A comparison of EEG seizure patterns recorded with surface and depth electrodes in patients with temporal lobe epilepsy

Surface-electromyography characteristics of clonic seizures with no scalp-EEG correlate: A comparative analysis with tremors

INTRODUCTION

Clonic seizures are characterized by twitching movements at a frequency of 0.2-5 Hz. The clonic "twitch" is produced by a brief synchronized contraction of agonist and antagonist muscles, followed by a synchronized silent period. In this study, we aimed to compare the surface-electromyography (sEMG) characteristics of scalp-EEG negative clonic seizures with those of nonepileptic movements like tremors that can resemble clonic seizures.

METHODS

We retrospectively identified patients who were diagnosed with scalp-EEG negative clonic seizures or tremors. We only included patients (n = 6) who were monitored simultaneously with video-EEG and sEMG electrodes. sEMG was placed on agonist and antagonist muscles of the affected extremity using a standardized placement system developed at our institution. We analyzed the following characteristics of sEMG bursts: the relationship between agonist and antagonist muscles and the temporal evolution of burst duration, burst amplitude, and burst frequency.

RESULTS

The following sEMG characteristics were observed: (i) sEMG bursts and corresponding silent periods were synchronous between agonist and antagonist muscles in clonic seizures. In tremors, an alternating pattern was seen. (ii) sEMG burst amplitude increased during the first 10 s of clonic seizures. There was no significant change in tremors. (iii) sEMG burst duration increased from the beginning to end of clonic seizures. There was no significant change in tremors. (iv) sEMG burst frequency decreased from the beginning to end of clonic seizures due to increased burst and silent period duration. There was no consistent change in burst frequency in tremors. (v) sEMG burst duration of ≥250 ms was indicative of a clonic seizure with a >90% positive predictive value.

CONCLUSIONS

Our study describes characteristic sEMG features of clonic seizures without scalp-EEG correlates, which can be used as an objective biomarker in distinguishing these from nonepileptic movements such as tremors.

Role of specific interictal and ictal EEG onset patterns

The objective of this review is to present the role of specific interictal and ictal EEG onset patterns during scalp video-EEG monitoring. Specific non-epileptiform abnormalities include temporal intermittent rhythmic delta activity (TIRDA) and temporal intermittent rhythmic theta activity (TIRTA) indicating a temporal lobe seizure onset, while interictal rhythmical midline theta activity occurs more frequently in frontal epilepsy. Specific interictal epileptiform abnormalities comprise Type 1 spikes pointing towards a mesial and Type 2spikes indicating a lateral temporal irritative zone. Unilateral temporal interictal epileptiform discharges (IEDs) are predictive for a good surgical seizure outcome in temporal lobe epilepsy. Small sharp spikes (SSS) named Benign Epileptiform Transients of Sleep (BETS) in the past represent scalp EEG markers of hippocampal epileptic activity. While the localizing value of IEDs in extratemporal epilepsies is often limited, a consistently localized spike focus predicts a good surgical seizure outcome in non-lesional extratemporal patients. A specific ictal EEG pattern for mesial temporal lobe epilepsy consists of a 5-9 Hz rhythmic temporal activity which also predicts a good surgical outcome. In extratemporal epilepsies, ictal scalp EEG frequently is non-localized. Concerning the correspondence of ictal scalp-EEG and intracranial EEG (iEEG) patterns there is no simple one-to-one relationship. Scalp-EEG and iEEG patterns correspond closer to each other when there is no delay between clinical and scalp-EEG onset. Paroxysmal fast activity on scalp-EEG matches with low-voltage fast activity on iEEG. Repetitive epileptiform discharges on scalp EEG indicate an underlying focal cortical dysplasia.

Epileptic activity on foramen ovale electrodes is associated with sleep and tau pathology in Alzheimer's disease

Both sleep alterations and epileptiform activity are associated with the accumulation of amyloid-β and tau pathology and are currently investigated for potential therapeutic interventions in Alzheimer's disease. However, a bidirectional intertwining relationship between sleep and neuronal hyperexcitability might modulate the effects of Alzheimer's disease pathology on the corresponding associations. To investigate this, we performed multiple day simultaneous foramen ovale (FO) plus scalp EEG and polysomnography recordings and acquired 18F-MK6240 tau PET-MR in three patients in the prodromal stage of Alzheimer's disease and in two patients with mild and moderate dementia due to Alzheimer's disease, respectively. As an eligibility criterion for the present study, subjects either had a history of a recent seizure (n = 2) or subclinical epileptiform activity (SEA) on a previous scalp EEG taken in a research context (n = 3). The 18F-MK6240 standard uptake value ratio (SUVR) and asymmetry index (AI) were calculated in a priori-defined volumes of interest. Linear mixed-effects models were used to study associations between interictal epileptiform discharges (IEDs), polysomnography parameters and 18F-MK6240 SUVR. Epileptiform activity was bilateral but asymmetrically present on FO electrodes in all patients and ≥95% of IEDs were not visible on scalp EEG. In one patient, two focal seizures were detected on FO electrodes, both without visual scalp EEG correlate. We observed lateralized periodic discharges, brief potentially ictal rhythmic discharges and lateralized rhythmic delta activity on FO electrodes in four patients. Unlike scalp EEG, intracranial electrodes showed a lateralization of epileptiform activity. Although the amount of IEDs on intracranial electrodes was not associated to the 18F-MK6240 SUVR binding in different volumes of interest, there was a congruent asymmetry of the 18F-MK6240 binding towards the most epileptic hemisphere for the mesial (P = 0.007) and lateral temporal cortex (P = 0.006). IEDs on intracranial electrodes were most abundant during slow wave sleep (SWS) (92/h) and non-REM sleep 2 (N2, 81/h), followed by non-REM sleep 1 (N1, 33/h) and least frequent during wakefulness (17/h) and REM sleep (9/h). The extent of IEDs during sleep was not reflected in the relative time in each sleep stage spent [REM% (P = 0.415), N1% (P = 0.668), N2% (P = 0.442), SWS% (P = 0.988)], and not associated with the arousal index (P = 0.317), apnoea-hypopnoea index (P = 0.846) or oxygen desaturation index (P = 0.746). Together, our observations suggest a multi-directional interaction between sleep, epileptiform activity and tau pathology in Alzheimer's disease.

EEG in Epilepsy

OBJECTIVE

The purpose of this article is to review the fundamentals and limitations of EEG, guide the selection of EEG type to answer clinical questions, and provide instruction on the interpretation of results within the patient's clinical context.

LATEST DEVELOPMENTS

EEG is the single most useful ancillary test to support the clinical diagnosis of epilepsy, but if used incorrectly it can cause great harm. Misapplication of EEG findings can lead to misdiagnosis and long-term mental and physical health sequelae. Although all neurologists may not have sufficient training for independent EEG interpretation, most should be able to review and apply the findings from the report accurately to guide patient care. Longer-term EEGs with similar recording electrodes tend to have higher diagnostic yields. Common EEG findings are described in this article, along with diagnostic limitations of some classically described patterns. There is an updated definition for an epileptiform discharge, along with a consensus on EEG patterns in the critically ill.

ESSENTIAL POINTS

EEG continues to be the most useful ancillary test to assist in the diagnosis of epilepsy. Its application requires proper understanding of its limitations and variability of testing results.

Patterns of ictal surface EEG in occipital seizures: A simultaneous scalp and intracerebral recording study

OBJECTIVE

To describe the ictal scalp EEG patterns of occipital seizures (OS) and their spatiotemporal correlations with intracerebral occipital ictal discharges derived from simultaneous SEEG-EEG recordings.

METHODS

Patients with SEEG confirmed OS (14 OS from 8 patients) were selected from an epilepsy surgery center and were monitored 3-10 days using simultaneous scalp EEG and SEEG recordings.

RESULTS

On scalp EEG, the most common onset patterns were background activity suppression (28.6 %) and high amplitude slow wave corresponding to intracerebral DC-shift (28.6 %) and occurred with a median delay of 0 s after intra-cerebral onset. The initial discharge involved occipital electrodes in only 50 % of the seizures (7/14) with additional basal temporal (8/14) or parietal electrodes (5/14). The onset was ipsilateral to the intra-cerebral onset zone in 71.4 % of seizures and bilateral in the remaining (28.6 %). The most common propagation pattern was either unilateral (50 %) or bilateral (50 %) and a rhythmic slow activity (66.7 %). Different OS subtypes display distinct scalp EEG patterns.

