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Jean Gotman - One of the best experts on this subject based on the ideXlab platform.
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removing High Frequency Oscillations a prospective multicenter study on seizure outcome
Neurology, 2018Co-Authors: Julia Jacobs, Rina Zelmann, Andreas Schulzebonhage, Malenka Mader, Piero Perucca, F Dubeau, Gary W Mathern, Jean GotmanAbstract:Objective To evaluate the use of interictal High-Frequency Oscillations (HFOs) in epilepsy surgery for prediction of postsurgical seizure outcome in a prospective multicenter trial. Methods We hypothesized that a seizure-free outcome could be expected in patients in whom the surgical planning included the majority of HFO-generating brain tissue while a poor seizure outcome could be expected in patients in whom only a few such areas were planned to be resected. Fifty-two patients were included from 3 tertiary epilepsy centers during a 1-year period. Ripples (80–250 Hz) and fast ripples (250–500 Hz) were automatically detected during slow-wave sleep with chronic intracranial EEG in 2 centers and acute intraoperative electrocorticography in 1 patient. Results There was a correlation between the removal of HFO-generating regions and seizure-free outcome at the group level for all patients. No correlation was found, however, for the center-specific analysis, and an individual prognostication of seizure outcome was true in only 36 patients (67%). Moreover, some patients became seizure-free without removal of the majority of HFO-generating tissue. The investigation of influencing factors, including comparisons of visual and automatic analysis, using a threshold analysis for areas with High HFO activity, and excluding contacts bordering the resection, did not result in improved prognostication. Conclusions On an individual patient level, a prediction of outcome was not possible in all patients. This may be due to the analysis techniques used. Alternatively, HFOs may be less specific for epileptic tissue than earlier studies have indicated.
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High Frequency Oscillations in the normal human brain
Annals of Neurology, 2018Co-Authors: Rina Zelmann, Birgit Frauscher, Francois Dubeau, Philippe Kahane, Nicolas Von Ellenrieder, Christine Rogers, Dang Khoa Nguyen, Jean GotmanAbstract:Objective High-Frequency Oscillations (HFOs) are a promising biomarker for the epileptogenic zone. It has not been possible, however, to differentiate physiological from pathological HFOs, and baseline rates of HFO occurrence vary substantially across brain regions. This project establishes region-specific normative values for physiological HFOs and High-Frequency activity (HFA). Methods Intracerebral stereo-encephalographic recordings with channels displaying normal physiological activity from nonlesional tissue were selected from 2 tertiary epilepsy centers. Twenty-minute sections from N2/N3 sleep were selected for automatic detection of ripples (80-250Hz), fast ripples (>250Hz), and HFA defined as long-lasting activity > 80Hz. Normative values are provided for 17 brain regions. Results A total of 1,171 bipolar channels with normal physiological activity from 71 patients were analyzed. The Highest rates of ripples were recorded in the occipital cortex, medial and basal temporal region, transverse temporal gyrus and planum temporale, pre- and postcentral gyri, and medial parietal lobe. The mean rate of fast ripples was very low (0.038/min). Only 5% of channels had a rate > 0.2/min HFA was observed in the medial occipital lobe, pre- and postcentral gyri, transverse temporal gyri and planum temporale, and lateral occipital lobe. Interpretation This multicenter atlas is the first to provide region-specific normative values for physiological HFO rates and HFA in common stereotactic space; rates above these can now be considered pathological. Physiological ripples are frequent in eloquent cortex. In contrast, physiological fast ripples are very rare, making fast ripples a good candidate for defining the epileptogenic zone. Ann Neurol 2018;84:374-385.
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the morphology of High Frequency Oscillations hfo does not improve delineating the epileptogenic zone
Clinical Neurophysiology, 2016Co-Authors: Rina Zelmann, Birgit Frauscher, Sergey Burnos, Johannes Sarnthein, Claire Haegelen, Jean GotmanAbstract:OBJECTIVE: We hypothesized that High Frequency Oscillations (HFOs) with irregular amplitude and Frequency more specifically reflect epileptogenicity than HFOs with stable amplitude and Frequency. METHODS: We developed a fully automatic algorithm to detect HFOs and classify them based on their morphology, with types defined according to regularity in amplitude and Frequency: type 1 with regular amplitude and Frequency; type 2 with irregular amplitude, which could result from filtering of sharp spikes; type 3 with irregular Frequency; and type 4 with irregular amplitude and Frequency. We investigated the association of different HFO types with the seizure onset zone (SOZ), resected area and surgical outcome. RESULTS: HFO rates of all types were significantly Higher inside the SOZ than outside. HFO types 1 and 2 were strongly correlated to each other and showed the Highest rates among all HFOs. Their occurrence was Highly associated with the SOZ, resected area and surgical outcome. The automatic detection emulated visual markings with 93% true positives and 57% false detections. CONCLUSIONS: HFO types 1 and 2 similarly reflect epileptogenicity. SIGNIFICANCE: For clinical application, it may not be necessary to separate real HFOs from "false Oscillations" produced by the filter effect of sharp spikes. Also for automatically detected HFOs, surgical outcome is better when locations with Higher HFO rates are included in the resection.
