24 hours of SEEG monitoring, whereas no activation pattern was observed for distant spikes. We found that a higher number of subregions generating distant spikes were associated with poor surgical outcomes (p = 0.002). However, we did not find any significant association between the number of subregions generating distant spikes with epilepsy duration (p = 0.67), temporal or extratemporal-onset epilepsy (p = 0.58), or the presence of an MRI lesion (p = 0.62). Conclusions IEDs involved within the SOZ were found to be activated during the first 24 hours of SEEG monitoring, which could aid in recognizing the pathological spikes and targeted mapping of the irritative zone. We also observed that a higher number of brain subregions generating IEDs outside the SOZ were associated with poor surgical outcomes, but this observation needs to be further studied with larger sample size prospective studies.

From theory to practical fundamentals of electroencephalographic source imaging in localizing the epileptogenic zone.

With continued advancement in computational technologies, the analysis of electroencephalography (EEG) has shifted from pure visual analysis to a noninvasive computational technique called EEG source imaging (ESI), which involves mathematical modeling of dipolar and distributed sources of a given scalp EEG pattern. ESI is a noninvasive phase I test for presurgical localization of the seizure onset zone in focal epilepsy. It is a relatively inexpensive modality, as it leverages scalp EEG and magnetic resonance imaging (MRI) data already collected typically during presurgical evaluation. With an adequate number of electrodes and combined with patient-specific MRI-based head models, ESI has proven to be a valuable and accurate clinical diagnostic tool for localizing the epileptogenic zone. Despite its advantages, however, ESI is routinely used at only a minority of epilepsy centers. This paper reviews the current evidence and practical fundamentals for using ESI of interictal and ictal epileptic activity during the presurgical evaluation of drug-resistant patients. We identify common errors in processing and interpreting ESI studies, describe the differences in approach needed for localizing interictal and ictal EEG discharges through practical examples, and describe best practices for optimizing the diagnostic information available from these studies.

Etiology and prognostic significance of ictal EEG patterns in patients with non-convulsive seizures.

We aimed to study the ictal EEG patterns in patients with non-convulsive seizures (NCS) and their relationship with underlying etiology and patient outcome. We conducted a retrospective review of EEG studies from patients undergoing continuous EEG (cEEG) monitoring for indication of altered mental status with a suspicion of NCS. Ictal EEG findings of NCS were categorized as three patterns: focal or generalized epileptiform discharges (EDs) at frequencies >2.5 Hz (Pattern 1); EDs at frequencies of ≤2.5 Hz or rhythmic activity >0.5 Hz with spatiotemporal evolution (Pattern 2); and EDs with ≤2.5 Hz with subtle clinical correlate during the ictal EEG or clinical and EEG improvement after a trial of IV anti-seizure drugs (Pattern 3). Patients with anoxic brain injury were excluded from the study. Associations between ictal EEG patterns and underlying etiology and their impact on in-hospital mortality was measured. Of 487 patients included in the study, NCS was recorded on cEEG monitoring in 57 (12%). The ictal EEG Pattern 2 was the most commonly seen ictal EEG finding in our cohort of patients with NCS (70%, n=40/57), followed by Pattern 3 (15%, n=9/57) and Pattern 1(14%, n=8/57). In patients with acute brain injury, Pattern 2 (67%, n=27/40) was a commonly seen ictal EEG finding, whereas Pattern 1 (62% n=5/8) was seen in patients with underlying acute medical illness. No statistically significant difference was found between ictal EEG patterns and underlying neurological versus medical etiologies (p=0.27) or in-hospital mortality (p=0.5). Spatiotemporal evolution of epileptiform discharges at a lower frequency was the most commonly recorded ictal EEG pattern in our cohort. Further prospective studies with a larger sample size of patients with NCS may provide valuable clinical data that could be used to evaluate the etiologic correlate of the various ictal EEG patterns and their effect on outcome.

New Frontiers for Deep Brain Stimulation: Directionality, Sensing Technologies, Remote Programming, Robotic Stereotactic Assistance, Asleep Procedures, and Connectomics.