CONCLUSION

Scalp EEG accurately determines intra-cerebral seizure onset time in OS and has good lateralizing value. However, initial scalp modification does not always involves occipital electrodes and the second modification is well lateralizing in only 50 % of seizures.

SIGNIFICANCE

This study describes will help clinicians to better identify OS during video EEG and better plan intra-cerebral explorations for epilepsy surgery.

Comparison of Continuous Intracortical and Scalp Electroencephalography in Comatose Patients with Acute Brain Injury

BACKGROUND

Depth electroencephalography (dEEG) is a recent invasive monitoring technique used in patients with acute brain injury. This study aimed to describe in detail the clinical manifestations of nonconvulsive seizures (NCSzs) with and without a surface EEG correlate, analyze their long-standing effects, and provide data that contribute to understanding the significance of certain scalp EEG patterns observed in critically ill patients.

METHODS

We prospectively enrolled a cohort of 33 adults with severe acute brain injury admitted to the neurological intensive care unit. All of them underwent multimodal invasive monitoring, including dEEG. All patients were scanned on a 3T magnetic resonance imaging scanner at 6 months after hospital discharge, and mesial temporal atrophy (MTA) was calculated using a visual scale.

RESULTS

In 21 (65.6%) of 32 study participants, highly epileptiform intracortical patterns were observed. A total of 11 (34.3%) patients had electrographic or electroclinical seizures in the dEEG, of whom 8 had both spontaneous and stimulus-induced (SI) seizures, and 3 patients had only spontaneous intracortical seizures. An unequivocal ictal scalp correlate was observed in only 3 (27.2%) of the 11 study participants. SI-NCSzs occurred during nursing care, medical procedures, and family visits. Subtle clinical manifestations, such as restlessness, purposeless stereotyped movements of the upper limbs, ventilation disturbances, jerks, head movements, hyperextension posturing, chewing, and oroalimentary automatisms, occurred during intracortical electroclinical seizures. MTA was detected in 18 (81.8%) of the 22 patients. There were no statistically significant differences between patients with MTA with and without seizures or status epilepticus.

CONCLUSIONS

Most NCSzs in critically ill comatose patients remain undetectable on scalp EEG. SI-NCSzs frequently occur during nursing care, medical procedures, and family visits. Semiology of NCSzs included ictal minor signs and subtle symptoms, such as breathing pattern changes manifested as patient-ventilator dyssynchrony.

Correspondence between scalp-EEG and stereoelectroencephalography seizure-onset patterns in patients with MRI-negative drug-resistant focal epilepsy

OBJECTIVE

Our objective was to evaluate the relationship between scalp-EEG and stereoelectroencephalography (SEEG) seizure-onset patterns (SOP) in patients with MRI-negative drug-resistant focal epilepsy.

METHODS

We analyzed retrospectively 41 patients without visible lesion on brain MRI who underwent video-EEG followed by SEEG. We defined five types of SOPs on scalp-EEG and eight types on SEEG. We examined how various clinical variables affected scalp-EEG SOPs.

RESULTS

The most prevalent scalp SOPs were rhythmic sinusoidal activity (56.8%), repetitive epileptiform discharges (22.7%), and paroxysmal fast activity (15.9%). The presence of paroxysmal fast activity on scalp-EEG was always seen without delay from clinical onset and correlated with the presence of low-voltage fast activity in SEEG (sensitivity = 22.6%, specificity = 100%). The main factor explaining the discrepancy between the scalp and SEEG SOPs was the delay between clinical and scalp-EEG onset. There was a correlation between the scalp and SEEG SOPs when the scalp onset was simultaneous with the clinical onset (p = 0.026). A significant delay between clinical and scalp discharge onset was observed in 25% of patients and featured always with a rhythmic sinusoidal activity on scalp, corresponding to similar morphology of the discharge on SEEG. The presence of repetitive epileptiform discharges on scalp was associated with an underlying focal cortical dysplasia (sensitivity = 30%, specificity = 90%). There was no significant association between the scalp SOP and the epileptogenic zone location (deep or superficial), or surgical outcome.

SIGNIFICANCE

In patients with MRI-negative focal epilepsy, scalp SOP could suggest the SEEG SOP and some etiology (focal cortical dysplasia) but has no correlation with surgical prognosis. Scalp SOP correlates with the SEEG SOP in cases of simultaneous EEG and clinical onset; otherwise, scalp SOP reflects the propagation of the SEEG discharge.

PLAIN LANGUAGE SUMMARY

We looked at the correspondence between the electrical activity recorded during the start of focal seizure using scalp and intracerebral electrodes in patients with no visible lesion on MRI. If there is a fast activity on scalp, it reflects similar activity inside the brain. We found a good correspondence between scalp and intracerebral electrical activity for cases without significant delay between clinical and scalp electrical onset (seen in 75% of the cases we studied). Visualizing repetitive epileptic activity on scalp could suggest a particular cause of the epilepsy: a subtype of brain malformation called focal cortical dysplasia.

Pitfalls in scalp EEG: Current obstacles and future directions

Although electroencephalography (EEG) serves a critical role in the evaluation and management of seizure disorders, it is commonly misinterpreted, resulting in avoidable medical, social, and financial burdens to patients and health care systems. Overinterpretation of sharply contoured transient waveforms as being representative of interictal epileptiform abnormalities lies at the core of this problem. However, the magnitude of these errors is amplified by the high prevalence of paroxysmal events exhibited in clinical practice that compel investigation with EEG. Neurology training programs, which vary considerably both in the degree of exposure to EEG and the composition of EEG didactics, have not effectively addressed this widespread issue. Implementation of competency-based curricula in lieu of traditional educational approaches may enhance proficiency in EEG interpretation amongst general neurologists in the absence of formal subspecialty training. Efforts in this regard have led to the development of a systematic, high-fidelity approach to the interpretation of epileptiform discharges that is readily employable across medical centers. Additionally, machine learning techniques hold promise for accelerating accurate and reliable EEG interpretation, particularly in settings where subspecialty interpretive EEG services are not readily available. This review highlights common diagnostic errors in EEG interpretation, limitations in current educational paradigms, and initiatives aimed at resolving these challenges.

Estimating Patient-Level Uncertainty in Seizure Detection Using Group-Specific Out-of-Distribution Detection Technique

Epilepsy is a chronic neurological disorder affecting around 1% of the global population, characterized by recurrent epileptic seizures. Accurate diagnosis and treatment are crucial for reducing mortality rates. Recent advancements in machine learning (ML) algorithms have shown potential in aiding clinicians with seizure detection in electroencephalography (EEG) data. However, these algorithms face significant challenges due to the patient-specific variability in seizure patterns and the limited availability of high-quality EEG data for training, causing erratic predictions. These erratic predictions are harmful, especially for high-stake domains in healthcare, negatively affecting patients. Therefore, ensuring safety in AI is of the utmost importance. In this study, we propose a novel ensemble method for uncertainty quantification to identify patients with low-confidence predictions in ML-based seizure detection algorithms. Our approach aims to mitigate high-risk predictions in previously unseen seizure patients, thereby enhancing the robustness of existing seizure detection algorithms. Additionally, our method can be implemented with most of the deep learning (DL) models. We evaluated the proposed method against established uncertainty detection techniques, demonstrating its effectiveness in identifying patients for whom the model's predictions are less certain. Our proposed method managed to achieve 87%, 89% and 75% in accuracy, specificity and sensitivity, respectively. This study represents a novel attempt to improve the reliability and robustness of DL algorithms in the domain of seizure detection. This study underscores the value of integrating uncertainty quantification into ML algorithms for seizure detection, offering clinicians a practical tool to gauge the applicability of ML models for individual patients.