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High Frequency Oscillations and spikes separating real hfos from false Oscillations
Clinical Neurophysiology, 2016Co-Authors: Mina Amiri, Jeanmarc Lina, Francesca Pizzo, Jean GotmanAbstract:Abstract Objective To demonstrate and quantify the occurrence of false High Frequency Oscillations (HFOs) generated by the filtering of sharp events. To distinguish real HFOs from spurious ones using analysis of the raw signal. Method We developed a new method to prevent false HFO detections due to the filtering effect by detecting Oscillations in the raw signal at the time of sharp events. We specified temporal features to classify sharp events with and without HFOs using support vector machine in both ripple and fast ripple bands. The traditionally used time–Frequency representation served as the gold standard to indicate real and false HFOs. Results 44% of ripples and 43% of FRs concurring with sharp events were found to be false HFOs. Sharp events with HFOs had significantly more Oscillations in the raw signal than sharp events without. They could be distinguished from false HFOs with accuracy of 76.6% in the ripple band and 72.6% in the fast ripple band. Conclusion It may be most appropriate to detect HFOs as Oscillations not only on the filtered signal but also on the raw signal. The classical time–Frequency display used for identifying HFOs should be used with great care due to the possible masking effect of broadband activities. Significance The separation of real HFOs from broadband activities will raise the validity of HFO detection methods and will therefore support future HFO investigations.
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High Frequency Oscillations hfos in clinical epilepsy
Progress in Neurobiology, 2012Co-Authors: Julia Jacobs, Maeike Zijlmans, Eishi Asano, Richard J Staba, Hiroshi Otsubo, Francois Dubeau, Ismail S Mohamed, Philippe Kahane, Vincent Navarro, Jean GotmanAbstract:Epilepsy is one of the most frequent neurological diseases. In focal medically refractory epilepsies, successful surgical treatment largely depends on the identification of epileptogenic zone. High-Frequency Oscillations (HFOs) between 80 and 500Hz, which can be recorded with EEG, may be novel markers of the epileptogenic zone. This review discusses the clinical importance of HFOs as markers of epileptogenicity and their application in different types of epilepsies. HFOs are clearly linked to the seizure onset zone, and the surgical removal of regions generating them correlates with a seizure free post-surgical outcome. Moreover, HFOs reflect the seizure-generating capability of the underlying tissue, since they are more frequent after the reduction of antiepileptic drugs. They can be successfully used in pediatric epilepsies such as epileptic spasms and help to understand the generation of this specific type of seizures. While mostly recorded on intracranial EEGs, new studies suggest that identification of HFOs on scalp EEG or magnetoencephalography (MEG) is possible as well. Thus not only patients with refractory epilepsies and invasive recordings but all patients might profit from the analysis of HFOs. Despite these promising results, the analysis of HFOs is not a routine clinical procedure; most results are derived from relatively small cohorts of patients and many aspects are not yet fully understood. Thus the review concludes that even if HFOs are promising biomarkers of epileptic tissue, there are still uncertainties about mechanisms of generation, methods of analysis, and clinical applicability. Large multicenter prospective studies are needed prior to widespread clinical application.
Jerome Engel - One of the best experts on this subject based on the ideXlab platform.
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extrahippocampal High Frequency Oscillations during epileptogenesis
Epilepsia, 2018Co-Authors: Mayur Patel, Joyel Almajano, Jerome Engel, Anatol BraginAbstract:The current study aimed to investigate the spatial and temporal patterns of High-Frequency Oscillations (HFOs) in the intra-/extrahippocampal areas during epileptogenesis. Local field potentials were bilaterally recorded from hippocampus (CA1), thalamus, motor cortex, and prefrontal cortex in 13 rats before and after intrahippocampal kainic acid (KA) lesions. HFOs in the ripple (100-200 Hz) and fast ripple (250-500 Hz) ranges were detected and their rates were computed during different time periods (1-5 weeks) after KA-induced status epilepticus (SE). Recurrent spontaneous seizures were observed in 7 rats after SE, and the other 6 rats did not develop epilepsy. During the latent period, the rate of hippocampal HFOs increased at the ipsilateral site of the KA lesion in both groups, and the HFO rate was significantly Higher in the animals that later developed epilepsy. Animals that later developed epilepsy also demonstrated widespread appearance of HFOs, in both the ripple and the fast ripple range, whereas animals that did not develop epilepsy only exhibited changes in the ipsilateral intrahippocampal HFO rate. This study demonstrates an association between an increased rate of widespread HFOs and the later development of epilepsy, suggesting the formation of large-scale distributed pathological networks during epileptogenesis.
