Electromagnetic evidence that benign epileptiform transients of sleep are traveling, rotating hippocampal spikes

Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity

Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.

Benign epileptiform variants in EEG: A comprehensive study of 3000 patients

BACKGROUND

The analysis of EEG demands expertise and keen observation to distinguish epileptiform discharges from benign epileptiform variants (BEVs), a frequent source of erroneous interpretation. The prevalence of BEVs varies based on geographical, racial, and ethnic characteristics. However, most data on BEVs originates from Western populations, and additional studies on different cohorts would enrich the existing literature.

METHODS

We reviewed EEGs from our institutional database to study the prevalence of benign epileptiform variants and analyzed their frequency, topography, and other characteristics. Additionally, we investigated the co-existence of epileptiform discharges with BEVs.

RESULTS

We identified 296 patients with BEVs after reviewing 3000 EEGs (9.9%). The most common BEV was small sharp spikes (SSS), observed in 114 patients (3.8%). Wicket waves, 6 Hz spike and slow wave, 14 and 6 Hz positive bursts, and Rhythmic Temporal Theta of Drowsiness (RTTD) were identified in 67 (2.2%), 40 (1.3%), 39 (1.3%), and 35 (1.16%) patients, respectively and one patient with Subclinical Rhythmic EEG Discharges in Adults (SREDA). Additionally, we observed the co-existence of epileptiform discharges with BEVs, most commonly with SSS (27.8%).

CONCLUSIONS

The present study is a large study with 3000 EEGs to describe the BEV characteristics. BEVs were seen in 9.9% of patients, BSSS being the most common. There were minor differences in frequency, gender or age distribution compared to existing literature. We demonstrated the co-existence of epileptiform discharges. Morphological characteristics remain the cornerstone in recognising BEVs. EEG readers need to be aware of features of BEVs to avoid wrongly interpretation.

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.

Normal variants and artifacts: Importance in EEG interpretation

Overinterpretation of EEG is an important contributor to the misdiagnosis of epilepsy. For the EEG to have a high diagnostic value and high specificity, it is critical to recognize waveforms that can be mistaken for abnormal patterns. This article describes artifacts, normal rhythms, and normal patterns that are prone to being misinterpreted as abnormal. Artifacts are potentials generated outside the brain. They are divided into physiologic and extraphysiologic. Physiologic artifacts arise from the body and include EMG, eyes, various movements, EKG, pulse, and sweat. Some physiologic artifacts can be useful for interpretation such as EMG and eye movements. Extraphysiologic artifacts arise from outside the body, and in turn can be divided into the environments (electrodes, equipment, and cellphones) and devices within the body (pacemakers and neurostimulators). Normal rhythms can be divided into awake patterns (alpha rhythm and its variants, mu rhythm, lambda waves, posterior slow waves of youth, HV-induced slowing, photic driving, and photomyogenic response) and sleep patterns (POSTS, vertex waves, spindles, K complexes, sleep-related hypersynchrony, and frontal arousal rhythm). Breach can affect both awake and sleep rhythms. Normal variants or variants of uncertain clinical significance include variants that may have been considered abnormal in the early days of EEG but are now considered normal. These include wicket spikes and wicket rhythms (the most common normal pattern overread as epileptiform), small sharp spikes (aka benign epileptiform transients of sleep), rhythmic midtemporal theta of drowsiness (aka psychomotor variant), Cigánek rhythm (aka midline theta), 6 Hz phantom spike-wave, 14 and 6 Hz positive spikes, subclinical rhythmic epileptiform discharges of adults (SREDA), slow-fused transients, occipital spikes of blindness, and temporal slowing of the elderly. Correctly identifying artifacts and normal patterns can help avoid overinterpretation and misdiagnosis. This is an educational review paper addressing a learning objective of the International League Against Epilepsy (ILAE) curriculum.

Beamforming Seizures from the Temporal Lobe Using Magnetoencephalography

BACKGROUND

Surgical treatment of drug-resistant temporal lobe epilepsy (TLE) depends on proper identification of the seizure onset zone (SOZ) and differentiation of mesial, temporolimbic seizure onsets from temporal neocortical seizure onsets. Noninvasive source imaging using electroencephalography (EEG) and magnetoencephalography (MEG) can provide accurate information on interictal spike localization; however, EEG and MEG have low sensitivity for epileptiform activity restricted to deep temporolimbic structures. Moreover, in mesial temporal lobe epilepsy (MTLE), interictal spikes frequently arise in neocortical foci distant from the SOZ, rendering interictal spike localization potentially misleading for presurgical planning.

METHODS

In this study, we used two different beamformer techniques applied to the MEG signal of ictal events acquired during EEG-MEG recordings in six patients with TLE (three neocortical, three MTLE) in whom the ictal source localization results could be compared to ground truth SOZ localizations determined from intracranial EEG and/or clinical, neuroimaging, and postsurgical outcome evidence.

