Basic Principles of Electroencephalogram

Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges (IEDs). Clinical MEG analysis in epileptic patients traditionally relies on the visual identification of IEDs, which is time consuming and partially subjective. Automatic, data-driven detection methods exist but show limited performance. Still, the rise of deep learning (DL)—with its ability to reproduce human-like abilities—could revolutionize clinical MEG practice. Here, we developed and validated STIED, a simple yet powerful supervised DL algorithm combining two convolutional neural networks with temporal (1D time-course) and spatial (2D topography) features of MEG signals inspired from current clinical guidelines. Our DL model enabled a successful identification of IEDs in patients suffering from focal epilepsy with frequent and high amplitude spikes (FE group), with high-performance metrics—accuracy, specificity, and sensitivity all exceeding 85%—when learning from spatiotemporal features of IEDs. This performance can be attributed to our handling of input data, which mimics established clinical MEG practice. Reverse engineering further revealed that STIED encodes fine spatiotemporal features of IEDs rather than their mere amplitude. The model trained on the FE group also showed promising results when applied to a separate group of presurgical patients with different types of refractory focal epilepsy, though further work is needed to distinguish IEDs from physiological transients. This proof-of-concept study represents a first step towards the use of STIED and DL algorithms in the routine clinical MEG evaluation of epilepsy.

Concurrent continuous EEG-fMRI is a novel multimodal technique that is finding its way into clinical practice in epilepsy. EEG timeseries are used to identify the timing of interictal epileptiform discharges (IEDs) which is then included in a GLM analysis in fMRI to localize the epileptic onset zone. Nevertheless, there are still some concerns about its reliability concerning BOLD changes correlated with IEDs. Even though IEDs are identified by an experienced neurologist-epiliptologist, the reliability and concordance of the mark-ups is depending on many factors including the level of fatigue, the amount of time that he spent or, in some cases, even the screen that is being used for the display of timeseries. This investigation is aiming to unravel the effect of misidentification or inaccuracy in the mark-ups of IEDs in the fMRI statistical parametric maps. Concurrent EEG-fMRI was conducted in six subjects with various types of epilepsy. IEDs were identified by an experienced neurologist-epiliptologist. Analysis of EEG was performed with EEGLAB and analysis of fMRI was conducted in FSL. Preliminary results revealed lower statistical significance for missing events or larger period of IEDs than the actual ones and the introduction of false positives and false negatives in statistical parametric maps when random events were included in the GLM on top of the IEDs. Our results suggest that mark-ups in EEG for simultaneous EEG-fMRI should be done with caution from an experienced and restful neurologist as it affects the fMRI results in various and unpredicted ways.

Background: In contrast to many neuroimaging modalities, clinical interpretation of EEG does not take advantage of post-processing and digital signal analysis. In most centers, EEG is still interpreted at sensor level, exactly as half a century ago. A major task in clinical EEG interpretation is the identification of interictal epileptiform discharges (IEDs). However, due to the overlap of background activity, IEDs can be hard to detect in the scalp EEG. Since traditional montages, like bipolar and average reference, are linear transformations of the recorded channels, the question is whether we can provide linear transformations of the digital EEG to take it back into the brain, at least on a macroscopic level. The goal is to improve visibility of epileptiform activities and to separate out most of the overlap.Methods: Multiple discrete sources provide a stable linear inverse to transform the EEG into source space with little cross-talk between source regions. The model can be based on a few dipoles or regional sources, adapted to the individual EEG and MRI data, or on selected standard sources evenly distributed throughout the brain, e.g. below the 25 EEG standard electrodes.Results: Auditory and somatosensory evoked potentials serve as teaching examples to show how various source spaces can reveal the underlying source components including their loss or alteration due to lesions. Source spaces were able to reveal the propagation of source activities in frontal IEDs and the sequential activation of the major nodes of the underlying epileptic network in myoclonic epilepsy. The power of multiple discrete sources in separating the activities of different brain regions was also evident in the ongoing EEG of cases with frontal cortical dysplasia and bitemporal lobe epilepsy. The new source space 25 made IEDs more clearly visible over the EEG background signals. The more focal nature of source vs. scalp space was quantitatively confirmed using a new measurement of focality.Conclusion: Multiple discrete sources have the power to transform the EEG back into the brain by defining new EEG traces in source space. Using standard source space 25, these can provide for improved clinical interpretation of EEG.