BIRDs (Brief Potentially Ictal Rhythmic Discharges) watching during EEG monitoring

Brief Potentially Ictal Rhythmic Discharges (BIRDs), initially described in neonates, have been shown to correlate with increased risk of seizures in both critically ill and non-critically ill adults. In critically ill patients, BIRDs are associated with acute brain injury and worse functional outcomes. In non-critically ill adults, BIRDs are seen in patients with epilepsy with a greater likelihood of having drug resistance. The location of BIRDs seems to better predict the seizure onset zone compared to other interictal epileptiform discharges. The definition of BIRDs includes Paroxysmal Fast Activity (PFA), and they have similar clinical significance regardless of the exact cut-off frequencies. Their potential as a biomarker for seizure activity and seizure onset zone has been suggested. In patients with status epilepticus, BIRDs also resolve or decrease when seizures resolve. Thus, if BIRDs are observed on scalp EEG, more extended EEG monitoring is recommended to estimate their seizure burden and to guide treatment. With the recent addition of BIRDs in the critical care EEG terminology, with future investigations, we may soon be able to reach a consensus about the definition of electrographic seizures and better understand their neurophysiology and clinical significance.

Seizure Duration and Spread Dynamics in MRI-Defined Subtypes of Temporal Lobe Epilepsy

BACKGROUND AND OBJECTIVES

MR and PET imaging enables subgroups of Temporal Lobe Epilepsy (TLE) to be defined on the basis of structural pathology. Few studies have examined the variation in electroclinical seizure spread patterns based on imaging findings. We performed a retrospective cohort study, to investigate the electroclinical differences between three specific groups of TLE: MRI-negative PET-positive TLE (MRI-neg TLE), temporal lobe lesion TLE (Lesional TLE) and unilateral hippocampal sclerosis TLE (HS-TLE).

METHODS

Patients with an electroclinical diagnosis of TLE who had video-scalp EEG recordings of seizures, were identified from the retrospective database of the Austin Comprehensive Epilepsy Program between 2005 and 2019. The cohort was further selected into the three defined groups based on imaging findings, using MRI and FDG-PET. Timings of clinical and electrographic seizure progression were measured, considering the onset, ipsilateral lobar spread, contralateral spread and termination. Durations were compared between groups using linear mixed models with inclusion of demographic and clinical covariates.

RESULTS

A total of 105 patients (137 seizures) were included, comprising 36 with MRI-neg TLE (54 seizures), 36 with Lesional TLE (18 lateral versus 16 mesial lesions; 44 seizures) and 33 with HS-TLE (39 seizures). Seizure duration was similar between MRI-neg TLE and Lesional TLE (mean 75.9 vs 71.7 seconds, p=0.91). Further dividing Lesional TLE into medial versus lateral temporal revealed no timing difference either. However, the HS-TLE group had longer total seizure duration (114 seconds) compared to both MRI-neg TLE (p<0.001) and Lesional TLE (p<0.001). Progression of electrographic spread also reflected this pattern, with involvement of extra-temporal regions and then the contralateral hemisphere each taking significantly longer in HS-TLE.

DISCUSSION

MRI-neg TLE appears electrographically similar to Lesional TLE, whether mesial or lateral, in the duration of seizures and the timing of electrographic spread. Both appear electrographically different from HS-TLE where propagation is slower, suggesting engagement of different epileptogenic networks or seizure suppression mechanisms.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the electroclinical features of seizures in HS-TLE are different than MRI-neg TLE and lesional TLE.

Medical Technology: A Systematic Review on Medical Devices Utilized for Epilepsy Prediction and Management

BACKGROUND

Epilepsy is a devastating neurological disorder that affects nearly 70 million people worldwide. Epilepsy causes uncontrollable, unprovoked and unpredictable seizures that reduce the quality of life of those afflicted, with 1-9 epileptic patient deaths per 1000 patients occurring annually due to sudden unexpected death in epilepsy (SUDEP). Predicting the onset of seizures and managing them may help patients from harming themselves and may improve their well-being. For a long time, electroencephalography (EEG) devices have been the mainstay for seizure detection and monitoring. This systematic review aimed to elucidate and critically evaluate the latest advancements in medical devices, besides EEG, that have been proposed for the management and prediction of epileptic seizures. A literature search was performed on three databases, PubMed, Scopus and EMBASE.

METHODS

Following title/abstract screening by two independent reviewers, 27 articles were selected for critical analysis in this review.

RESULTS

These articles revealed ambulatory, non-invasive and wearable medical devices, such as the in-ear EEG devices; the accelerometer-based devices and the subcutaneous implanted EEG devices might be more acceptable than traditional EEG systems. In addition, extracerebral signalbased devices may be more efficient than EEG-based systems, especially when combined with an intervention trigger. Although further studies may still be required to improve and validate these proposed systems before commercialization, these findings may give hope to epileptic patients, particularly those with refractory epilepsy, to predict and manage their seizures.

CONCLUSION

The use of medical devices for epilepsy may improve patients' independence and quality of life and possibly prevent sudden unexpected death in epilepsy (SUDEP).

The Sensitivity of Scalp EEG at Detecting Seizures-A Simultaneous Scalp and Stereo EEG Study

PURPOSE

Compare the detection rate of seizures on scalp EEG with simultaneous intracranial stereo EEG (SEEG) recordings.

METHODS

Twenty-seven drug-resistant epilepsy patients undergoing SEEG with simultaneous scalp EEG as part of their surgical work-up were included. A total of 172 seizures were captured.

RESULTS

Of the 172 seizures detected on SEEG, 100 demonstrated scalp ictal patterns. Focal aware and subclinical seizures were less likely to be seen on scalp, with 33% of each observed when compared with focal impaired aware (97%) and focal to bilateral tonic-clonic seizures (100%) (P < 0.001). Of the 72 seizures without ictal scalp correlate, 32 demonstrated an abnormality during the SEEG seizure that was identical to an interictal abnormality. Seizures from patients with MRI lesions were statistically less likely to be seen on scalp than seizures from nonlesional patients (P = 0.0162). Stereo EEG seizures not seen on scalp were shorter in duration (49 seconds) compared with SEEG seizures seen on scalp (108.6 seconds) (P < 0.001).

CONCLUSIONS

Scalp EEG is not a sensitive tool for the detection of focal aware and subclinical seizures but is highly sensitive for the detection of focal impaired aware and focal to bilateral tonic-clonic seizures. Longer duration of seizure and seizures from patients without MRI lesions were more likely to be apparent on scalp. Abnormalities seen interictally may at times represent an underlying seizure. The cognitive, affective, and behavioral long-term effects of ongoing difficult-to-detect seizures are not known.

Semiology, EEG, and neuroimaging findings in temporal lobe epilepsies

Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. First descriptions of TLE date back in time and detailed portraits of epileptic seizures of temporal origin can be found in early medical reports as well as in the works of various artists and dramatists. Depending on the seizure onset zone, several subtypes of TLE have been identified, each one associated with peculiar ictal semiology. TLE can result from multiple etiological causes, ranging from genetic to lesional ones. While the diagnosis of TLE relies on detailed analysis of clinical as well as electroencephalographic (EEG) features, the lesions responsible for seizure generation can be highlighted by multiple brain imaging modalities or, in selected cases, by genetic investigations. TLE is the most common cause of refractory epilepsy and despite the great advances in diagnostic tools, no lesion is found in around one-third of patients. Surgical treatment is a safe and effective option, requiring presurgical investigations to accurately identify the seizure onset zone (SOZ). In selected cases, presurgical investigations need intracerebral investigations (such as stereoelectroencephalography) or dedicated metabolic imaging techniques (interictal PET and ictal SPECT) to correctly identify the brain structures to be removed.

Headache in people with epilepsy

Epidemiological estimates indicate that individuals with epilepsy are more likely to experience headaches, including migraine, than individuals without epilepsy. Headaches can be temporally unrelated to seizures, or can occur before, during or after an episode; seizures and migraine attacks are mostly not temporally linked. The pathophysiological links between headaches (including migraine) and epilepsy are complex and have not yet been fully elucidated. Correct diagnoses and appropriate treatment of headaches in individuals with epilepsy is essential, as headaches can contribute substantially to disease burden. Here, we review the insights that have been made into the associations between headache and epilepsy over the past 5 years, including information on the pathophysiological mechanisms and genetic variants that link the two disorders. We also discuss the current best practice for the management of headaches co-occurring with epilepsy and highlight future challenges for this area of research.