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High Frequency Oscillations the state of clinical research
Epilepsia, 2017Co-Authors: Birgit Frauscher, Jan Cimbalnik, Eishi Asano, Hiroshi Otsubo, Katsuhiro Kobayashi, Fabrice Bartolomei, Maryse A Van T Klooster, Stefan Rampp, Yvonne Holler, Jerome EngelAbstract:Modern electroencephalographic (EEG) technology contributed to the appreciation that the EEG signal outside the classical Berger Frequency band contains important information. In epilepsy, research of the past decade focused particularly on interictal High-Frequency Oscillations (HFOs) > 80 Hz. The first large application of HFOs was in the context of epilepsy surgery. This is now followed by other applications such as assessment of epilepsy severity and monitoring of antiepileptic therapy. This article reviews the evidence on the clinical use of HFOs in epilepsy with an emphasis on the latest developments. It Highlights the growing literature on the association between HFOs and postsurgical seizure outcome. A recent meta-analysis confirmed a Higher resection ratio for HFOs in seizure-free versus non-seizure-free patients. Residual HFOs in the postoperative electrocorticogram were shown to predict epilepsy surgery outcome better than preoperative HFO rates. The review further discusses the different attempts to separate physiological from epileptic HFOs, as this might increase the specificity of HFOs. As an example, analysis of sleep microstructure demonstrated a different coupling between HFOs inside and outside the epileptogenic zone. Moreover, there is increasing evidence that HFOs are useful to measure disease activity and assess treatment response using noninvasive EEG and magnetoencephalography. This approach is particularly promising in children, because they show High scalp HFO rates. HFO rates in West syndrome decrease after adrenocorticotropic hormone treatment. Presence of HFOs at the time of rolandic spikes correlates with seizure Frequency. The time-consuming visual assessment of HFOs, which prevented their clinical application in the past, is now overcome by validated computer-assisted algorithms. HFO research has considerably advanced over the past decade, and use of noninvasive methods will make HFOs accessible to large numbers of patients. Prospective multicenter trials are awaited to gather information over long recording periods in large patient samples.
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ictal onset patterns of local field potentials High Frequency Oscillations and unit activity in human mesial temporal lobe epilepsy
Epilepsia, 2016Co-Authors: Shennan A Weiss, Anatol Bragin, Itzhak Fried, Jerome Engel, Catalina Alvaradorojas, Eric Behnke, Tony A Fields, Richard J StabaAbstract:Objective To characterize local field potentials, High Frequency Oscillations, and single unit firing patterns in microelectrode recordings of human limbic onset seizures.
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High Frequency Oscillations where we are and where we need to go
Progress in Neurobiology, 2012Co-Authors: Jerome Engel, Fernando Lopes H Da SilvaAbstract:High-Frequency Oscillations (HFOs) are EEG field potentials with frequencies Higher than 30 Hz; commonly the Frequency band between 30 and 70 Hz is denominated the gamma band, but with the discovery of activities at frequencies Higher than 70 Hz a variety of terms have been proposed to describe the latter (Gotman and Crone, 2011). In general we may consider that the term HFO encompasses activities from 30 to 600 Hz. The best practice is to indicate always explicitly the Frequency range of the HFOs in any specific study. There are numerous types of HFOs: those in normal brain appear to facilitate synchronization and information transfer necessary for cognitive processes and memory, while a particular class of HFOs in the brain of animals and people with epilepsy appears to reflect fundamental mechanisms of epileptic phenomena and could serve as biomarkers of epileptogenesis and epileptogenicity in abnormal conditions such as epilepsy. A better understanding of the significance of HFOs depends on a deeper analysis of the mechanisms of generation of different kinds of HFOs, that typically are at the crossroads between intrinsic membrane properties and neuronal interactions, both chemical and electrical. There is still a lack of understanding of how specific information is carried by HFOs and can be operational in normal cognitive processes such as in working and long-term memory and abnormal conditions such as epilepsy. The complexity of these processes makes the development of relevant computational models of dynamical neuronal networks most compelling.