Unique place of ambulatory EEG (aEEG) in management of epilepsy.

Source localization of small sharp spikes: Low resolution electromagnetic tomography (LORETA) reveals two distinct cortical sources

P1-3-10. Effect of hyperventilation on seizures and EEG findings during routine EEG

Clinical Neurophysiology: EEG–Video Monitoring

Electroencephalographic Cerebral Dysrhythmic Abnormalities in the Trinity of Nonepileptic General Population, Neuropsychiatric, and Neurobehavioral Disorders

SYNGAP1 haploinsufficiency results in a developmental and epileptic encephalopathy (DEE) causing generalized epilepsies accompanied by a spectrum of neurodevelopmental symptoms. Concerning interictal epileptiform discharges (IEDs) in electroencephalograms (EEG), potential biomarkers have been postulated, including changes in background activity, fixation-off sensitivity (FOS) or eye closure sensitivity (ECS). In this study we clinically evaluate a new cohort of 36 SYNGAP1-DEE individuals. Standardized questionnaires were employed to collect clinical, electroencephalographic and genetic data. We investigated electroencephalographic findings, focusing on the cortical distribution of interictal abnormalities and their changes with age. Among the 36 SYNGAP1-DEE cases 18 presented variants in the SYNGAP1 gene that had never been previously reported. The mean age of diagnosis was 8 years and 8 months, ranging from 2 to 17years, with 55.9% being male. All subjects had global neurodevelopmental/language delay and behavioral abnormalities; 83.3% had moderate to profound intellectual disability (ID), 91.7% displayed autistic traits, 73% experienced sleep disorders and 86.1% suffered from epileptic seizures, mainly eyelid myoclonia with absences (55.3%). A total of 63 VEEGs were revised, observing a worsening of certain EEG findings with increasing age. A disorganized background was observed in all age ranges, yet this was more common among older cases. The main IEDs were bilateral synchronous and asynchronous posterior discharges, accounting for ≥50% in all age ranges. Generalized alterations with maximum amplitude in the anterior region showed as the second most frequent IED (≥15% in all age ranges) and were also more common with increasing age. Finally, diffuse fast activity was much more prevalent in cases with 6years or older. To the best of our knowledge, this is the first study to analyze EEG features across different age groups, revealing an increase in interictal abnormalities over infancy and adolescence. Our findings suggest that SYNGAP1 haploinsufficiency has complex effects in human brain development, some of which might unravel at different developmental stages. Furthermore, they highlight the potential of baseline EEG to identify candidate biomarkers and the importance of natural history studies to develop specialized therapies and clinical trials.

A comparison is made between the results of standard intracarotid speech amytal testing and a new methodology, echoplanar blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI), in patients undergoing presurgical evaluation for intractable epilepsy. Of the 15 patients entered in the study, all had fMRIs while performing a verbal fluency task. Twelve of these patients also underwent standard intracarotid sodium amytal testing for speech and memory. Results of the fMRIs as compared to the intracarotid speech amytal testing are discussed, including agreement and disagreement between studies. Potential reasons for poor concordance are discussed, including complexity of the verbal fluency task, and motion and technical issues in MRI scan acquisition and data analysis.