Determinants of cognition in autoimmune limbic encephalitis-A retrospective cohort study

Autoimmune limbic encephalitis (ALE) is the most common type of autoimmune encephalitis (AIE). Subacute memory disturbance, temporal lobe seizures, and psychiatric symptoms are clinical hallmarks of the disease. However, little is known on the factors contributing to cognitive functioning in ALE. Hence, we here investigate major determinants of cognitive functioning in ALE. In a retrospective analysis of 102 patients with ALE, we first compared verbal learning capacity, nonverbal learning capacity, and attentional and executive functioning by absence or presence of different types of neural autoantibodies (AABs). Subsequently we established three linear regression models including 63, 38, and 61 patients, respectively to investigate how cognitive functioning in these domains may depend on common markers of ALE such as intrathecal inflammation, blood-cerebrospinal fluid (CSF)-barrier function, mesiotemporal epileptiform discharges and slowing, determined by electroencephalography (EEG) and structural mesiotemporal changes, measured with magnetic resonance imaging (MRI). We also accounted for possible effects of cancer- and immunotherapy and other centrally effective medication. There was no effect of AAB status on cognitive functioning. Although the regression models could not predict verbal and nonverbal learning capacity, structural mesiotemporal neural network alterations on T2-/fluid attenuated inversion recovery (FLAIR)-signal-weighted MRI and mesiotemporal epileptiform discharges or slowing on EEG exerted a significant impact on memory functions. In contrast, the regression model significantly predicted attentional and executive functioning with CSF white blood cell count and centrally effective medication being significant determinants. In this cohort, cognitive functioning in ALE does not depend on the AAB status. Common markers of ALE cannot predict memory functioning that only partially depends on structural and functional alterations of mesiotemporal neural networks. Common markers of ALE significantly predict attentional and executive functioning that is significantly related to centrally effective medication and CSF white blood cell count, which may point toward inflammation affecting brain regions beyond the limbic system.

Seizures in autoimmune encephalitis: Findings from an EEG pooled analysis

PURPOSE

Seizures are common in autoimmune encephalitis (AE), and an extensive work-up is required to exclude alternative etiologies. The aim of our study was to identify possible clinical/EEG peculiarities suggesting the immune-mediated origin of late-onset seizures.

METHODS

Thirty patients diagnosed with AE (19 men, median age 68 years, 18 seronegative) were included. Overall 212 video-electroencephalographic (EEG) and 31 24-h ambulatory EEG (AEEG) recordings were retrospectively reviewed. Posterior dominant rhythm, interictal epileptiform discharges (IEDs), clinical (CSs) and subclinical seizures (SCSs) were analyzed.

RESULTS

Six-hundred-nineteen ictal events were recorded in 19/30 subjects, mostly (568/619) during AE acute stage. Among ten patients with CSs other than faciobrachial dystonic seizures, 7 showed prominent autonomic and emotional manifestations. SCSs were detected in 11 subjects, mainly via AEEG (260/287 SCSs vs 150/332 CSs, p < 0.001). Eight patients presented seizures during hyperventilation. IEDs, documented in 21 cases, were bilateral in 14 and focal temporal in 13. Multiple ictal EEG patterns were detected in 9/19 patients, 6 of whom had both CSs and SCSs, bilateral asynchronous seizures and ictal activities arising from temporal and extra-temporal regions. No correlation was found between the lateralization of MRI alterations and that of EEG findings.

CONCLUSION

Our study confirms that adult-onset, high frequency focal seizures with prominent autonomic and emotional manifestations should be investigated for AE. Multiple ictal EEG patterns could represent a 'red flag', reflecting a widespread neuronal excitability related to the underlying immune-mediated process. Finally, our work enhances the crucial role of long-lasting EEG monitoring in revealing subclinical and relapsing seizures.

Ictal onset sites and γ-aminobutyric acidergic neuron loss in epileptic pilocarpine-treated rats

OBJECTIVE

The present study tested whether ictal onset sites are regions of more severe interneuron loss in epileptic pilocarpine-treated rats, a model of human temporal lobe epilepsy.

METHODS

Local field potential recordings were evaluated to identify ictal onset sites. Electrode sites were visualized in Nissl-stained sections. Adjacent sections were processed with proximity ligation in situ hybridization for glutamic acid decarboxylase 2 (Gad2). Gad2 neuron profile numbers at ictal onset sites were compared to contralateral regions. Other sections were processed with immunocytochemistry for reelin or nitric oxide synthase (NOS), which labeled major subtypes of granule cell layer-associated interneurons. Stereology was used to estimate numbers of reelin and NOS granule cell layer-associated interneurons per hippocampus.

RESULTS

Ictal onset sites varied between and within rats but were mostly in the ventral hippocampus and were frequently bilateral. There was no conclusive evidence of more severe Gad2 neuron profile loss at sites of earliest seizure activity compared to contralateral regions. Numbers of granule cell layer-associated NOS neurons were reduced in the ventral hippocampus.

SIGNIFICANCE

In epileptic pilocarpine-treated rats, ictal onset sites were mostly in the ventral hippocampus, where there was loss of granule cell layer-associated NOS interneurons. These findings suggest the hypothesis that loss of granule cell layer-associated NOS interneurons in the ventral hippocampus is a mechanism of temporal lobe epilepsy.

Realistic spiking neural network: Non-synaptic mechanisms improve convergence in cell assembly

Learning in neural networks inspired by brain tissue has been studied for machine learning applications. However, existing works primarily focused on the concept of synaptic weight modulation, and other aspects of neuronal interactions, such as non-synaptic mechanisms, have been neglected. Non-synaptic interaction mechanisms have been shown to play significant roles in the brain, and four classes of these mechanisms can be highlighted: (i) electrotonic coupling; (ii) ephaptic interactions; (iii) electric field effects; and iv) extracellular ionic fluctuations. In this work, we proposed simple rules for learning inspired by recent findings in machine learning adapted to a realistic spiking neural network. We show that the inclusion of non-synaptic interaction mechanisms improves cell assembly convergence. By including extracellular ionic fluctuation represented by the extracellular electrodiffusion in the network, we showed the importance of these mechanisms to improve cell assembly convergence. Additionally, we observed a variety of electrophysiological patterns of neuronal activity, particularly bursting and synchronism when the convergence is improved.

Ultra-long-term subcutaneous home monitoring of epilepsy-490 days of EEG from nine patients

Objective

To explore the feasibility of home monitoring of epilepsy patients with a novel subcutaneous electroencephalography (EEG) device, including clinical implications, safety, and compliance via the first real‐life test.

Methods

We implanted a beta‐version of the 24/7 EEG SubQ (UNEEG Medical A/S, Denmark) subcutaneously in nine participants with temporal lobe epilepsy. Data on seizures, adverse events, compliance in using the device, and use of antiepileptic drugs (AEDs) were collected. EEG was recorded for up to 3 months, and all EEG data were reviewed visually to identify electrographic seizures. These were descriptively compared to seizure counts and AED changes reported in diaries from the same period.

Results

Four hundred ninety days of EEG and 338 electrographic seizures were collected. Eight participants completed at least 9 weeks of home monitoring, while one cancelled participation after 4 weeks due to postimplantation soreness. In total, 13 cases of device‐related adverse events were registered, none of them serious. Recordings obtained from the device covered 73% of the time, on average (range 45%‐91%). Descriptively, electrographic seizure counts were substantially different from diary seizure counts. We uncovered several cases of underreporting and revealed important information on AED response. Electrographic seizure counts revealed circadian distributions of seizures not visible from seizure diaries.

Significance

The study shows that home monitoring for up to 3 months with a subcutaneous EEG device is feasible and well tolerated. No serious adverse device‐related events were reported. An objective seizure count can be derived, which often differs substantially from self‐reported seizure counts. Larger clinical trials quantifying the benefits of objective seizure counting should be a priority for future research as well as development of algorithms for automated review of data.

New Approaches to Studying Silent Mesial Temporal Lobe Seizures in Alzheimer's Disease

Silent seizures were discovered in mouse models of Alzheimer's disease over 10 years ago, yet it remains unclear whether these seizures are a salient feature of Alzheimer's disease in humans. Seizures that arise early in the course of Alzheimer's disease most likely originate from the mesial temporal lobe, one of the first structures affected by Alzheimer's disease pathology and one of the most epileptogenic regions of the brain. Several factors greatly limit our ability to identify mesial temporal lobe seizures in patients with Alzheimer's disease, however. First, mesial temporal lobe seizures can be difficult to recognize clinically, as their accompanying symptoms are often subtle or even non-existent. Second, electrical activity arising from the mesial temporal lobe is largely invisible on the scalp electroencephalogram (EEG), the mainstay of diagnosis for epilepsy in this population. In this review, we will describe two new approaches being used to study silent mesial temporal lobe seizures in Alzheimer's disease. We will first describe the methodology and application of foramen ovale electrodes, which captured the first recordings of silent mesial temporal lobe seizures in humans with Alzheimer's disease. We will then describe machine learning approaches being developed to non-invasively identify silent mesial temporal lobe seizures on scalp EEG. Both of these tools have the potential to elucidate the role of silent seizures in humans with Alzheimer's disease, which could have important implications for early diagnosis, prognostication, and development of targeted therapies for this population.

