Nicolas Roehri

Time-Frequency Strategies for Increasing High-Frequency Oscillation Detectability in Intracerebral EEG

Background: High-frequency oscillations (HFOs) are considered to be highly representative of brain tissues capable of producing epileptic seizures. The visual review of HFOs on intracerebral electroencephalography is time consuming and tedious, and it can be improved by time-frequency (TF) analysis. The main issue is that the signal is dominated by lower frequencies that mask the HFOs. Our aim was to flatten (i.e., whiten) the frequency spectrum to enhance the fast oscillations while preserving an optimal signal to noise ratio (SNR). Method: We investigated eight methods of data whitening based on either prewhitening or TF normalization in order to improve the detectability of HFOs. We detected all local maxima of the TF image above a range of thresholds in the HFO band. Results: We obtained the precision and recall curves at different SNR and for different HFO types and illustrate the added value of whitening both in the TF plane and in time domain. Conclusion: The normalization strategies based on a baseline and on our proposed method (the “H0 z-score”) are more precise than the others. Significance: The H0 z-score provides an optimal framework for representing and detecting HFOs, independent of a baseline and a priori frequency bands.

What are the assets and weaknesses of HFO detectors? A benchmark framework based on realistic simulations

High-frequency oscillations (HFO) have been suggested as biomarkers of epileptic tissues. While visual marking of these short and small oscillations is tedious and time-consuming, automatic HFO detectors have not yet met a large consensus. Even though detectors have been shown to perform well when validated against visual marking, the large number of false detections due to their lack of robustness hinder their clinical application. In this study, we developed a validation framework based on realistic and controlled simulations to quantify precisely the assets and weaknesses of current detectors. We constructed a dictionary of synthesized elements—HFOs and epileptic spikes—from different patients and brain areas by extracting these elements from the original data using discrete wavelet transform coefficients. These elements were then added to their corresponding simulated background activity (preserving patient- and region- specific spectra). We tested five existing detectors against this benchmark. Compared to other studies confronting detectors, we did not only ranked them according their performance but we investigated the reasons leading to these results. Our simulations, thanks to their realism and their variability, enabled us to highlight unreported issues of current detectors: (1) the lack of robust estimation of the background activity, (2) the underestimated impact of the 1/f spectrum, and (3) the inadequate criteria defining an HFO. We believe that our benchmark framework could be a valuable tool to translate HFOs into a clinical environment.

High‐frequency oscillations are not better biomarkers of epileptogenic tissues than spikes

High‐frequency oscillations (HFOs) in intracerebral EEG (stereoelectroencephalography; SEEG) are considered as better biomarkers of epileptogenic tissues than spikes. How this can be applied at the patient level remains poorly understood. We investigated how well HFOs and spikes can predict epileptogenic regions with a large spatial sampling at the patient level.

Brain regions and epileptogenicity influence epileptic interictal spike production and propagation during NREM sleep in comparison with wakefulness

Non–rapid eye movement (NREM) sleep is known to be a brain state associated with an activation of interictal epileptic activity. The goal of this work was to quantify topographic changes occurring during NREM sleep in comparison with wakefulness.

Epileptogenic networks in nodular heterotopia: A stereoelectroencephalography study

Defining the roles of heterotopic and normotopic cortex in the epileptogenic networks in patients with nodular heterotopia is challenging. To elucidate this issue, we compared heterotopic and normotopic cortex using quantitative signal analysis on stereoelectroencephalography (SEEG) recordings.

Early onset motor semiology in seizures triggered by cortical stimulation during SEEG

OBJECTIVES The objective of the study was to describe electroclinical patterns in habitual seizures with motor semiology at onset, triggered by diagnostic stimulation, in patients undergoing presurgical evaluation using stereoelectroencephalography (SEEG). METHODS Seizure semiology, stimulation parameters, electroclinical data, and anatomical localization were evaluated in stimulated and spontaneous seizures. RESULTS From 120 habitual seizures triggered by 50-Hz train bipolar stimulation during SEEG, 20 presented initial motor semiology (elementary motor signs, complex motor behavior, or both). Two patterns occurred: long latency onset (7/20), where semiology occurred after the stimulation train, following visible cortical epileptic discharge similarly to spontaneous seizures; and short latency onset (13/20), in which typical semiological expression occurred during the stimulation train, preceding typical cortical discharge. CONCLUSIONS This novel observation shows that in some conditions, seizures with habitual motor semiology could be triggered early during stimulation, before typical cortical epileptic discharge became visible. The earliness of clinical onset with regard to visible cortical discharge, notably in comparison with clinically similar spontaneous seizures, suggests differences in electrophysiological mechanisms that require further investigation. These may involve preferential involvement of descending corticosubcortical connections within the same epileptogenic network for a given patient.