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Further evidence that pathologic High-Frequency Oscillations are bursts of population spikes derived from recordings of identified cells in dentate gyrus.
Epilepsia, 2011Co-Authors: Anatol Bragin, Simone K. Benassi, Farshad Kheiri, Jerome EngelAbstract:Summary Purpose: To analyze activity of identified dentate gyrus granular cells and interneurons during pathologic High-Frequency Oscillations (pHFOs). Methods: Pilocarpine-treated epileptic mice were anesthetized with urethane and ketamine. Their heads were fixed in a stereotaxic frame. Extracellular unit activity was recoded with glass micropipettes, whereas multiunit and local field activity was simultaneously recorded with attached tungsten microelectrodes. After electrophysiologic experiments, recorded cells were labeled by neurobiotin and visualized by immunohistochemical methods. Key Findings and Significances: pHFOs containing more than three waves were recorded in our experiments, but pathologic single-population spikes also occurred. Identified granular cells discharged preferentially in synchrony with pHFOs and single population spikes, whereas interneurons decreased their discharge Frequency during this time. These experiments provide additional confirmation that pHFOs in the dentate gyrus represent single or recurrent population spikes, which in turn reflect summated hypersynchronous discharges of principal cells.
Maeike Zijlmans - One of the best experts on this subject based on the ideXlab platform.
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how to record High Frequency Oscillations in epilepsy a practical guideline
Epilepsia, 2017Co-Authors: Maeike Zijlmans, Akio Ikeda, Matthias Dümpelmann, Gregory A Worrell, Thomas Stieglitz, Andrei Barborica, Marcel Heers, Naotaka Usui, Michel Le Van QuyenAbstract:SummaryObjective Technology for localizing epileptogenic brain regions plays a central role in surgical planning. Recent improvements in acquisition and electrode technology have revealed that High-Frequency Oscillations (HFOs) within the 80–500 Hz Frequency range provide the neurophysiologist with new information about the extent of the epileptogenic tissue in addition to ictal and interictal lower Frequency events. Nevertheless, two decades after their discovery there remain questions about HFOs as biomarkers of epileptogenic brain and there use in clinical practice. Methods In this review, we provide practical, technical guidance for epileptologists and clinical researchers on recording, evaluation, and interpretation of ripples, fast ripples, and very High-Frequency Oscillations. Results We emphasize the importance of low noise recording to minimize artifacts. HFO analysis, either visual or with automatic detection methods, of High fidelity recordings can still be challenging because of various artifacts including muscle, movement, and filtering. Magnetoencephalography and intracranial electroencephalography (iEEG) recordings are subject to the same artifacts. Significance High-Frequency Oscillations are promising new biomarkers in epilepsy. This review provides interested researchers and clinicians with a review of current state of the art of recording and identification and potential challenges to clinical translation.
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automatic detection of High Frequency Oscillations during epilepsy surgery predicts seizure outcome
Clinical Neurophysiology, 2016Co-Authors: Tommaso Fedele, Maeike Zijlmans, Frans S S Leijten, Maryse A Van T Klooster, Sergey Burnos, Willemiek J E M Zweiphenning, Nicole E C Van Klink, Johannes SarntheinAbstract:Abstract Objective High Frequency Oscillations (HFOs) and in particular fast ripples (FRs) in the post-resection electrocorticogram (ECoG) have recently been shown to be Highly specific predictors of outcome of epilepsy surgery. FR visual marking is time consuming and prone to observer bias. We validate here a fully automatic HFO detector against seizure outcome. Methods Pre-resection ECoG dataset ( N =14 patients) with visually marked HFOs were used to optimize the detector's parameters in the time–Frequency domain. The optimized detector was then applied on a larger post-resection ECoG dataset ( N =54) and the output was compared with visual markings and seizure outcome. The analysis was conducted separately for ripples (80–250Hz) and FRs (250–500Hz). Results Channel-wise comparison showed a High association between automatic detection and visual marking ( p Conclusions Our automatic and fully unsupervised detection of HFO events matched the expert observer's performance in both event selection and outcome prediction. Significance The detector provides a standardized definition of clinically relevant HFOs, which may spread its use in clinical application.
