keyword
MENU ▼
Read by QxMD icon Read
search

HFOs

keyword
https://www.readbyqxmd.com/read/28702346/automatic-detection-and-visualisation-of-meg-ripple-oscillations-in-epilepsy
#1
Nicole van Klink, Frank van Rosmalen, Jukka Nenonen, Sergey Burnos, Liisa Helle, Samu Taulu, Paul Lawrence Furlong, Maeike Zijlmans, Arjan Hillebrand
High frequency oscillations (HFOs, 80-500 Hz) in invasive EEG are a biomarker for the epileptic focus. Ripples (80-250 Hz) have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~ 2400 beamformer-based virtual sensors in the grey matter...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28681378/update-on-the-mechanisms-and-roles-of-high-frequency-oscillations-in-seizures-and-epileptic-disorders
#2
REVIEW
Premysl Jiruska, Catalina Alvarado-Rojas, Catherine A Schevon, Richard Staba, William Stacey, Fabrice Wendling, Massimo Avoli
High-frequency oscillations (HFOs) are a type of brain activity that is recorded from brain regions capable of generating seizures. Because of the close association of HFOs with epileptogenic tissue and ictogenesis, understanding their cellular and network mechanisms could provide valuable information about the organization of epileptogenic networks and how seizures emerge from the abnormal activity of these networks. In this review, we summarize the most recent advances in the field of HFOs and provide a critical evaluation of new observations within the context of already established knowledge...
July 6, 2017: Epilepsia
https://www.readbyqxmd.com/read/28676240/local-nmda-receptor-hypofunction-evokes-generalized-effects-on-gamma-and-high-frequency-oscillations-and-behavior
#3
Jaime Lee, Matthew R Hudson, Terence J O'Brien, Jess Nithianantharajah, Nigel C Jones
The NMDA receptor (NMDAr) hypofunction theory of schizophrenia suggests that aberrant signaling through NMDAr underlies the pathophysiology of this disease. This is commonly modeled in rodents via treatment with NMDAr antagonists, which causes a range of behavioral effects that represent endophenotypes related to schizophrenia. These drugs also disrupt high-frequency neural oscillations within the brain, also potentially relevant to disease. We studied the effect of localized NMDAr hypofunction on the generation of neural oscillations occurring both locally and in distant brain regions, and on behaviors routinely used as endophenotypes to model psychosis in rodents...
July 1, 2017: Neuroscience
https://www.readbyqxmd.com/read/28669244/automated-detector-of-high-frequency-oscillations-in-epilepsy-based-on-maximum-distributed-peak-points
#4
Guo-Ping Ren, Jia-Qing Yan, Zhi-Xin Yu, Dan Wang, Xiao-Nan Li, Shan-Shan Mei, Jin-Dong Dai, Xiao-Li Li, Yun-Lin Li, Xiao-Fei Wang, Xiao-Feng Yang
High frequency oscillations (HFOs) are considered as biomarker for epileptogenicity. Reliable automation of HFOs detection is necessary for rapid and objective analysis, and is determined by accurate computation of the baseline. Although most existing automated detectors measure baseline accurately in channels with rare HFOs, they lose accuracy in channels with frequent HFOs. Here, we proposed a novel algorithm using the maximum distributed peak points method to improve baseline determination accuracy in channels with wide HFOs activity ranges and calculate a dynamic baseline...
April 17, 2017: International Journal of Neural Systems
https://www.readbyqxmd.com/read/28666056/high-frequency-oscillations-the-state-of-clinical-research
#5
REVIEW
Birgit Frauscher, Fabrice Bartolomei, Katsuhiro Kobayashi, Jan Cimbalnik, Maryse A van 't Klooster, Stefan Rampp, Hiroshi Otsubo, Yvonne Höller, Joyce Y Wu, Eishi Asano, Jerome Engel, Philippe Kahane, Julia Jacobs, Jean Gotman
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...
June 30, 2017: Epilepsia
https://www.readbyqxmd.com/read/28655938/significance-of-high-frequency-electrical-brain-activity
#6
REVIEW
Katsuhiro Kobayashi, Tomoyuki Akiyama, Takashi Agari, Tatsuya Sasaki, Takashi Shibata, Yoshiyuki Hanaoka, Mari Akiyama, Fumika Endoh, Makio Oka, Isao Date
 Electroencephalogram (EEG) data include broadband electrical brain activity ranging from infra-slow bands (< 0.1 Hz) to traditional frequency bands (e.g., the approx. 10 Hz alpha rhythm) to high-frequency bands of up to 500 Hz. High-frequency oscillations (HFOs) including ripple and fast ripple oscillations (80-200 Hz and>200 / 250 Hz, respectively) are particularly of note due to their very close relationship to epileptogenicity, with the possibility that they could function as a surrogate biomarker of epileptogenicity...