Over the last few years, while expanding its clinical indications from movement disorders to epilepsy and psychiatry, the field of deep brain stimulation (DBS) has seen significant innovations. Hardware developments have introduced directional leads to stimulate specific brain targets and sensing electrodes to determine optimal settings via feedback from local field potentials. In addition, variable-frequency stimulation and asynchronous high-frequency pulse trains have introduced new programming paradigms to efficiently desynchronize pathological neural circuitry and regulate dysfunctional brain networks not responsive to conventional settings. Overall, these innovations have provided clinicians with more anatomically accurate programming and closed-looped feedback to identify optimal strategies for neuromodulation. Simultaneously, software developments have simplified programming algorithms, introduced platforms for DBS remote management via telemedicine, and tools for estimating the volume of tissue activated within and outside the DBS targets. Finally, the surgical accuracy has improved thanks to intraoperative magnetic resonance or computerized tomography guidance, network-based imaging for DBS planning and targeting, and robotic-assisted surgery for ultra-accurate, millimetric lead placement. These technological and imaging advances have collectively optimized DBS outcomes and allowed "asleep" DBS procedures. Still, the short- and long-term outcomes of different implantable devices, surgical techniques, and asleep vs. awake procedures remain to be clarified. This expert review summarizes and critically discusses these recent innovations and their potential impact on the DBS field.

Predictors of Nonconvulsive Seizure and Their Effect on Short-term Outcome.

INTRODUCTION: Nonconvulsive seizures (NCSs) are common in critically ill adult patients with acute neurologic conditions. However, the effect of NCSs on patient outcome remains unclear. In this study, we aimed to determine the effect of NCSs on short-term outcome and to assess the clinical and EEG factors associated with NCSs. METHODS: We retrospectively identified 219 adult patients from the EEG reporting system who underwent continuous EEG (cEEG) monitoring between January 2018 and June 2018. Patients with anoxic brain injury were excluded from the study. Clinical, laboratory, and EEG data were reviewed to determine potentially predictive factors of NCSs. The impact of NCSs on in-hospital mortality, length of stay, and disability on discharge was measured; an modified Rankin scale of three or greater was considered disabled. RESULTS: Of the 219 patients included in our study, a total of 14% (n = 31) had NCSs on continuous EEG, of which 42% (n = 13) had their first seizure discharge recorded during the first hour of continuous EEG monitoring. The presence of clinical seizures before continuous EEG (odds ratio = 1.787; 95% confidence interval = 1.197-2.667, P = 0.0045), history of epilepsy (odds ratio = 1.508; 95% confidence interval = 1.027-2.215, P = 0.035), and comatose state (29 vs. 16%; P = 0.0006) were associated with NCSs. Among EEG characteristics, the presence of interictal epileptiform discharges (P < 0.0001), lateralized rhythmic delta activity (P = 0.02), and lateralized periodic discharges (P < 0.0001) were associated with NCSs. Nonconvulsive seizures were significantly associated with longer in-hospital stay (23.68 ± 24.84 vs. 17.14 ± 20.52; P = 0.036) and disability on discharge (87% [n = 27] vs. 13% [n = 4], P = 0.02). However, there was no significant association between NCS and in-hospital mortality (9.6% [n = 3] vs. 10.6% [n = 20]; P = 0.1). CONCLUSIONS: Nonconvulsive seizures are associated with longer in-hospital stay and disability on discharge but not with in-hospital mortality in adult patients.

Epidiolex-induced skin rash.

Epidiolex® (cannabidiol, aka CBD) is a recently approved FDA prescription drug for the treatment of epilepsy associated with Lennox-Gastaut and Dravet syndromes, and is increasingly used for treatment-resistant epilepsy. Rash was rarely reported in Epidiolex® clinical trial data. We report a case of Epidiolex®-related skin rash that developed in a delayed fashion in a 23-year-old female with medically refractory epilepsy. We also review the potential mechanism of Epidiolex®-related skin rash.

Psychosocial and Physiologic Characteristics of Patients with Non-epileptic Events: A Retrospective Study.

Background The main focus of this study is to aid early identification of psychogenic non-epileptic seizure (PNES) patients by identifying physical and psychosocial characteristics to reduce the health care burden, to reduce the unnecessary use of anti-epileptic medications and their side effects, and maximizing cost-effective use of video electroencephalography (VEEG). Methods We analyzed PNES subject data from VEEG monitoring performed at the Epilepsy Center at the Marshall University School of Medicine. We reviewed more than 360 episodes in 54 subjects older than 18 years (mean age ± standard deviation (SD): 48 ± 12.97 years; 83% female). Results We found that most of our PNES patients were older than 45 years of age (66.7%), females (83.3%); obese (66.6%) or overweight (18.5%); either single (33.3%), separated (7.4%), divorced (22.2%), or widowed (14.8%); of low education, unemployed (either received government assistance (83.3%) or disability benefits (57.4%)) with associated physical illness (85.2%) and psychiatric illness (96.3%).  Conclusion Our study adds to the current knowledge of the sociodemographic and sociocultural variability of PNES. It might enable early diagnosis and management of patients with PNES.