Non-electrographic Seizures Due to Subdural Hematoma: A Case Series and Review of the Literature

Seizures due to subdural hematoma (SDH) are a common finding, typically diagnosed using electroencephalography (EEG). At times, aggressive management of seizures is necessary to improve neurologic recovery and outcomes. Here, we present three patients who had undergone emergent SDH evacuation and showed postoperative focal deficits without accompanying electrographic epileptiform activity. After infarction and recurrent hemorrhage were ruled out, seizures were suspected despite a negative EEG. Patients were treated aggressively with AEDs and eventually showed clinical improvement. Long-term monitoring with EEG revealed electrographic seizures in a delayed fashion. EEG recordings are an important tool for seizure detection, but should be used as an adjunct to, rather than a replacement for, the clinical examination in the acute setting. At times, aggressive treatment of suspected postoperative seizures is warranted despite lack of corresponding electrographic activity and can improve clinical outcomes.

Focal epilepsies and focal disorders

Electroencephalographic (EEG) investigations are crucial in the diagnosis and management of patients with focal epilepsies. EEG may reveal different interictal epileptiform discharges (IEDs: abnormal spikes, sharp waves). The EEG visibility of a spike depends on the surface area of cortex involved (>10cm²) and the brain localization of cortical generators. Regions generating IEDs (defining the "irritative zone") are not necessarily equivalent to the seizure onset zone. Focal seizures are dynamic processes originating from one or several brain regions (that generate fast oscillations and are called the epileptogenic zone) before spreading to other structures (that generate lower frequency oscillations and are called the propagation zone). Several factors limit the expression of seizures on scalp EEG, such as the area involved, degree of synchronization, and depth of the cortical generators. Different scalp EEG seizure onset patterns may be observed: fast discharge, background flattening, rhythmic spikes, sinusoidal discharge, or sharp activity. However, to a large extent EEG changes are linked to seizure propagation. Finally, in the context of presurgical evaluation, the combination of interictal and ictal EEG features is crucial to provide an optimal hypothesis concerning the epileptogenic zone.

Simultaneous scalp EEG improves seizure lateralization during unilateral intracranial EEG evaluation in temporal lobe epilepsy

PURPOSE

To determine if simultaneous bilateral scalp EEG (scEEG) can accurately detect a contralateral seizure onset in patients with unilateral intracranial EEG (IEEG) implantation.

METHODS

We evaluated 39 seizures from 9 patients with bitemporal epilepsy who underwent simultaneous scEEG and IEEG (SSIEEG). To simulate conditions of unilateral IEEG implantation with a missed contralateral seizure onset, we analyzed the IEEG recording contralateral to the seizure onset (CL- IEEG), in conjunction with simultaneous scEEG. The following criteria were evaluated between scEEG and CL- IEEG (1) latency: the time to onset of EEG seizure (2) location: concordance of ictal onset zones and (3) pattern: congruence of EEG morphology and frequency.

RESULTS

SSIEEG correctly lateralized 36/39 (92.3%) seizures compared to 13/39 (33.3%) seizures using CL- IEEG alone (OR = 24.0, p < 0.01), 33 (84.6%) seizures using scEEG alone (OR = 2.2, p = 0.29) and 26 (66.9%) seizures using time of clinical onset alone (OR = 6.0, p = 0.01). For the three criteria evaluated, (1) 22/39 (56.4%) seizures had an earlier onset on the scEEG, compared to CL- IEEG; (2) lack of congruence of location of seizure onset was noted in 33/39 (84.6%) of the seizures; and (3) 22/39 (56.4%) seizures did not have a congruent ictal pattern.

CONCLUSIONS

The chronological, topographic and morphologic features of SSIEEG can accurately detect the hemisphere of seizure onset in most cases with unilateral IEEG implantation. SSIEEG is significantly better than, IEEG, scEEG or clinical onset alone in this scenario. We propose that SSIEEG should be considered in all cases of intractable focal epilepsy undergoing unilateral IEEG evaluation.

The Hippocampus and Cortex Together Generate the Scalp EEG Ictal Discharge in Temporal Lobe Epilepsy

PURPOSE

The scalp EEG ictal discharge in temporal lobe epilepsy is reportedly visible only after the intracranial discharge becomes well synchronized and present over 10 to 30 cm of cortex. We investigated the role of the hippocampal formation in the generation of the scalp EEG ictal discharge.

METHODS

Intracranial EEG video monitors were recorded using simultaneous scalp, stereotaxic depth, and subdural strip electrodes in 19 subjects with temporal lobe epilepsy. The location, frequency, morphology, and timing of the initial ictal discharge, and subsequent ictal patterns, were examined in hippocampal formation, medial paleocortex, and lateral temporal neocortex electrocorticographic and scalp temporal EEG recordings.

RESULTS

In every subject, a scalp ictal discharge was visible only after the intracranial ictal discharge had spread to involve the whole temporal lobe (hippocampal formation, medial paleocortex, and lateral temporal neocortex). Beta/gamma frequency and decremental electrocorticographic ictal discharges were never visualized in the EEG. The scalp EEG ictal discharge frequency was 2.4 to 10 Hz and appeared a median of 18 seconds after a faster frequency electrocorticographic initial ictal discharge, once the intracranial discharge slowed to an alpha, theta, or delta frequency.

CONCLUSIONS

In temporal lobe epilepsy, an ictal pattern is not readily visible in the scalp EEG until the intracranial ictal discharge is ≤10 Hz and has propagated from its site of onset to involve the hippocampus, medial paleocortex, and lateral temporal neocortex.

Features of Simultaneous Scalp and Intracranial EEG That Predict Localization of Ictal Onset Zone

OBJECTIVE

To assess the utility of simultaneous scalp EEG in patients with focal epilepsy undergoing intracranial EEG evaluation after a detailed presurgical testing, including an inpatient scalp video EEG evaluation.

METHODS

Patients who underwent simultaneous scalp and intracranial EEG (SSIEEG) monitoring were classified into group 1 or 2 depending on whether the seizure onset zone was delineated or not. Seizures were analyzed using the following 3 EEG features at the onset of seizures latency, location, and pattern.

RESULTS

The criteria showed at least one of the following features when comparing SSIEEG: prolonged latency, absence of anatomical congruence, lack of concordance of EEG pattern in 11.11% (1/9) of the patients in group 1 and 75 % (3/4) of the patients in group 2. These 3 features were not present in any of the 5 patients who had Engel class I outcome compared with 1 of the 2 patients (50%) who had seizure recurrence after resective surgery. The mean latency of seizure onset in scalp EEG compared with intracranial EEG of patients in group 1 was 17.48 seconds (SD = 16.07) compared with 4.33 seconds (SD = 11.24) in group 2 ( P = .03). None of the seizures recorded in patients in group 1 had a discordant EEG pattern in SSIEEG.

CONCLUSION

Concordance in EEG features like latency, location, and EEG pattern, at the onset of seizures in SSIEEG is associated with a favorable outcome after epilepsy surgery in patients with intractable focal epilepsy.

SIGNIFICANCE

Simultaneous scalp EEG complements intracranial EEG evaluation even after a detailed inpatient scalp video EEG evaluation and could be part of standard intracranial EEG studies in patients with intractable focal epilepsy.

Association between scalp and intracerebral electroencephalographic seizure-onset patterns: A study in different lesional pathological substrates

OBJECTIVE

Our purpose was to determine the correlation between scalp electroencephalography (EEG) and intracerebral EEG (iEEG) seizure-onset patterns in patients with focal lesional epilepsy to determine whether scalp seizure-onset patterns can be specific to intracerebral seizure-onset patterns and to lesion type.