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identification of epileptic High Frequency Oscillations in the time domain by using meg beamformer based virtual sensors
Clinical Neurophysiology, 2016Co-Authors: Nicole E C Van Klink, Arjan Hillebrand, Maeike ZijlmansAbstract:Abstract Objective High Frequency Oscillations (HFOs, >80 Hz) are biomarkers for epileptogenic cortex in invasive and non-invasive electroencephalography (EEG). Identification of HFOs in magnetoencephalography (MEG) is hindered by noise. Computing spatial filters using beamforming to reconstruct time series for selected brain regions, so-called virtual sensors (VS), can increase the signal-to-noise ratio. We identified HFOs in MEG in time domain using VS. Methods Fifteen minutes of MEG data were selected from 12 patients. VS were placed around the epileptic spikes (affected region) and in the contralateral hemisphere. VS and physical sensors were reviewed for HFOs and spikes. HFO locations were compared to spikes and other clinical parameters. Results Eight patients showed 78 time points with 575 HFOs in VS, 513 were in the affected region. HFOs could not be identified in physical sensors for 61 of the 78 VS time points. HFOs overlapped with presumed epileptogenic areas and were also visible in unfiltered VS signals. Conclusion Beamformer-based VS analysis can help to identify epileptic HFOs that are not discernable in physical MEG sensors. Significance This approach can be extended to enable localization of non-invasively recorded HFOs. This would help surgical planning and reduce the need for invasive diagnostics.
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automated seizure onset zone approximation based on nonharmonic High Frequency Oscillations in human interictal intracranial eegs
International Journal of Neural Systems, 2015Co-Authors: Evelien E Geertsema, Maeike Zijlmans, Gerhard H Visser, D N Velis, Steven Claus, Stiliyan KalitzinAbstract:A novel automated algorithm is proposed to approximate the seizure onset zone (SOZ), while providing reproducible output. The SOZ, a surrogate marker for the epileptogenic zone (EZ), was approximated from intracranial electroencephalograms (iEEG) of nine people with temporal lobe epilepsy (TLE), using three methods: (1) Total ripple length (TRL): Manually segmented High-Frequency Oscillations, (2) Rippleness (R): Area under the curve (AUC) of the autocorrelation functions envelope, and (3) Autoregressive model residual variation (ARR, novel algorithm): Time-variation of residuals from autoregressive models of iEEG windows. TRL, R, and ARR results were compared in terms of separability, using Kolmogorov-Smirnov tests, and performance, using receiver operating characteristic (ROC) curves, to the gold standard for SOZ delineation: visual observation of ictal video-iEEGs. TRL, R, and ARR can distinguish signals from iEEG channels located within the SOZ from those outside it (p < 0.01). The ROC AUC was 0.82 for ARR, while it was 0.79 for TRL, and 0.64 for R. ARR outperforms TRL and R, and may be applied to identify channels in the SOZ automatically in interictal iEEGs of people with TLE. ARR, interpreted as evidence for nonharmonicity of High-Frequency EEG components, could provide a new way to delineate the EZ, thus contributing to presurgical workup.
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High Frequency Oscillations hfos in clinical epilepsy
Progress in Neurobiology, 2012Co-Authors: Julia Jacobs, Maeike Zijlmans, Eishi Asano, Richard J Staba, Hiroshi Otsubo, Francois Dubeau, Ismail S Mohamed, Philippe Kahane, Vincent Navarro, Jean GotmanAbstract:Epilepsy is one of the most frequent neurological diseases. In focal medically refractory epilepsies, successful surgical treatment largely depends on the identification of epileptogenic zone. High-Frequency Oscillations (HFOs) between 80 and 500Hz, which can be recorded with EEG, may be novel markers of the epileptogenic zone. This review discusses the clinical importance of HFOs as markers of epileptogenicity and their application in different types of epilepsies. HFOs are clearly linked to the seizure onset zone, and the surgical removal of regions generating them correlates with a seizure free post-surgical outcome. Moreover, HFOs reflect the seizure-generating capability of the underlying tissue, since they are more frequent after the reduction of antiepileptic drugs. They can be successfully used in pediatric epilepsies such as epileptic spasms and help to understand the generation of this specific type of seizures. While mostly recorded on intracranial EEGs, new studies suggest that identification of HFOs on scalp EEG or magnetoencephalography (MEG) is possible as well. Thus not only patients with refractory epilepsies and invasive recordings but all patients might profit from the analysis of HFOs. Despite these promising results, the analysis of HFOs is not a routine clinical procedure; most results are derived from relatively small cohorts of patients and many aspects are not yet fully understood. Thus the review concludes that even if HFOs are promising biomarkers of epileptic tissue, there are still uncertainties about mechanisms of generation, methods of analysis, and clinical applicability. Large multicenter prospective studies are needed prior to widespread clinical application.
Rina Zelmann - One of the best experts on this subject based on the ideXlab platform.