After-Hours EEG: Relative Value of Emergent Routine Versus Prolonged EEG Recordings.

OBJECTIVE: After-hours EEG is increasingly used in hospital patients. Although the detection of seizures and interictal epileptiform discharges has been shown to be higher with prolonged EEG (pEEG) than routine-duration EEG, the relative value for particular indications can inform utilization. METHOD: The Mayo EEG Report System was queried for after-hours emergent routine EEG (ErEEG) and pEEG performed between January 2015 and June 2015. Total 296 after-hours ErEEG were identified, of which 140 converted into pEEG were included in the study for direct comparison of two modalities. Indications were categorized as: mental status changes, recent seizures rule out continued nonconvulsive seizures, spells, and prognosis after anoxic brain injury. Categorical data were analyzed using the McNemar and Fisher exact tests; a P value of 0.05 was considered significant. RESULT: Prolonged EEG was superior to ErEEG for detection of interictal epileptiform discharges (61 vs. 48/140, P = 0.004) and seizures (29 vs. 17/140, P = 0.012). Seizure detection was greater for pEEG than ErEEG for the indication of evaluating for subclinical seizures after recent observed clinical seizures (14/41 [34.1%] versus 4/41 [9.8%], P = 0.002). There was no significant difference between modalities for seizure detection in patients undergoing evaluation of spells or mental status changes without previous observed seizures. Detection of seizures on pEEG was higher for recordings greater than 24 hours (8/46, 17%, P = 0.014) and 48 hours (19/26, 73%, P < 0.001) than recordings less than 24 hours (2/68, 3%). Seizure detection was higher with pEEG in comatose patients than ErEEG (17/51, 33% vs. 12/89, 13%; P = 0.009). CONCLUSIONS: Increased value was demonstrated for pEEG over ErEEG in patients undergoing evaluation after observed recent clinical seizures and for coma. No significant difference was found between ErEEG and pEEG for seizure detection in the relatively small subgroups of patients with mental status changes other than coma and without preceding seizure or spells.

Predictive models in the diagnosis and treatment of autoimmune epilepsy.

OBJECTIVE: To validate predictive models for neural antibody positivity and immunotherapy response in epilepsy. METHODS: We conducted a retrospective study of epilepsy cases at Mayo Clinic (Rochester-MN; Scottsdale-AZ, and Jacksonville-FL) in whom autoimmune encephalopathy/epilepsy/dementia autoantibody testing profiles were requested (06/30/2014-06/30/2016). An Antibody Prevalence in Epilepsy (APE) score, based on clinical characteristics, was assigned to each patient. Among patients who received immunotherapy, a Response to Immunotherapy in Epilepsy (RITE) score was assigned. Favorable seizure outcome was defined as >50% reduction of seizure frequency at the first follow-up. RESULTS: Serum and cerebrospinal fluid (CSF) from 1,736 patients were sent to the Mayo Clinic Neuroimmunology Laboratory for neural autoantibody evaluation. Three hundred eighty-seven of these patients met the diagnostic criteria for epilepsy. Central nervous system (CNS)-specific antibodies were detected in 44 patients. Certain clinical features such as new-onset epilepsy, autonomic dysfunction, viral prodrome, faciobrachial dystonic seizures/oral dyskinesia, inflammatory CSF profile, and mesial temporal magnetic resonance imaging (MRI) abnormalities had a significant association with positive antibody results. A significantly higher proportion of antibody-positive patients had an APE score ≥4 (97.7% vs. 21.6%, p < 0.01). Sensitivity and specificity of an APE score ≥4 to predict presence of specific neural auto-antibody were 97.7% and 77.9%, respectively. In the subset of patients who received immunotherapy (77), autonomic dysfunction, faciobrachial dystonic seizures/oral dyskinesia, early initiation of immunotherapy, and presence of antibodies targeting plasma membrane proteins (cell-surface antigens) were associated with favorable seizure outcome. Sensitivity and specificity of a RITE score ≥7 to predict favorable seizure outcome were 87.5% and 83.8%, respectively. SIGNIFICANCE: APE and RITE scores can aid diagnosis, treatment, and prognostication of autoimmune epilepsy. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.