RESULTS

Beamformer analysis proved to be highly accurate in all cases and was able to identify focal SOZs in mesial, temporolimbic structures. In three patients, interictal spikes were absent, too complex for dipole modeling, or localized to anterolateral temporal neocortex distant to a mesial temporal SOZ, and thus unhelpful in presurgical investigation.

CONCLUSIONS

MEG beamformer source reconstruction is suitable for analysis of ictal events in TLE and can complement or supersede the traditional analysis of interictal spikes. The method outlined is applicable to any type of epileptiform event, expanding the information value of MEG and broadening its utility for presurgical recording in epilepsy.

Magnetoencephalography to confirm epileptiform discharges mimicking small sharp spikes in temporal lobe epilepsy

OBJECTIVE

To determine whether magnetoencephalography (MEG) can identify epileptiform discharges mimicking small sharp spikes (SSSs) on scalp electroencephalography (EEG) in patients with temporal lobe epilepsy (TLE).

METHODS

We retrospectively reviewed simultaneous scalp EEG and MEG recordings of 83 consecutive patients with TLE and 49 with extra-TLE (ETLE).

RESULTS

SSSs in scalp EEG were detected in 15 (18.1%) of 83 TLE patients compared to only two (4.1%) of 49 ETLE patients (p = 0.029). Five of the 15 TLE patients had MEG spikes with concurrent SSSs in EEG, but neither of the 2 ETLE patients. Three of these 5 TLE patients had additional interictal epileptiform discharges (IEDs) in EEG and MEG. Equivalent current dipoles (ECDs) of MEG spikes with concurrent SSSs and IEDs showed no difference in temporal lobe localization and horizontal orientation, whereas ECD moments were smaller in MEG spikes with concurrent SSSs than those with IEDs.

CONCLUSIONS

SSSs were more common in TLE than in ETLE. At least some morphologically diagnosed SSSs are true but low-amplitude epileptiform discharges in TLE which can be identified with simultaneous MEG.

SIGNIFICANCE

Simultaneous MEG is useful to identify epileptiform discharges mimicking SSSs in patients with TLE.

Intracranial correlates of small sharp spikes

OBJECTIVE

To identify cortical correlates of scalp small sharp spikes (SSS) using simultaneous scalp and intracranial EEG recordings.

METHODS

Patients were retrospectively evaluated based on a database of intracranial long-term recordings at the Epilepsy Center Freiburg. Inclusion criteria were: simultaneous recordings with intracranial and scalp EEGs and the presence of at least five unequivocal SSS in the scalp EEG. Intracranial recordings were analyzed regarding the co-occurring intracranial potentials during scalp SSS.

RESULTS

33 patients, aged 9-60y, 17 females, fulfilled the above-mentioned criteria. Almost all patients had intracranial SSS correlates in the form of spike/polyspike-waves in the temporal lobe, predominantly in the hippocampus (24/28), less frequently involving the amygdala (5/29), temporal basal (3/18), lateral neocortical (4/32), entorhinal cortices (1/12), and the parietal lobe (2/13). Amplitudes of intrahippocampal spikes or polyspikes co-occurring with SSS were significantly higher than intracranial discharges without scalp correlates. In 45% of patients, intracranial spikes accompanying SSS were located within the seizure onset zone (SOZ).

CONCLUSIONS

Our results strongly support an epileptic origin of SSS and provide evidence about their heterogenous generators.

SIGNIFICANCE

This study suggests that SSS cannot with certainty be classified as "benign" but rather considered as one of the EEG manifestations of focal epilepsy.

The clinical significance of small sharp spikes: A retrospective study of 909 patients in epilepsy monitoring unit

OBJECTIVES

To determine the incidence and clinical significance of small sharp spikes (SSS) in the patient population of the adult Epilepsy Monitoring Unit (EMU).

METHODS

This is a retrospective study of EEG data and medical records from consecutive patients who underwent video-EEG recording in the adult EMU from March 2013 to February 2019. SSS, interictal epileptiform discharges (IEDs), and ictal patterns were identified.

RESULTS

Of the 909 patients reviewed, SSS were observed in110 (12.1 %) patients. Epilepsy was present in 101 of the 110 (91.8 %) patients with SSS and in 441 of the 799 (55.2 %) patients without SSS. The incidence of epilepsy was significantly higher in patients with SSS than in those without SSS (OR = 9.1, 95 % CI: 4.5-18.3, P < 0.01). The sensitivity of SSS for epilepsy was 18.6 % and the specificity was 97.5 %. The incidence of SSS was strongly correlated with the frequency of IEDs (OR 1.89; 95 %CI: 1.60-2.24, P < 0.01). When both present, SSS and IEDs were co-lateralized in the same hemisphere.

CONCLUSIONS

There is a statistically significant association between SSS and focal epilepsy. SSS have similar clinical implications to IEDs in the lateralization and localization of temporal lobe seizures. SSS can be an epileptiform EEG pattern for temporal lobe epilepsy.