EEG–fMRI validation studies in comparison with icEEG: A review

Purpose. To evaluate the congruence or discrepancy of the localization of magnetic resonance imaging (MRI) lesions with interictal epileptiform discharges (IEDs) or epileptic seizure patterns (ESPs) in surface EEG in lesional pediatric epilepsy patients. Methods. We retrospectively analyzed presurgical MRI and video-EEG monitoring findings of patients up to age 18 years. Localization of MRI lesions were compared with ictal and interictal noninvasive EEG findings of patients with frontal, temporal, parietal, or occipital lesions. Results. A total of 71 patients were included. Localization of ESPs showed better congruence with MRI in patients with frontal lesions (n = 21, 77.5%) than in patients with temporal lesions (n = 24; 40.7%) (P = .009). No significant IED distribution differences between MRI localizations could be found. Conclusions. MRI lesions and EEG findings are rarely fully congruent. Congruence of MRI lesions and ESPs was highest in children with frontal lesions. This is in contrast to adults, in whom temporal lesions showed the highest congruency with the EEG localization of ESP. Lesional pediatric patients should be acknowledged as surgical candidates despite incongruent findings of interictal and ictal surface EEG.

Intra-operative electrocorticography (ECoG) has been traditionally used in the surgical management of medically refractory partial epilepsies to identify the limits of the epileptogenic zone. This retrospective study had as goal to evaluate whether tailored surgery based on the presurgical evaluation completed by intra-operative post-resection ECoG improves outcome. We reviewed 94 cases of epilepsy surgery with intra-operative ECoG and determined how many had an ECoG-guided surgical procedure in addition to the initial planned surgery. We also reviewed the presence of specific recurrent ECoG patterns of interictal epileptiform discharges (IED) in the exposed cortical surface, such as: electrographic seizures, bursts, intermittent spike waves, polyspikes or fast rhythms and continuous or quasi-continuous spiking. When performing a post-resection ECoG-tailored surgery, outcome did not improve in lesional or non-lesional epilepsy. Postoperative residual IED did not correlate with a poorer outcome. In our study, the persistence of post-resection IED on ECoG is not correlated with outcome in patients with lesional or non-lesional epilepsy.

In this issue, Gilbert et al1 have provided some new insights into the utility of sleep deprivation before recording of electroencephalograms (EEGs), to increase the likelihood of identification of interictal epileptiform discharges. A design flaw, which makes the results less universally applicable, is that the subjects and referring physicians both represented heterogeneous groups. The subjects included children who were known epileptics, patients with initial seizures, children with and without antiepileptic drug treatment, and children with a variety of other presenting complaints. The referring physicians were specialists and generalists treating differing populations. Nevertheless, by comparing 2 time periods during which subjects underwent EEG recording with a standard sleep deprivation protocol or a non–sleep-deprivation protocol, the authors were able to establish a large enough sample size to provide some important results. Of the 820 eligible subjects who underwent EEG recordings during …

Measuring neuro-haemodynamic correlates in the brain of epilepsy patients using EEG-fMRI has opened new avenues in clinical neuroscience, as these are two complementary methods for understanding brain function. In this study, we investigated three patients with drug-resistant reflex epilepsy using EEG-fMRI. Different types of reflex epilepsy such as eating, startle myoclonus, and hot water epilepsy were included in the study. The analysis of EEG-fMRI data was based on the visual identification of interictal epileptiform discharges on scalp EEG. The convolution of onset time and duration of these epilepsy spikes was estimated, and using these condition-specific effects in a general linear model approach, we evaluated activation of fMRI. Patients with startle myoclonus epilepsy experienced epilepsy in response to sudden sound or touch, in association with increased delta and theta activity with a spike-and-slow-wave pattern of interictal epileptiform discharges on EEG and fronto-parietal network activation pattern on SPECT and EEG-fMRI. Eating epilepsy was triggered by sight or smell of food and fronto-temporal discharges were noted on video-EEG (VEEG). Similarly, fronto-temporo-parietal involvement was noted on SPECT and EEG-fMRI. Hot water epilepsy was triggered by contact with hot water either in the bath or by hand immersion, and VEEG showed fronto-parietal involvement. SPECT and EEG fMRI revealed a similar fronto-parietal-occipital involvement. From these results, we conclude that continuous EEG recording can improve the modelling of BOLD changes related to interictal epileptic activity and this can thus be used to understand the neuro-haemodynamic substrates involved in reflex epilepsy.