High density scalp EEG in frontal lobe epilepsy

The Fingerprint of Scalp-EEG in Drug-Resistant Frontal Lobe Epilepsies

PURPOSE

Scalp-EEG incompletely covers the frontal lobe cortex. Underrepresentation of frontobasal or frontomesial structures, fast ictal spreading, and false lateralization impede scalp-EEG interpretation. Hence, we investigated the significance of scalp-EEG in the presurgical workup of frontal lobe epilepsy.

METHODS

Using descriptive statistical methods and Pearson chi-squared test for group comparisons, we retrospectively investigated postsurgical outcome, interictal epileptiform discharges (iiEDs), and electrographic seizure patterns on scalp-EEG in 81 consecutive patients undergoing resective epilepsy surgery within the margins of the frontal lobe.

RESULTS

Postoperatively, patients with frontopolar iiEDs (n = 7) or concordant frontopolar iiED focus and seizure-onset (n = 2) were seizure free (n = 7/7, Engel Ia). MRI-positive patients with frontopolar iiEDs or frontopolar seizure-onset (n = 1/8 Engel Id, n = 7/8 Engel Ia) underwent surgery without stereo-EEG. Thirteen of 16 patients with frontolateral (n = 8/10, Engel Ia), or left frontobasal (n = 5/6, Engel Ia) seizure-onset undergoing further stereo-EEG, were seizure-free postoperatively. Seizure-onset prevalent over one electrode (n = 37/44 Engel I, p = 0.02), fast activity (FA)/flattening at seizure-onset (n = 29/33 Engel I, p = 0.02), FA/flattening during the seizure (n = 38/46 Engel I, p = 0.05), or focal rhythmic sharp-/spike-/polyspike-and-slow waves during the seizure (n = 24/31, Engel Ia, p = 0.05) were favorable prognostic markers. Interictal polyspike waves (p = 0.006 for Engel Ia) and interictal paroxysmal FA (p = 0.02 for Engel I) were unfavorable prognostic markers.

CONCLUSIONS

Frontopolar scalp-EEG findings serve as biomarkers for predicting favorable surgical outcome in lesional frontal lobe epilepsy. Consequently, careful analysis of scalp-EEG assists in bypassing stereo-EEG in these patients.

Normative brain mapping using scalp EEG and potential clinical application

A normative electrographic activity map could be a powerful resource to understand normal brain function and identify abnormal activity. Here, we present a normative brain map using scalp EEG in terms of relative band power. In this exploratory study we investigate its temporal stability, its similarity to other imaging modalities, and explore a potential clinical application. We constructed scalp EEG normative maps of brain dynamics from 17 healthy controls using source-localised resting-state scalp recordings. We then correlated these maps with those acquired from MEG and intracranial EEG to investigate their similarity. Lastly, we use the normative maps to lateralise abnormal regions in epilepsy. Spatial patterns of band powers were broadly consistent with previous literature and stable across recordings. Scalp EEG normative maps were most similar to other modalities in the alpha band, and relatively similar across most bands. Towards a clinical application in epilepsy, we found abnormal temporal regions ipsilateral to the epileptogenic hemisphere. Scalp EEG relative band power normative maps are spatially stable across time, in keeping with MEG and intracranial EEG results. Normative mapping is feasible and may be potentially clinically useful in epilepsy. Future studies with larger sample sizes and high-density EEG are now required for validation.

Stereo-EEG localization of midline onset seizures on scalp EEG

PURPOSE

The objective of this study was to describe the sEEG-defined seizure onset zone (SOZ), seizure semiology, presurgical evaluations, surgical intervention and outcome in patients with midline onset noninvasive phase I monitoring.

METHODS

A single center sEEG database was reviewed to identify patients with seizures onset predominantly involving midline electrodes (FZ, CZ, PZ, OZ) on scalp EEG. Data abstracted included clinical factors, seizure semiology graded into lobar segmentation, imaging and electrographic findings, sEEG plan, interventions, and outcome.