June 2017: Acta Medica Okayama
https://www.readbyqxmd.com/read/28644911/interictal-oscillations-and-focal-epileptic-disorders
#7
Maxime Lévesque, Pariya Salami, Zahra Shiri, Massimo Avoli
Neuronal network oscillations represent a main feature of the brain activity recorded in the EEG under normal and pathological conditions such as epilepsy. Specific oscillations occur between seizures in patients and in animal models of focal epilepsy, and thus they are termed interictal. According to their shape and intrinsic signal frequency, interictal oscillations are classified as spikes and high frequency oscillations (HFOs). Interictal spikes are recorded in the "wideband" EEG signal and consist of large-amplitude events that usually last less than 1 s; HFOs, in contrast, are extracted by amplifying the appropriately filtered EEG signal, and are usually categorized as ripples (80-200 Hz) and fast ripples (250-500 Hz)...
June 23, 2017: European Journal of Neuroscience
https://www.readbyqxmd.com/read/28622421/how-to-record-high-frequency-oscillations-in-epilepsy-a-practical-guideline
#8
REVIEW
Maeike Zijlmans, Gregory A Worrell, Matthias Dümpelmann, Thomas Stieglitz, Andrei Barborica, Marcel Heers, Akio Ikeda, Naotaka Usui, Michel Le Van Quyen
OBJECTIVE: 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...
June 16, 2017: Epilepsia
https://www.readbyqxmd.com/read/28549276/different-seizure-onset-patterns-in-mesiotemporal-lobe-epilepsy-have-a-distinct-interictal-signature
#9
Birgit Frauscher, Nicolás von Ellenrieder, François Dubeau, Jean Gotman
OBJECTIVE: Experimental research demonstrated that distinct underlying mechanisms go along with different seizure-onset patterns on EEG. These different mechanisms may reflect different tissue abnormalities which, we hypothesize, could also be reflected in morphological differences in the interictal epileptic and background EEG activity. METHODS: We searched our database of intracranial EEG recordings for mesiotemporal lobe epilepsy patients with either predominant low-voltage fast activity (LVF) or periodic spiking (PS)...
July 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28521267/epileptogenic-high-frequency-oscillations-skip-the-motor-area-in-children-with-multilobar-drug-resistant-epilepsy
#10
Yasushi Iimura, Kevin Jones, Kyoko Hattori, Yushi Okazawa, Atsuko Noda, Kana Hoashi, Yutaka Nonoda, Eishi Asano, Tomoyuki Akiyama, Cristina Go, Ayako Ochi, O Carter Snead, Elizabeth J Donner, James T Rutka, James M Drake, Hiroshi Otsubo
OBJECTIVE: Subtotal hemispherectomy involves the resection of multiple lobes in children with drug-resistant epilepsy, skipping the motor area (MA). We determined epileptogenicity using the occurrence rate (OR) of high-frequency oscillations (HFOs) and the modulation index (MI), demonstrating strength of coupling between HFO and slow wave. We hypothesized that epileptogenicity increased over the multiple lobes but skipped the MA. METHODS: We analyzed 23 children (14 subtotal hemispherectomy; 9 multilobar resections)...
July 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28406919/what-are-the-assets-and-weaknesses-of-hfo-detectors-a-benchmark-framework-based-on-realistic-simulations
#11
Nicolas Roehri, Francesca Pizzo, Fabrice Bartolomei, Fabrice Wendling, Christian-George Bénar
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...
2017: PloS One
https://www.readbyqxmd.com/read/28380659/tailoring-epilepsy-surgery-with-fast-ripples-in-the-intraoperative-electrocorticogram
#12
Maryse A van 't Klooster, Nicole E C van Klink, Willemiek J E M Zweiphenning, Frans S S Leijten, Rina Zelmann, Cyrille H Ferrier, Peter C van Rijen, Willem M Otte, Kees P J Braun, Geertjan J M Huiskamp, Maeike Zijlmans
OBJECTIVE: Intraoperative electrocorticography (ECoG) can be used to delineate the resection area in epilepsy surgery. High-frequency oscillations (HFOs; 80-500 Hz) seem better biomarkers for epileptogenic tissue than spikes. We studied how HFOs and spikes in combined pre- and postresection ECoG predict surgical outcome in different tailoring approaches. METHODS: We, retrospectively, marked HFOs, divided into fast ripples (FRs; 250-500 Hz) and ripples (80-250 Hz), and spikes in pre- and postresection ECoG sampled at 2,048 Hz in people with refractory focal epilepsy...
May 2017: Annals of Neurology
https://www.readbyqxmd.com/read/28337411/physiological-and-pathological-high-frequency-oscillations-have-distinct-sleep-homeostatic-properties
#13
Nicolás von Ellenrieder, François Dubeau, Jean Gotman, Birgit Frauscher
OBJECTIVE: The stage of sleep is a known modulator of high-frequency oscillations (HFOs). For instance, high amplitude slow waves during NREM sleep and the subtypes of REM sleep were shown to contribute to a better separation between physiological and pathological HFOs. This study investigated rates and spatial spread of the different HFO types (physiological and pathological ripples in the 80-250 Hz frequency band, and fast ripples above 250 Hz) depending on time spent in sleep across the different sleep cycles...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28327467/automated-detection-of-epileptic-ripples-in-meg-using-beamformer-based-virtual-sensors
#14
Carolina Migliorelli, Joan F Alonso, Sergio Romero, Rafał Nowak, Antonio Russi, Miguel A Mañanas
OBJECTIVE: In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events...