Interictal stereotactic-EEG functional connectivity in refractory focal epilepsies

Drug-refractory focal epilepsies are network diseases associated with functional connectivity alterations both during ictal and interictal periods. A large majority of studies on the interictal/resting state have focused on functional MRI-based functional connectivity. Few studies have used electrophysiology, despite its high temporal capacities. In particular, stereotactic-EEG is highly suitable to study functional connectivity because it permits direct intracranial electrophysiological recordings with relative large-scale sampling. Most previous studies in stereotactic-EEG have been directed towards temporal lobe epilepsy, which does not represent the whole spectrum of drug-refractory epilepsies. The present study aims at filling this gap, investigating interictal functional connectivity alterations behind cortical epileptic organization and its association with post-surgical prognosis. To this purpose, we studied a large cohort of 59 patients with malformation of cortical development explored by stereotactic-EEG with a wide spatial sampling (76 distinct brain areas were recorded, median of 13.2 per patient). We computed functional connectivity using non-linear correlation. We focused on three zones defined by stereotactic-EEG ictal activity: the epileptogenic zone, the propagation zone and the non-involved zone. First, we compared within-zone and between-zones functional connectivity. Second, we analysed the directionality of functional connectivity between these zones. Third, we measured the associations between functional connectivity measures and clinical variables, especially post-surgical prognosis. Our study confirms that functional connectivity differs according to the zone under investigation. We found: (i) a gradual decrease of the within-zone functional connectivity with higher values for epileptogenic zone and propagation zone, and lower for non-involved zones; (ii) preferential coupling between structures of the epileptogenic zone; (iii) preferential coupling between epileptogenic zone and propagation zone; and (iv) poorer post-surgical outcome in patients with higher functional connectivity of non-involved zone (within- non-involved zone, between non-involved zone and propagation zone functional connectivity). Our work suggests that, even during the interictal state, functional connectivity is reinforced within epileptic cortices (epileptogenic zone and propagation zone) with a gradual organization. Moreover, larger functional connectivity alterations, suggesting more diffuse disease, are associated with poorer post-surgical prognosis. This is consistent with computational studies suggesting that connectivity is crucial in order to model the spatiotemporal dynamics of seizures.10.1093/brain/awy214_video1awy214media15833456182001.

Reply to “Are spikes non‐inferior to high‐frequency oscillations?” by S. Weiss and M. Sperling

High frequency oscillations (HFOs) are considered a promising neurophysiological biomarker of epileptogenic activity. Recently, Roehri and colleagues reported results of a retrospective study of diagnostic accuracy that utilized a receiver operating characteristic (ROC) approach to determine if HFO and spike rates can delineate the seizure onset zone. In a tour de force of automated intracranial electroencephalography (EEG) analysis, the study specifically quantified the sensitivity, specificity, and area under the receiver operating curve (AUC) for spikes, ripples, and fast ripples for delineating a surrogate of the seizure-onset zone, called the epileptogenicity index. The authors conclude that, because the partial AUC is not always larger for HFOs as compared with spikes, HFOs are not superior to spikes for predicting epileptogenicity. The authors also conclude that fast ripples are not sensitive enough to be unique biomarkers of epilepsy. In light of the findings reported by Roehri and colleagues, it is important to refocus inquiries into the clinical relevance of high-frequency oscillations. Clinicians rely primarily on the visual inspection of intracranial EEG to delineate epileptogenic sites. Sometimes intraoperative recordings lasting only several minutes are utilized. Even a single instance of an HFO may be used for clinical decision making. In several past studies, a single fast ripple in an unresected electrode site has shown superior predictive value for poor postoperative surgical outcome. Roehri and colleagues also demonstrate that fast ripples have a superior specificity for the seizure onset zone. If a clinician identifies a fast ripple, should he or she now conclude that its significance is identical to a spike? HFO biomarker sensitivity, as defined by Roehri and colleagues, also requires further consideration. Roehri and colleagues compared the spatial distribution of electrode sites with elevated HFO rates with the sites exhibiting an increased epileptogenecity index. The epileptogenecity index is defined by EEG features observed at seizure onset and early spread. Attributed to spatial sampling limitations and volume conduction, it is unknown if all the electrode sites with an elevated epileptogenicity index are capable of independently generating a seizure. If HFOs are generated exclusively by epileptogenic tissue, and the epileptogenic index is elevated in regions besides epileptogenic tissue, then HFO sensitivity for the epileptogenic index would be decreased, but would not reflect a failure of HFOs to delineate epileptogenic regions. We look forward to future studies following STAR-D criteria that examine postoperative seizure outcomes in order to reassess this important topic in epilepsy surgery research. Potential Conflicts of Interest Dr Weiss is the founder of Fastwave LLC, an EEG software manufacturer, and, in addition, Dr Weiss has a patent 14507432 pending, a patent 62297202 pending, and a patent PCT/US17/64509 pending.

Reply to “are spikes noninferior to high‐frequency oscillations?”