METHODS

We retrospectively analyzed 61 patients with focal epilepsy and a structural magnetic resonance imaging (MRI)-visible lesion, who first underwent extensive scalp recordings and then iEEG studies (stereo-EEG) for presurgical evaluation, and who showed an iEEG seizure onset in the lesional/perilesional area. Five seizure-onset patterns were recognized on scalp EEG, and 7 on iEEG, and in each patient, only the predominant scalp and iEEG seizure-onset patterns were compared. Because scalp and iEEG recordings were acquired at different times, we followed strict criteria based on semiology and topography to match scalp with intracerebral seizures.

RESULTS

Seventy-one pairs of seizure-onset patterns matched between scalp and iEEG were identified. Each scalp pattern did not correspond to a single intracerebral pattern, but there were significant associations: (1) paroxysmal fast activity (≥13 Hz) at scalp onset was associated with low-voltage fast activity at iEEG onset (P < .001), with malformations of cortical development (P < .001), and with superficial seizure-onset zone based on iEEG (P < .001); (2) rhythmic slow activity (<13 Hz) at scalp onset was associated with low-frequency high-amplitude periodic spikes at iEEG onset (P = .0014), with medial temporal atrophy/sclerosis (P < .001), and with deep seizure-onset zone (P < .001); and (3) repetitive epileptiform discharge at scalp onset was associated with a burst of high-amplitude polyspikes at iEEG onset (P = .0002).

SIGNIFICANCE

Our results disclosed that in focal epilepsy patients with seizures generated in an MRI-visible lesion, some scalp seizure-onset patterns are highly associated with a specific intracerebral pattern, with specific pathologies, and with the depth of seizure-onset zone. These findings allow the interpretation of scalp seizure-onset patterns to be significantly more informative.

SCOPE-mTL: A non-invasive tool for identifying and lateralizing mesial temporal lobe seizures prior to scalp EEG ictal onset

OBJECTIVE

In mesial temporal lobe (mTL) epilepsy, seizure onset can precede the appearance of a scalp EEG ictal pattern by many seconds. The ability to identify this early, occult mTL seizure activity could improve lateralization and localization of mTL seizures on scalp EEG.

METHODS

Using scalp EEG spectral features and machine learning approaches on a dataset of combined scalp EEG and foramen ovale electrode recordings in patients with mTL epilepsy, we developed an algorithm, SCOPE-mTL, to detect and lateralize early, occult mTL seizure activity, prior to the appearance of a scalp EEG ictal pattern.

RESULTS

Using SCOPE-mTL, 73% of seizures with occult mTL onset were identified as such, and no seizures that lacked an occult mTL onset were identified as having one. Predicted mTL seizure onset times were highly correlated with actual mTL seizure onset times (r=0.69). 50% of seizures with early mTL onset were lateralizable prior to scalp ictal onset, with 94% accuracy.

CONCLUSIONS

SCOPE-mTL can identify and lateralize mTL seizures prior to scalp EEG ictal onset, with high sensitivity, specificity, and accuracy.

SIGNIFICANCE

Quantitative analysis of scalp EEG can provide important information about mTL seizures, even in the absence of a visible scalp EEG ictal correlate.

Widespread changes in network activity allow non-invasive detection of mesial temporal lobe seizures

Decades of experience with intracranial recordings in patients with epilepsy have demonstrated that seizures can occur in deep cortical regions such as the mesial temporal lobes without showing any obvious signs of seizure activity on scalp electroencephalogram. Predicated on the idea that these seizures are purely focal, currently, the only way to detect these 'scalp-negative seizures' is with intracranial recordings. However, intracranial recordings are only rarely performed in patients with epilepsy, and are almost never performed outside of the context of epilepsy. As such, little is known about scalp-negative seizures and their role in the natural history of epilepsy, their effect on cognitive function, and their association with other neurological diseases. Here, we developed a novel approach to non-invasively identify scalp-negative seizures arising from the mesial temporal lobe based on scalp electroencephalogram network connectivity measures. We identified 25 scalp-negative mesial temporal lobe seizures in 10 patients and obtained control records from an additional 13 patients, all of whom underwent recordings with foramen ovale electrodes and scalp electroencephalogram. Scalp data from these records were used to train a scalp-negative seizure detector, which consisted of a pair of logistic regression classifiers that used scalp electroencephalogram coherence properties as input features. On cross-validation performance, this detector correctly identified scalp-negative seizures in 40% of patients, and correctly identified the side of seizure onset for each seizure detected. In comparison, routine clinical interpretation of these scalp electroencephalograms failed to identify any of the scalp-negative seizures. Among the patients in whom the detector raised seizure alarms, 80% had scalp-negative mesial temporal lobe seizures. The detector had a false alarm rate of only 0.31 per day and a positive predictive value of 75%. Of the 13 control patients, false seizure alarms were raised in only one patient. The fact that our detector specifically recognizes focal mesial temporal lobe seizures based on scalp electroencephalogram coherence features, lends weight to the hypothesis that even focal seizures are a network phenomenon that involve widespread neural connectivity. Our scalp-negative seizure detector has clear clinical utility in patients with temporal lobe epilepsy, and its potential easily translates to other neurological disorders, such as Alzheimer's disease, in which occult mesial temporal lobe seizures are suspected to play a significant role. Importantly, our work establishes a novel approach of using computational approaches to non-invasively detect deep seizure activity, without the need for invasive intracranial recordings.

Correlation of invasive EEG and scalp EEG

Ever since the implementation of invasive EEG recordings in the clinical setting, it has been perceived that a considerable proportion of epileptic discharges present at a cortical level are missed by routine scalp EEG recordings. Several in vitro, in vivo, and simulation studies have been performed in the past decades aiming to clarify the interrelations of cortical sources with their scalp and invasive EEG correlates. The amplitude ratio of cortical potentials to their scalp EEG correlates, the extent of the cortical area involved in the discharge, as well as the localization of the cortical source and its geometry have been each independently linked to the recording of the cortical discharge with scalp electrodes. The need to elucidate these interrelations has been particularly imperative in the field of epilepsy surgery with its rapidly growing EEG-based localization technologies. Simultaneous multiscale EEG recordings with scalp, subdural and/or depth electrodes, applied in presurgical epilepsy workup, offer an excellent opportunity to shed some light to this fundamental issue. Whereas past studies have considered predominantly neocortical sources in the context of temporal lobe epilepsy, current investigations have included deep sources, as in mesial temporal epilepsy, as well as extratemporal sources. Novel computational tools may serve to provide surrogates for the shortcomings of EEG recording methodology and facilitate further developments in modern electrophysiology.

Specific imbalance of excitatory/inhibitory signaling establishes seizure onset pattern in temporal lobe epilepsy

Low-voltage fast (LVF) and hypersynchronous (HYP) patterns are the seizure-onset patterns most frequently observed in intracranial EEG recordings from mesial temporal lobe epilepsy (MTLE) patients. Both patterns also occur in models of MTLE in vivo and in vitro, and these studies have highlighted the predominant involvement of distinct neuronal network/neurotransmitter receptor signaling in each of them. First, LVF-onset seizures in epileptic rodents can originate from several limbic structures, frequently spread, and are associated with high-frequency oscillations in the ripple band (80-200 Hz), whereas HYP onset seizures initiate in the hippocampus and tend to remain focal with predominant fast ripples (250-500 Hz). Second, in vitro intracellular recordings from principal cells in limbic areas indicate that pharmacologically induced seizure-like discharges with LVF onset are initiated by a synchronous inhibitory event or by a hyperpolarizing inhibitory postsynaptic potential barrage; in contrast, HYP onset is associated with a progressive impairment of inhibition and concomitant unrestrained enhancement of excitation. Finally, in vitro optogenetic experiments show that, under comparable experimental conditions (i.e., 4-aminopyridine application), the initiation of LVF- or HYP-onset seizures depends on the preponderant involvement of interneuronal or principal cell networks, respectively. Overall, these data may provide insight to delineate better therapeutic targets in the treatment of patients presenting with MTLE and, perhaps, with other epileptic disorders as well.