March 22, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28280577/detecting-and-characterizing-high-frequency-oscillations-in-epilepsy-a-case-study-of-big-data-analysis
#15
Liang Huang, Xuan Ni, William L Ditto, Mark Spano, Paul R Carney, Ying-Cheng Lai
We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings...
January 2017: Royal Society Open Science
https://www.readbyqxmd.com/read/28269503/differentiation-of-spindle-associated-hippocampal-hfos-based-on-a-correlation-analysis
#16
Daniel Lachner Piza, Jonas C Bruder, Julia Jacobs, Andreas Schulze-Bonhage, Thomas Stieglitz, Matthias Dumpelmann
High Frequency Oscillations (HFOs) have been described as biomarkers of epileptogenic tissue; however their pathological/physiological classification poses a challenge to their predictive power. For the population of ripples co-occurring with sleep spindles, those ripples improving the antiparallel correlation of ripple-peaks and sleep spindle-troughs were classified as coupled-ripples and the rest as uncoupled-ripples. For the same population of ripples two reference groups called in-SOZ and non-SOZ were formed according to the ripples' location inside or outside the seizure onset zone (SOZ)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268496/computational-modeling-of-high-frequency-oscillations-recorded-with-clinical-intracranial-macroelectrodes
#17
M Shamas, P Benquet, I Merlet, W El Falou, M Khalil, F Wendling
High Frequency Oscillations (HFOs) are a potential biomarker of epileptogenic regions. They have been extensively investigated in terms of automatic detection, classification and feature extraction. However, the mechanisms governing the generation of HFOs as well as the observability conditions on clinical intracranial macroelectrodes remain elusive. In this paper, we propose a novel physiologically-relevant macroscopic model for accurate simulation of HFOs as invasively recorded in epileptic patients. This model accounts for both the temporal and spatial properties of the cortical patch at the origin of epileptiform activity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28258937/evoked-versus-spontaneous-high-frequency-oscillations-in-the-chronic-electrocorticogram-in-focal-epilepsy
#18
M A van 't Klooster, N E C van Klink, D van Blooijs, C H Ferrier, K P J Braun, F S S Leijten, G J M Huiskamp, M Zijlmans
OBJECTIVE: Spontaneous high frequency oscillations (HFOs; ripples 80-250Hz, fast ripples (FRs) 250-500Hz) are biomarkers for epileptogenic tissue in focal epilepsy. Single pulse electrical stimulation (SPES) can evoke HFOs. We hypothesized that stimulation distinguishes pathological from physiological ripples and compared the occurrence of evoked and spontaneous HFOs within the seizure onset zone (SOZ) and eloquent functional areas. METHODS: Ten patients underwent SPES during 2048Hz electrocorticography (ECoG)...
May 2017: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28235667/automated-detection-of-high-frequency-oscillations-in-electrophysiological-signals-methodological-advances
#19
Miguel Navarrete, Jan Pyrzowski, Juliana Corlier, Mario Valderrama, Michel Le Van Quyen
In recent years, new recording technologies have advanced such that oscillations of neuronal networks can be identified from simultaneous, multisite recordings at high temporal and spatial resolutions. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings also depends on the development of new mathematical methods capable of extracting meaningful information related to time, frequency and space. In this review, we aim to bridge this gap by focusing on the new analysis tools developed for the automated detection of high-frequency oscillations (HFOs, > 40 Hz) in local field potentials...
February 21, 2017: Journal of Physiology, Paris
https://www.readbyqxmd.com/read/28227755/differentiation-of-spindle-associated-hippocampal-hfos-based-on-a-correlation-analysis
#20
Daniel Lachner Piza, Jonas C Bruder, Julia Jacobs, Andreas Schulze-Bonhage, Thomas Stieglitz, Matthias Dumpelmann, Daniel Lachner Piza, Jonas C Bruder, Julia Jacobs, Andreas Schulze-Bonhage, Thomas Stieglitz, Matthias Dumpelmann, Thomas Stieglitz, Matthias Dumpelmann, Jonas C Bruder, Andreas Schulze-Bonhage, Daniel Lachner Piza, Julia Jacobs
High Frequency Oscillations (HFOs) have been described as biomarkers of epileptogenic tissue; however their pathological/physiological classification poses a challenge to their predictive power. For the population of ripples co-occurring with sleep spindles, those ripples improving the antiparallel correlation of ripple-peaks and sleep spindle-troughs were classified as coupled-ripples and the rest as uncoupled-ripples. For the same population of ripples two reference groups called in-SOZ and non-SOZ were formed according to the ripples' location inside or outside the seizure onset zone (SOZ)...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
keyword
keyword
43856
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"