High frequency oscillations (HFOs) are considered a promising neurophysiological biomarker of epileptogenic activity. Recently, Roehri and colleagues reported results of a retrospective study of diagnostic accuracy that utilized a receiver operating characteristic (ROC) approach to determine if HFO and spike rates can delineate the seizure onset zone. In a tour de force of automated intracranial electroencephalography (EEG) analysis, the study specifically quantified the sensitivity, specificity, and area under the receiver operating curve (AUC) for spikes, ripples, and fast ripples for delineating a surrogate of the seizure-onset zone, called the epileptogenicity index. The authors conclude that, because the partial AUC is not always larger for HFOs as compared with spikes, HFOs are not superior to spikes for predicting epileptogenicity. The authors also conclude that fast ripples are not sensitive enough to be unique biomarkers of epilepsy. In light of the findings reported by Roehri and colleagues, it is important to refocus inquiries into the clinical relevance of high-frequency oscillations. Clinicians rely primarily on the visual inspection of intracranial EEG to delineate epileptogenic sites. Sometimes intraoperative recordings lasting only several minutes are utilized. Even a single instance of an HFO may be used for clinical decision making. In several past studies, a single fast ripple in an unresected electrode site has shown superior predictive value for poor postoperative surgical outcome. Roehri and colleagues also demonstrate that fast ripples have a superior specificity for the seizure onset zone. If a clinician identifies a fast ripple, should he or she now conclude that its significance is identical to a spike? HFO biomarker sensitivity, as defined by Roehri and colleagues, also requires further consideration. Roehri and colleagues compared the spatial distribution of electrode sites with elevated HFO rates with the sites exhibiting an increased epileptogenecity index. The epileptogenecity index is defined by EEG features observed at seizure onset and early spread. Attributed to spatial sampling limitations and volume conduction, it is unknown if all the electrode sites with an elevated epileptogenicity index are capable of independently generating a seizure. If HFOs are generated exclusively by epileptogenic tissue, and the epileptogenic index is elevated in regions besides epileptogenic tissue, then HFO sensitivity for the epileptogenic index would be decreased, but would not reflect a failure of HFOs to delineate epileptogenic regions. We look forward to future studies following STAR-D criteria that examine postoperative seizure outcomes in order to reassess this important topic in epilepsy surgery research. Potential Conflicts of Interest Dr Weiss is the founder of Fastwave LLC, an EEG software manufacturer, and, in addition, Dr Weiss has a patent 14507432 pending, a patent 62297202 pending, and a patent PCT/US17/64509 pending.

Reply to “are spikes noninferior to high-frequency oscillations?”: Reply

High frequency oscillations (HFOs) are considered a promising neurophysiological biomarker of epileptogenic activity. Recently, Roehri and colleagues reported results of a retrospective study of diagnostic accuracy that utilized a receiver operating characteristic (ROC) approach to determine if HFO and spike rates can delineate the seizure onset zone. In a tour de force of automated intracranial electroencephalography (EEG) analysis, the study specifically quantified the sensitivity, specificity, and area under the receiver operating curve (AUC) for spikes, ripples, and fast ripples for delineating a surrogate of the seizure-onset zone, called the epileptogenicity index. The authors conclude that, because the partial AUC is not always larger for HFOs as compared with spikes, HFOs are not superior to spikes for predicting epileptogenicity. The authors also conclude that fast ripples are not sensitive enough to be unique biomarkers of epilepsy. In light of the findings reported by Roehri and colleagues, it is important to refocus inquiries into the clinical relevance of high-frequency oscillations. Clinicians rely primarily on the visual inspection of intracranial EEG to delineate epileptogenic sites. Sometimes intraoperative recordings lasting only several minutes are utilized. Even a single instance of an HFO may be used for clinical decision making. In several past studies, a single fast ripple in an unresected electrode site has shown superior predictive value for poor postoperative surgical outcome. Roehri and colleagues also demonstrate that fast ripples have a superior specificity for the seizure onset zone. If a clinician identifies a fast ripple, should he or she now conclude that its significance is identical to a spike? HFO biomarker sensitivity, as defined by Roehri and colleagues, also requires further consideration. Roehri and colleagues compared the spatial distribution of electrode sites with elevated HFO rates with the sites exhibiting an increased epileptogenecity index. The epileptogenecity index is defined by EEG features observed at seizure onset and early spread. Attributed to spatial sampling limitations and volume conduction, it is unknown if all the electrode sites with an elevated epileptogenicity index are capable of independently generating a seizure. If HFOs are generated exclusively by epileptogenic tissue, and the epileptogenic index is elevated in regions besides epileptogenic tissue, then HFO sensitivity for the epileptogenic index would be decreased, but would not reflect a failure of HFOs to delineate epileptogenic regions. We look forward to future studies following STAR-D criteria that examine postoperative seizure outcomes in order to reassess this important topic in epilepsy surgery research. Potential Conflicts of Interest Dr Weiss is the founder of Fastwave LLC, an EEG software manufacturer, and, in addition, Dr Weiss has a patent 14507432 pending, a patent 62297202 pending, and a patent PCT/US17/64509 pending.