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distinguishing false and true positive detections of High Frequency Oscillations
Journal of Neural Engineering, 2020Co-Authors: S Gliske, Rina Zelmann, Catalina Alvaradorojas, Zihan Qin, Katy Lau, Pariya Salami, William C StaceyAbstract:Objective High Frequency Oscillations (HFOs) are a promising biomarker of tissue that instigates seizures. However, ambiguous data and random background fluctuations can cause any HFO detector (human or automated) to falsely label non-HFO data as an HFO (a false positive detection). The objective of this paper was to identify quantitative features of HFOs that distinguish between true and false positive detections. Approach Feature selection was performed using background data in multi-day, interictal intracranial recordings from ten patients. We selected the feature most similar between randomly selected segments of background data and HFOs detected in surrogate background data (false positive detections by construction). We then compared these results with fuzzy clustering of detected HFOs in clinical data to verify the feature's applicability. We validated the feature is sensitive to false versus true positive HFO detections by using an independent data set (six subjects) scored for HFOs by three human reviewers. Lastly, we compared the effect of redacting putative false positive HFO detections on the distribution of HFOs across channels and their association with seizure onset zone (SOZ) and resected volume (RV). Main results Of the 15 analyzed features, the analysis selected only skewness of the curvature (skewCurve). The feature was validated in human scored data to be associated with distinguishing true and false positive HFO detections. Automated HFO detections with Higher skewCurve were more focal based on entropy measures and had increased localization to both the SOZ and RV. Significance We identified a quantitative feature of HFOs which helps distinguish between true and false positive detections. Redacting putative false positive HFO detections improves the specificity of HFOs as a biomarker of epileptic tissue.
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removing High Frequency Oscillations a prospective multicenter study on seizure outcome
Neurology, 2018Co-Authors: Julia Jacobs, Rina Zelmann, Andreas Schulzebonhage, Malenka Mader, Piero Perucca, F Dubeau, Gary W Mathern, Jean GotmanAbstract:Objective To evaluate the use of interictal High-Frequency Oscillations (HFOs) in epilepsy surgery for prediction of postsurgical seizure outcome in a prospective multicenter trial. Methods We hypothesized that a seizure-free outcome could be expected in patients in whom the surgical planning included the majority of HFO-generating brain tissue while a poor seizure outcome could be expected in patients in whom only a few such areas were planned to be resected. Fifty-two patients were included from 3 tertiary epilepsy centers during a 1-year period. Ripples (80–250 Hz) and fast ripples (250–500 Hz) were automatically detected during slow-wave sleep with chronic intracranial EEG in 2 centers and acute intraoperative electrocorticography in 1 patient. Results There was a correlation between the removal of HFO-generating regions and seizure-free outcome at the group level for all patients. No correlation was found, however, for the center-specific analysis, and an individual prognostication of seizure outcome was true in only 36 patients (67%). Moreover, some patients became seizure-free without removal of the majority of HFO-generating tissue. The investigation of influencing factors, including comparisons of visual and automatic analysis, using a threshold analysis for areas with High HFO activity, and excluding contacts bordering the resection, did not result in improved prognostication. Conclusions On an individual patient level, a prediction of outcome was not possible in all patients. This may be due to the analysis techniques used. Alternatively, HFOs may be less specific for epileptic tissue than earlier studies have indicated.
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High Frequency Oscillations in the normal human brain
Annals of Neurology, 2018Co-Authors: Rina Zelmann, Birgit Frauscher, Francois Dubeau, Philippe Kahane, Nicolas Von Ellenrieder, Christine Rogers, Dang Khoa Nguyen, Jean GotmanAbstract:Objective High-Frequency Oscillations (HFOs) are a promising biomarker for the epileptogenic zone. It has not been possible, however, to differentiate physiological from pathological HFOs, and baseline rates of HFO occurrence vary substantially across brain regions. This project establishes region-specific normative values for physiological HFOs and High-Frequency activity (HFA). Methods Intracerebral stereo-encephalographic recordings with channels displaying normal physiological activity from nonlesional tissue were selected from 2 tertiary epilepsy centers. Twenty-minute sections from N2/N3 sleep were selected for automatic detection of ripples (80-250Hz), fast ripples (>250Hz), and HFA defined as long-lasting activity > 80Hz. Normative values are provided for 17 brain regions. Results A total of 1,171 bipolar channels with normal physiological activity from 71 patients were analyzed. The Highest rates of ripples were recorded in the occipital cortex, medial and basal temporal region, transverse temporal gyrus and planum temporale, pre- and postcentral gyri, and medial parietal lobe. The mean rate of fast ripples was very low (0.038/min). Only 5% of channels had a rate > 0.2/min HFA was observed in the medial occipital lobe, pre- and postcentral gyri, transverse temporal gyri and planum temporale, and lateral occipital lobe. Interpretation This multicenter atlas is the first to provide region-specific normative values for physiological HFO rates and HFA in common stereotactic space; rates above these can now be considered pathological. Physiological ripples are frequent in eloquent cortex. In contrast, physiological fast ripples are very rare, making fast ripples a good candidate for defining the epileptogenic zone. Ann Neurol 2018;84:374-385.