RESULTS

Twelve patients were identified (8 males, median age of sEEG 28 years) out of 100 cases of sEEG performed from January 2015-September 2019. "Frontal lobe" seizure semiology was the most common. sEEG-defined SOZ were frontal (5), diffuse (1), multifocal (1), frontal and insular (1), frontal and cingulate (1), insular (1), cingulate (1), and mesial temporal (1). CZ and/or FZ scalp EEG changes were present for all patients with SOZ involving the frontal, cingulate, and insular regions. PZ/OZ scalp involvement was present in one patient with mesial temporal SOZ. Four patients underwent a definitive resective or ablative surgery, and the remaining patients underwent a palliative intervention. Of those with follow-up information available, 8/11 had seizure reduction by ≥ 50%, including 4 with an Engel I outcome. No clinical factors were associated with outcome.

CONCLUSIONS

SOZ for midline onset seizures from noninvasive phase I monitoring was most commonly in the frontal, cingulate, and insular regions. A complex cortical network between these regions may explain overlap in semiology and scalp EEG findings. While the number rendered seizure-free was limited, a significant proportion experienced a reasonably favorable outcome justifying use of sEEG to identify surgical options in these patients.

Optimized EEG based mood detection with signal processing and deep neural networks for brain-computer interface

Electroencephalogram (EEG) is a very promising and widely implemented procedure to study brain signals and activities by amplifying and measuring the post-synaptical potential arising from electrical impulses produced by neurons and detected by specialized electrodes attached to specific points in the scalp. It can be studied for detecting brain abnormalities, headaches, and other conditions. However, there are limited studies performed to establish a smart decision-making model to identify EEG's relation with the mood of the subject. In this experiment, EEG signals of 28 healthy human subjects have been observed with consent and attempts have been made to study and recognise moods. Savitzky-Golay band-pass filtering and Independent Component Analysis have been used for data filtration.Different neural network algorithms have been implemented to analyze and classify the EEG data based on the mood of the subject. The model is further optimised by the usage of Blackman window-based Fourier Transformation and extracting the most significant frequencies for each electrode. Using these techniques, up to 96.01% detection accuracy has been obtained.

Deep phenotyping of frontal lobe epilepsy compared to other epilepsy syndromes

AIMS

Frontal lobe epilepsy (FLE) is understudied and often misdiagnosed. We sought to comprehensively phenotype FLE and to differentiate FLE from other focal and generalised epilepsy syndromes.

METHODS

This was a retrospective, observational cohort study of 1078 cases of confirmed epilepsy in a tertiary neurology centre in London. Data sources were electronic health records, investigation reports and clinical letters.

RESULTS

166 patients had FLE based on clinical findings and investigations-97 with identifiable electroencephalography (EEG) foci in frontal areas (definite FLE), while 69 had no frontal EEG foci (probable FLE). Apart from EEG findings, probable and definite FLE did not differ in other features. FLE was distinct from generalized epilepsy, which tended to present with tonic-clonic seizures and be due to genetic causes. FLE and temporal lobe epilepsy (TLE) both featured focal unaware seizures and underlying structural or metabolic aetiology. FLE, TLE and generalized epilepsy differed in their EEG (P = 0.0003) and MRI (P = 0.002) findings, where FLE had a higher rate of normal EEG and abnormal MRI findings compared to TLE.

CONCLUSIONS

EEG is often normal for FLE, and abnormalities are commonly identified with MRI. There was no difference in the clinical features of definite and probable FLE, suggesting they represent the same clinical entity. The diagnosis of FLE can be made even when scalp EEG is normal. This large medical cohort provides hallmark features of FLE that differentiate it from TLE and other epilepsy syndromes.

Central-positive complexes in ECT-induced seizures: Possible evidence for thalamocortical mechanisms

OBJECTIVE

Central-positive complexes (CPCs) are elicited during electroconvulsive therapy (ECT) as generalized high-amplitude waveforms with maximum positive voltage over the vertex. While these complexes have been qualitatively assessed in previous literature, quantitative analyses are lacking. This study aims to characterize CPCs across temporal, spatial, and spectral domains.

METHODS

High-density 64-electrode electroencephalogram (EEG) recordings during 50 seizures acquired from 11 patients undergoing right unilateral ECT allowed for evaluation of spatiotemporal characteristics of CPCs via source localization and spectral analysis.

RESULTS

Peak-amplitude CPC scalp topology was consistent across seizures, showing maximal positive polarity over the midline fronto-central region and maximal negative polarity over the suborbital regions. The sources of these peak potentials were localized to the bilateral medial thalamus and cingulate cortical regions. Delta, beta, and gamma oscillations were correlated with the peak amplitude of CPCs during seizures induced during ketamine, whereas delta and gamma oscillations were associated with CPC peaks during etomidate anesthesia (excluding the dose-charge titration).