Interneurons contribute to the hemodynamic/metabolic response to epileptiform discharges

Interpretation of hemodynamic responses in epilepsy is hampered by an incomplete understanding of the underlying neurovascular coupling, especially the contributions of excitation and inhibition. We made simultaneous multimodal recordings of local field potentials (LFPs), firing of individual neurons, blood flow, and oxygen level in the somatosensory cortex of anesthetized rats. Epileptiform discharges induced by bicuculline injections were used to trigger large local events. LFP and blood flow were robustly coupled, as were LFP and tissue oxygen. In a parametric linear model, LFP and the baseline activities of cerebral blood flow and tissue partial oxygen tension contributed significantly to blood flow and oxygen responses. In an analysis of recordings from 402 neurons, blood flow/tissue oxygen correlated with the discharge of putative interneurons but not of principal cells. Our results show that interneuron activity is important in the vascular and metabolic responses during epileptiform discharges.

Initiation, Propagation, and Termination of Partial (Focal) Seizures

The neurophysiological patterns that correlate with partial (focal) seizures are well defined in humans by standard electroencephalogram (EEG) and presurgical depth electrode recordings. Seizure patterns with similar features are reproduced in animal models of partial seizures and epilepsy. However, the network determinants that support interictal spikes, as well as the initiation, progression, and termination of seizures, are still elusive. Recent findings show that inhibitory networks are prominently involved at the onset of these seizures, and that extracellular changes in potassium contribute to initiate and sustain seizure progression. The end of a partial seizure correlates with an increase in network synchronization, which possibly involves both excitatory and inhibitory mechanisms.

Preictal activity of subicular, CA1, and dentate gyrus principal neurons in the dorsal hippocampus before spontaneous seizures in a rat model of temporal lobe epilepsy

Previous studies suggest that spontaneous seizures in patients with temporal lobe epilepsy might be preceded by increased action potential firing of hippocampal neurons. Preictal activity is potentially important because it might provide new opportunities for predicting when a seizure is about to occur and insight into how spontaneous seizures are generated. We evaluated local field potentials and unit activity of single, putative excitatory neurons in the subiculum, CA1, CA3, and dentate gyrus of the dorsal hippocampus in epileptic pilocarpine-treated rats as they experienced spontaneous seizures. Average action potential firing rates of neurons in the subiculum, CA1, and dentate gyrus, but not CA3, increased significantly and progressively beginning 2-4 min before locally recorded spontaneous seizures. In the subiculum, CA1, and dentate gyrus, but not CA3, 41-57% of neurons displayed increased preictal activity with significant consistency across multiple seizures. Much of the increased preictal firing of neurons in the subiculum and CA1 correlated with preictal theta activity, whereas preictal firing of neurons in the dentate gyrus was independent of theta. In addition, some CA1 and dentate gyrus neurons displayed reduced firing rates preictally. These results reveal that different hippocampal subregions exhibit differences in the extent and potential underlying mechanisms of preictal activity. The finding of robust and significantly consistent preictal activity of subicular, CA1, and dentate neurons in the dorsal hippocampus, despite the likelihood that many seizures initiated in other brain regions, suggests the existence of a broader neuronal network whose activity changes minutes before spontaneous seizures initiate.

Clinical and electrographic findings in epileptic vertigo and dizziness: a systematic review

OBJECTIVE

Seizures can cause vestibular symptoms, even without obvious epileptic features. We sought to characterize epileptic vertigo or dizziness (EVD) to improve differentiation from nonepileptic causes, particularly when vestibular symptoms are the sole manifestation.

METHODS

We conducted a systematic review with electronic (Medline) and manual search for English-language studies (1955-2014). Two independent reviewers selected studies. Study/patient characteristics were abstracted. We defined 3 study population types: (1) seizures, some experiencing vertigo/dizziness (disease cohort); (2) vertigo/dizziness, some due to seizures (symptom cohort); (3) vertigo/dizziness due to seizures in all patients (EVD-only cohort).

RESULTS

We identified 84 studies describing 11,354 patients (disease cohort = 8,129; symptom cohort = 2,965; EVD-only cohort = 260). Among 1,055 EVD patients in whom a distinction could be made, non-isolated EVD was present in 8.5%, isolated EVD in 0.8%. Thorough diagnostic workups (ictal EEG, vestibular testing, and brain MRI to exclude other causes) were rare (<0.1%). Ictal EEG was reported in 487 (4.3%), formal neuro-otologic assessment in 1,107 (9.7%). Localized EEG abnormalities (n = 350) were most frequently temporal (79.8%) and uncommonly parietal (11.8%). Duration of episodic vestibular symptoms varied, but was very brief (<30 seconds) in 69.6% of isolated EVD and 6.9% of non-isolated EVD.

CONCLUSIONS

Non-isolated EVD is much more prevalent than isolated EVD, which appears to be rare. Diagnostic evaluations for EVD are often incomplete. EVD is primarily associated with temporal lobe seizures; whether this reflects greater epidemiologic prevalence of temporal lobe seizures or a tighter association with dizziness/vertigo presentations than with other brain regions remains unknown. Consistent with clinical wisdom, isolated EVD spells often last just seconds, although many patients experience longer spells.

Olfactory Hallucinations without Clinical Motor Activity: A Comparison of Unirhinal with Birhinal Phantosmia

Olfactory hallucinations without subsequent myoclonic activity have not been well characterized or understood. Herein we describe, in a retrospective study, two major forms of olfactory hallucinations labeled phantosmias: one, unirhinal, the other, birhinal. To describe these disorders we performed several procedures to elucidate similarities and differences between these processes. From 1272, patients evaluated for taste and smell dysfunction at The Taste and Smell Clinic, Washington, DC with clinical history, neurological and otolaryngological examinations, evaluations of taste and smell function, EEG and neuroradiological studies 40 exhibited cyclic unirhinal phantosmia (CUP) usually without hyposmia whereas 88 exhibited non-cyclic birhinal phantosmia with associated symptomology (BPAS) with hyposmia. Patients with CUP developed phantosmia spontaneously or after laughing, coughing or shouting initially with spontaneous inhibition and subsequently with Valsalva maneuvers, sleep or nasal water inhalation; they had frequent EEG changes usually ipsilateral sharp waves. Patients with BPAS developed phantosmia secondary to several clinical events usually after hyposmia onset with few EEG changes; their phantosmia could not be initiated or inhibited by any physiological maneuver. CUP is uncommonly encountered and represents a newly defined clinical syndrome. BPAS is commonly encountered, has been observed previously but has not been clearly defined. Mechanisms responsible for phantosmia in each group were related to decreased gamma-aminobutyric acid (GABA) activity in specific brain regions. Treatment which activated brain GABA inhibited phantosmia in both groups.

Early activation of ventral hippocampus and subiculum during spontaneous seizures in a rat model of temporal lobe epilepsy

Temporal lobe epilepsy is the most common form of epilepsy in adults. The pilocarpine-treated rat model is used frequently to investigate temporal lobe epilepsy. The validity of the pilocarpine model has been challenged based largely on concerns that seizures might initiate in different brain regions in rats than in patients. The present study used 32 recording electrodes per rat to evaluate spontaneous seizures in various brain regions including the septum, dorsomedial thalamus, amygdala, olfactory cortex, dorsal and ventral hippocampus, substantia nigra, entorhinal cortex, and ventral subiculum. Compared with published results from patients, seizures in rats tended to be shorter, spread faster and more extensively, generate behavioral manifestations more quickly, and produce generalized convulsions more frequently. Similarities to patients included electrographic waveform patterns at seizure onset, variability in sites of earliest seizure activity within individuals, and variability in patterns of seizure spread. Like patients, the earliest seizure activity in rats was recorded most frequently within the hippocampal formation. The ventral hippocampus and ventral subiculum displayed the earliest seizure activity. Amygdala, olfactory cortex, and septum occasionally displayed early seizure latencies, but not above chance levels. Substantia nigra and dorsomedial thalamus demonstrated consistently late seizure onsets, suggesting their unlikely involvement in seizure initiation. The results of the present study reveal similarities in onset sites of spontaneous seizures in patients with temporal lobe epilepsy and pilocarpine-treated rats that support the model's validity.