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the morphology of High Frequency Oscillations hfo does not improve delineating the epileptogenic zone
Clinical Neurophysiology, 2016Co-Authors: Rina Zelmann, Birgit Frauscher, Sergey Burnos, Johannes Sarnthein, Claire Haegelen, Jean GotmanAbstract:OBJECTIVE: We hypothesized that High Frequency Oscillations (HFOs) with irregular amplitude and Frequency more specifically reflect epileptogenicity than HFOs with stable amplitude and Frequency. METHODS: We developed a fully automatic algorithm to detect HFOs and classify them based on their morphology, with types defined according to regularity in amplitude and Frequency: type 1 with regular amplitude and Frequency; type 2 with irregular amplitude, which could result from filtering of sharp spikes; type 3 with irregular Frequency; and type 4 with irregular amplitude and Frequency. We investigated the association of different HFO types with the seizure onset zone (SOZ), resected area and surgical outcome. RESULTS: HFO rates of all types were significantly Higher inside the SOZ than outside. HFO types 1 and 2 were strongly correlated to each other and showed the Highest rates among all HFOs. Their occurrence was Highly associated with the SOZ, resected area and surgical outcome. The automatic detection emulated visual markings with 93% true positives and 57% false detections. CONCLUSIONS: HFO types 1 and 2 similarly reflect epileptogenicity. SIGNIFICANCE: For clinical application, it may not be necessary to separate real HFOs from "false Oscillations" produced by the filter effect of sharp spikes. Also for automatically detected HFOs, surgical outcome is better when locations with Higher HFO rates are included in the resection.
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High Frequency Oscillations in intra operative electrocorticography before and after epilepsy surgery
Clinical Neurophysiology, 2014Co-Authors: Frans S S Leijten, Cyrille H Ferrier, Van N E C Klink, Van T M Klooster, Rina Zelmann, Kees P J Braun, Van P C Rijen, Van M J A M Putten, Geertjan J M HuiskampAbstract:Objective Removal of brain tissue showing High Frequency Oscillations (HFOs; ripples: 80–250 Hz and fast ripples: 250–500 Hz) in preresection electrocorticography (preECoG) in epilepsy patients seems a predictor of good surgical outcome. We analyzed occurrence and localization of HFOs in intra-operative preECoG and postresection electrocorticography (postECoG). Methods HFOs were automatically detected in one-minute epochs of intra-operative ECoG sampled at 2048 Hz of fourteen patients. Ripple, fast ripple, spike, ripples on a spike (RoS) and not on a spike (RnoS) rates were analyzed in pre- and postECoG for resected and nonresected electrodes. Results Ripple, spike and fast ripple rates decreased after resection. RnoS decreased less than RoS (74% vs. 83%; p = 0.01). Most fast ripples in preECoG were located in resected tissue. PostECoG fast ripples occurred in one patient with poor outcome. Patients with good outcome had relatively High postECoG RnoS rates, specifically in the sensorimotor cortex. Conclusions Our observations show that fast ripples in intra-operative ECoG, compared to ripples, may be a better biomarker for epileptogenicity. Further studies have to determine the relation between resection of epileptogenic tissue and physiological ripples generated by the sensorimotor cortex. Significance Fast ripples in intra-operative ECoG can help identify the epileptogenic zone, while ripples might also be physiological.
Anatol Bragin - One of the best experts on this subject based on the ideXlab platform.