CONCLUSIONS

Our findings demonstrate the consistency of CPC presence across participant, stimulus charge, time, and anesthetic agent, with peaks localized to bilateral medial thalamus and cingulate cortical regions and associated with delta, beta, and gamma band oscillations (depending on the anesthetic condition).

SIGNIFICANCE

The consistency and reproducibility of CPCs offers ECT as a new avenue for studying the dynamics of generalized seizure activity and thalamocortical networks.

Evaluation of the Patient With Paroxysmal Spells Mimicking Epileptic Seizures

BACKGROUND

The diagnostic issue of paroxysmal spells, including epileptic seizure (ES) mimics, is one that neurologists frequently encounter. This review provides an up-to-date overview of the most common causes of ES mimics encountered in the outpatient setting.

REVIEW SUMMARY

Paroxysmal spells are characterized by changes in awareness, attention, perception, or abnormal movements. These can be broadly classified as ES and nonepileptic spells (NES). NES mimics ES but are distinguished by their symptomatology and lack of epileptiform activity on electroencephalography. NES may have psychological or physiological underpinnings. Psychogenic non-ES are the most common mimics of ES. Physiological causes of NES include syncope, cerebrovascular, movement, and sleep-related disorders.

CONCLUSIONS

Distinguishing NES from ES at times may be challenging even to the most experienced clinicians. However, detailed history with an emphasis on the clinical clues, including taking a moment-by-moment history of the event from the patient and observers and physical examination, helps create an appropriate differential diagnosis to guide further diagnostic testing. An accurate diagnosis of NES prevents iatrogenic harm, including unnecessary exposure to antiseizure medications and overuse of health care resources. It also allows for the correct specialist referral and appropriate treatment.

Improving the prediction of epilepsy surgery outcomes using basic scalp EEG findings

OBJECTIVE

This study aims to evaluate the role of scalp electroencephalography (EEG; ictal and interictal patterns) in predicting resective epilepsy surgery outcomes. We use the data to further develop a nomogram to predict seizure freedom.

METHODS

We retrospectively reviewed the scalp EEG findings and clinical data of patients who underwent surgical resection at three epilepsy centers. Using both EEG and clinical variables categorized into 13 isolated candidate predictors and 6 interaction terms, we built a multivariable Cox proportional hazards model to predict seizure freedom 2 years after surgery. Harrell's step-down procedure was used to sequentially eliminate the least-informative variables from the model until the change in the concordance index (c-index) with variable removal was less than 0.01. We created a separate model using only clinical variables. Discrimination of the two models was compared to evaluate the role of scalp EEG in seizure-freedom prediction.

RESULTS

Four hundred seventy patient records were analyzed. Following internal validation, the full Clinical + EEG model achieved an optimism-corrected c-index of 0.65, whereas the c-index of the model without EEG data was 0.59. The presence of focal to bilateral tonic-clonic seizures (FBTCS), high preoperative seizure frequency, absence of hippocampal sclerosis, and presence of nonlocalizable seizures predicted worse outcome. The presence of FBTCS had the largest impact for predicting outcome. The analysis of the models' interactions showed that in patients with unilateral interictal epileptiform discharges (IEDs), temporal lobe surgery cases had a better outcome. In cases with bilateral IEDs, abnormal magnetic resonance imaging (MRI) predicted worse outcomes, and in cases without IEDs, patients with extratemporal epilepsy and abnormal MRI had better outcomes.

SIGNIFICANCE

This study highlights the value of scalp EEG, particularly the significance of IEDs, in predicting surgical outcome. The nomogram delivers an individualized prediction of postoperative outcome, and provides a unique assessment of the relationship between the outcome and preoperative findings.