Dynamic neurovascular coupling and uncoupling during ictal onset, propagation, and termination revealed by simultaneous in vivo optical imaging of neural activity and local blood volume

Traditional models of ictal propagation involve the concept of an initiation site and a progressive outward march of activation. The process of neurovascular coupling, whereby the brain supplies oxygenated blood to metabolically active neurons presumably results in a similar outward cascade of hyperemia. However, ictal neurovascular coupling has never been assessed in vivo using simultaneous measurements of membrane potential change and hyperemia with wide spatial sampling. In an acute rat ictal model, using simultaneous intrinsic optical signal (IOS) and voltage-sensitive dye (VSD) imaging of cerebral blood volume and membrane potential changes, we demonstrate that seizures consist of multiple dynamic multidirectional waves of membrane potential change with variable onset sites that spread through a widespread network. Local blood volume evolves on a much slower spatiotemporal scale. At seizure onset, the VSD waves extend beyond the IOS signal. During evolution, spatial correlation with hemodynamic signal only exists briefly at the maximal spread of the VSD signal. At termination, the IOS signal extends spatially and temporally beyond the VSD waves. Hence, vascular reactivity evolves in a separate but parallel fashion to membrane potential changes resulting in a mechanism of neurovascular coupling and uncoupling, which is as dynamic as the seizure itself.

A novel telemetry system for recording EEG in small animals

It has become increasingly evident that continuous EEG monitoring is necessary to observe the development of epilepsy in animals, and to determine the effect of drugs on spontaneous seizures. Telemetric recording systems have been increasingly used to monitor EEG in freely moving animals. One challenge faced by such systems is to monitor frequencies above 80Hz continuously for weeks. We present an implantable, 2.4-ml, telemetric sensor that can monitor EEG at 512 samples per second for eight weeks in a freely moving animal. With minor modifications, the same transmitter can operate at higher sample rates with a proportional decrease in operating life. Signal transmission is through bursts of 915-MHz radio power. The burst transmission and several other novel techniques reduce the transmitter's power consumption by two orders of magnitude while allowing 8 transmitters to share the same recording system. The use of radio-frequency transmission permits digitization within the sensor to sixteen-bit resolution, thus eliminating transmission-generated signal noise. The result is a signal with dynamic range 9mV, bandwidth 160Hz, input noise 12μV, and AC power interference less than 1μV. All circuit diagrams are open-source. Data acquisition takes place over the Internet using open-source software that works on multiple operating systems. The resulting system permits long-term, continuous, monitoring of EEG signals, therefore providing continuous and reliable data upon which to base studies of epilepsy in freely moving animals.

An assessment of MEG coherence imaging in the study of temporal lobe epilepsy

PURPOSE

This study examines whether magnetoencephalographic (MEG) coherence imaging is more sensitive than the standard single equivalent dipole (ECD) model in lateralizing the site of epileptogenicity in patients with drug-resistant temporal lobe epilepsy (TLE).

METHODS

An archival review of ECD MEG analyses of 30 presurgical patients with TLE was undertaken with data extracted subsequently for coherence analysis by a blinded reviewer for comparison of accuracy of lateralization. Postoperative outcome was assessed by Engel classification. MEG coherence images were generated from 10 min of spontaneous brain activity and compared to surgically resected brain areas outlined on each subject's magnetic resonance image (MRI). Coherence values were averaged independently for each hemisphere to ascertain the laterality of the epileptic network. Reliability between runs was established by calculating the correlation between epochs. Match rates compared the results of each of the two MEG analyses with optimal postoperative outcome.

KEY FINDINGS

The ECD method provided an overall match rate of 50% (13/16 cases) for Engel class I outcomes, with 37% (11/30 cases) found to be indeterminate (i.e., no spikes identified on MEG). Coherence analysis provided an overall match rate of 77% (20/26 cases). Of 19 cases without evidence of mesial temporal sclerosis, coherence analysis correctly lateralized the side of TLE in 11 cases (58%). Sensitivity of the ECD method was 41% (indeterminate cases included) and that of the coherence method 73%, with a positive predictive value of 70% for an Engel class Ia outcome. Intrasubject coherence imaging reliability was consistent from run-to-run (correlation > 0.90) using three 10-min epochs.

SIGNIFICANCE

MEG coherence analysis has greater sensitivity than the ECD method for lateralizing TLE and demonstrates reliable stability from run-to-run. It, therefore, improves upon the capability of MEG in providing further information of use in clinical decision-making where the laterality of TLE is questioned.

Electroencephalographic features of temporal lobe epilepsy

Electroencephalography (EEG) is an important tool for diagnosing, lateralizing and localizing temporal lobe seizures. In this paper, we review the EEG characteristics of temporal lobe epilepsy (TLE). Several "non-standard" electrodes may be needed to further evaluate the EEG localization, Ictal EEG recording is a major component of preoperative protocols for surgical consideration. Various ictal rhythms have been described including background attenuation, start-stop-start phenomenon, irregular 2-5 Hz lateralized activity, and 5-10 Hz sinusoidal waves or repetitive epileptiform discharges. The postictal EEG can also provide valuable lateralizing information. Postictal delta can be lateralized in 60% of patients with TLE and is concordant with the side of seizure onset in most patients. When patients are being considered for resective surgery, invasive EEG recordings may be needed. Accurate localization of the seizure onset in these patients is required for successful surgical management.

Two forms of déjà vu experiences in patients with epilepsy

Persons with epilepsy experience déjà vu phenomena with or without seizure recognition. Déjà vu experiences are also common mental phenomena in nonclinical individuals. The purpose of this study was to clarify two forms of déjà vu experiences in persons with epilepsy. Déjà vu experiences of 312 patients with epilepsy and 402 nonclinical individuals were evaluated using the Inventory of Déjà vu Experiences Assessment. In the patients with epilepsy, characteristics of déjà vu experiences with seizure recognition (SR form) were compared with those experiences with no seizure recognition (NSR form). The incidence (63.1%) of déjà vu experiences in patients with epilepsy was significantly lower than that (76.1%) of nonclinical individuals (chi(2)=14.2, P=0.000). Among the patients with epilepsy, 55.6% had the NSR form and 24.0% had the SR form. Those with the NSR form manifested fewer psychopathological characteristics than did those with the SR form. Patients tended to view the SR form more negatively (i.e., frightened, uncomfortable, or disturbed) than the NSR form. The NSR form was significantly associated with idiopathic generalized epilepsies, less frequent antiepileptic drug administration, and no mesial temporal sclerosis. Although there was a significant association between the frequency of the SR form and patients' habitual seizures, the frequency of the NSR form was not associated with the frequency of the patients' habitual seizures. Persons with epilepsy experience two forms of déjà vu which are differently associated with their seizure recognition.

Judging a Book by Its Cover: Seizures versus Its Mimickers

Interrater Reliability of EEG-Video Monitoring. Benbadis SR, LaFrance WC Jr, Papandonatos GD, Korabathina K, Lin K, Kraemer HC, NES Treatment Workshop. Neurology 2009;73(11):843–846. OBJECTIVE: The diagnosis of psychogenic nonepileptic seizures (PNES) can be challenging. In the absence of a gold standard to verify the reliability of the diagnosis by EEG-video, we sought to assess the interrater reliability of the diagnosis using EEG-video recordings. METHODS: Patient samples consisted of 22 unselected consecutive patients who underwent EEG-video monitoring and had at least an episode recorded. Other test results and histories were not provided because the goal was to assess the reliability of the EEG-video. Data were sent to 22 reviewers, who were board-certified neurologists and practicing epileptologists at epilepsy centers. Choices were: 1) PNES, 2) epilepsy, and 3) nonepileptic but not psychogenic (“physiologic”) events. Interrater agreement was measured using a κ coefficient for each diagnostic category. We used generalized κ coefficients, which measure the overall level of between-method agreement beyond that which can be ascribed to chance. We also report category-specific κ values. RESULTS: For the diagnosis of PNES, there was moderate agreement ( κ = 0.57, 95% confidence interval [CI] 0.39–0.76). For the diagnosis of epilepsy, there was substantial agreement ( κ = 0.69, 95% CI 0.51–0.86). For physiologic nonepileptic episodes, the agreement was low ( κ = 0.09, 95% CI 0.02–0.27). The overall κ statistic across all three diagnostic categories was moderate at 0.56 (95% CI 0.41–0.73). CONCLUSIONS: Interrater reliability for the diagnosis of PNES by EEG-video monitoring was only moderate. Although this may be related to limitations of the study (diagnosis based on EEG-video alone, artificial nature of the forced choice paradigm, single episode), it highlights the difficulties and subjective components inherent to this diagnosis.