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extrahippocampal High Frequency Oscillations during epileptogenesis
Epilepsia, 2018Co-Authors: Mayur Patel, Joyel Almajano, Jerome Engel, Anatol BraginAbstract:The current study aimed to investigate the spatial and temporal patterns of High-Frequency Oscillations (HFOs) in the intra-/extrahippocampal areas during epileptogenesis. Local field potentials were bilaterally recorded from hippocampus (CA1), thalamus, motor cortex, and prefrontal cortex in 13 rats before and after intrahippocampal kainic acid (KA) lesions. HFOs in the ripple (100-200 Hz) and fast ripple (250-500 Hz) ranges were detected and their rates were computed during different time periods (1-5 weeks) after KA-induced status epilepticus (SE). Recurrent spontaneous seizures were observed in 7 rats after SE, and the other 6 rats did not develop epilepsy. During the latent period, the rate of hippocampal HFOs increased at the ipsilateral site of the KA lesion in both groups, and the HFO rate was significantly Higher in the animals that later developed epilepsy. Animals that later developed epilepsy also demonstrated widespread appearance of HFOs, in both the ripple and the fast ripple range, whereas animals that did not develop epilepsy only exhibited changes in the ipsilateral intrahippocampal HFO rate. This study demonstrates an association between an increased rate of widespread HFOs and the later development of epilepsy, suggesting the formation of large-scale distributed pathological networks during epileptogenesis.
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ictal onset patterns of local field potentials High Frequency Oscillations and unit activity in human mesial temporal lobe epilepsy
Epilepsia, 2016Co-Authors: Shennan A Weiss, Anatol Bragin, Itzhak Fried, Jerome Engel, Catalina Alvaradorojas, Eric Behnke, Tony A Fields, Richard J StabaAbstract:Objective To characterize local field potentials, High Frequency Oscillations, and single unit firing patterns in microelectrode recordings of human limbic onset seizures.
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Further evidence that pathologic High-Frequency Oscillations are bursts of population spikes derived from recordings of identified cells in dentate gyrus.
Epilepsia, 2011Co-Authors: Anatol Bragin, Simone K. Benassi, Farshad Kheiri, Jerome EngelAbstract:Summary Purpose: To analyze activity of identified dentate gyrus granular cells and interneurons during pathologic High-Frequency Oscillations (pHFOs). Methods: Pilocarpine-treated epileptic mice were anesthetized with urethane and ketamine. Their heads were fixed in a stereotaxic frame. Extracellular unit activity was recoded with glass micropipettes, whereas multiunit and local field activity was simultaneously recorded with attached tungsten microelectrodes. After electrophysiologic experiments, recorded cells were labeled by neurobiotin and visualized by immunohistochemical methods. Key Findings and Significances: pHFOs containing more than three waves were recorded in our experiments, but pathologic single-population spikes also occurred. Identified granular cells discharged preferentially in synchrony with pHFOs and single population spikes, whereas interneurons decreased their discharge Frequency during this time. These experiments provide additional confirmation that pHFOs in the dentate gyrus represent single or recurrent population spikes, which in turn reflect summated hypersynchronous discharges of principal cells.
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High Frequency Oscillations in epileptic brain
Current Opinion in Neurology, 2010Co-Authors: Anatol Bragin, Jerome Engel, Richard J StabaAbstract:Purpose of reviewIt has been 10 years since pathological High-Frequency Oscillations (pHFOs) were described in the brain of epileptic animals and patients. This review summarizes progress in research on mechanisms of their generation and potential clinical applications over that period.Recent findin
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High Frequency Oscillations what is normal and what is not
Epilepsia, 2009Co-Authors: Jerome Engel, Anatol Bragin, Richard J Staba, Istvan ModyAbstract:SUMMARY High-Frequency Oscillations (HFOs) in the 80– 200 Hz range can be recorded from normal hippocampus and parahippocampal structures of humans and animals. They are believed to reflect inhibitory field potentials, which facilitate information transfer by synchronizing neuronal activity over long distances. HFOs in the range of 250– 600 Hz (fast ripples, FRs) are pathologic and are readily recorded from hippocampus and parahippocampal structures of patients with mesial temporal lobe epilepsy, as well as rodent models of this disorder. These Oscillations, and similar HFOs recorded from neocortex of patients, appear to identify brain tissue capable of spontaneous ictogenesis and are believed to reflect the neuronal substrates of epileptogenesis and epileptogenicity. The distinction between normal and pathologic HFOs (pHFOs), however, cannot be made on the basis of Frequency alone, as Oscillations in the FR Frequency range can be recorded from some areas of normal neocortex, whereas Oscillations in the ripple Frequency range are present in epileptic dentate gyrus where normal ripples never occur and, therefore, appear to be pathologic. The suggestion that FRs may be harmonics of normal ripples is unlikely, because of their spatially distinct generators, and evidence that FRs reflect synchronized firing of abnormally bursting neurons rather than inhibitory field potentials. These synchronous population spikes, however, can fire at ripple frequencies, and their harmonics appear to give rise to FRs. Investigations into the fundamental neuronal processes responsible for pHFOs could provide insights into basic mechanisms of epilepsy. The potential for pHFOs to act as biomarkers for epileptogenesis and epileptogenicity is also discussed.