Presurgical Evaluation of Epilepsy Using Resting-State MEG Functional Connectivity

Epilepsy is caused by abnormal electrical discharges (clinically identified by electrophysiological recording) in a specific part of the brain [originating in only one part of the brain, namely, the epileptogenic zone (EZ)]. Epilepsy is now defined as an archetypical hyperexcited neural network disorder. It can be investigated through the network analysis of interictal discharges, ictal discharges, and resting-state functional connectivity. Currently, there is an increasing interest in embedding resting-state connectivity analysis into the preoperative evaluation of epilepsy. Among the various neuroimaging technologies employed to achieve brain functional networks, magnetoencephalography (MEG) with the excellent temporal resolution is an ideal tool for estimating the resting-state connectivity between brain regions, which can reveal network abnormalities in epilepsy. What value does MEG resting-state functional connectivity offer for epileptic presurgical evaluation? Regarding this topic, this paper introduced the origin of MEG and the workflow of constructing source-space functional connectivity based on MEG signals. Resting-state functional connectivity abnormalities correlate with epileptogenic networks, which are defined by the brain regions involved in the production and propagation of epileptic activities. This paper reviewed the evidence of altered epileptic connectivity based on low- or high-frequency oscillations (HFOs) and the evidence of the advantage of using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. More importantly, this review highlighted that MEG-based resting-state functional connectivity has the potential to predict postsurgical outcomes. In conclusion, resting-state MEG functional connectivity has made a substantial progress toward serving as a candidate biomarker included in epileptic presurgical evaluations.

Quantitative spatio-temporal characterization of epileptic spikes using high density EEG: Differences between NREM sleep and REM sleep

In this study, we applied high-density EEG recordings (HD-EEG) to quantitatively characterize the fine-grained spatiotemporal distribution of inter-ictal epileptiform discharges (IEDs) across different sleep stages. We quantified differences in spatial extent and duration of IEDs at the scalp and cortical levels using HD-EEG source-localization, during non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep, in six medication-refractory focal epilepsy patients during epilepsy monitoring unit admission. Statistical analyses were performed at single subject level and group level across different sleep stages for duration and distribution of IEDs. Tests were corrected for multiple comparisons across all channels and time points. Compared to NREM sleep, IEDs during REM sleep were of significantly shorter duration and spatially more restricted. Compared to NREM sleep, IEDs location in REM sleep also showed a higher concordance with electrographic ictal onset zone from scalp EEG recording. This study supports the localizing value of REM IEDs over NREM IEDs and suggests that HD-EEG may be of clinical utility in epilepsy surgery work-up.

PET and ictal SPECT can be helpful for localizing epileptic foci

Purpose of review

Functional neuroimaging with PET and SPECT is a commonly used tool in presurgical evaluation. The following article reviews the literature of PET and SPECT in presurgical assessment of epilepsies published in the last year.

Recent findings

FDG-PET adds concomitant information in temporal and extratemporal lobe epilepsy in adults and children. The pattern of hypometabolism in FDG-PET is a good additional predictor or seizure outcome in TLE with mesial temporal sclerosis or negative MRI. There is growing evidence that diagnostic value of FDG-PET increases with postprocessing. Although several methods were applied in the reviewed literature, all of them seem to outperform the visual analysis. Imaging of the epileptic focus with ictal SPECT is depending on short injection latencies. It is particularly useful in patients with nonlesional MRI and mostly of extratemporal localization. Areas of hyperperfusion remote of SOZ are reflecting the epileptic network. Combining more concordant investigations including PET and SPECT in MRI-negative evaluation adds to better presurgical stratification and therefore, better postsurgical outcome. FET-PET shows increased uptake in status epilepticus.

Summary

PET and SPECT are important investigations to localize the epileptic focus in temporal lobe and nonlesional extratemporal epilepsies. Postprocessing for both modalities is important to increase diagnostic value.

Adult EEG

After more than 85 years of development and use in clinical practice, the electroencephalogram (EEG) remains a dependable, inexpensive, and useful diagnostic tool for the investigation of the electrophysiologic activity of the brain. The advent of digital technology has led to greater sophistication and multiple software applications to extend the utility of EEG beyond the confines of the laboratory. Despite the discovery of new waveforms, basic neurophysiologic principles remain essential to the clinical care of patients. Patterns in the interictal EEG make it possible to clarify the differential diagnosis of paroxysmal neurological events, classify seizure type and epilepsy syndromes, and characterize and quantify seizures when ictal recordings are obtained. EEG can also demonstrate cerebral dysfunction when structural imaging is normal to detect focal or lateralized abnormalities in patients with encephalopathy. High-density EEG with electrical source imaging has improved localization in candidates for epilepsy surgery. Quantitative EEG and broadband EEG are advancing our understanding of the functional processes of the brain itself.