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https://www.readbyqxmd.com/read/28337411/physiological-and-pathological-high-frequency-oscillations-have-distinct-sleep-homeostatic-properties
#1
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
#2
Carolina Migliorelli, Joan Alonso, Sergio Romero, Rafal Nowak, Antonio Russi, Miguel Mananas
OBJECTIVE: In epilepsy, high-frequency oscillations (HFOs) are considered events highly linked to the seizure onset zone (SOZ). The detection of HFOs in noninvasive signals such as scalp EEG and MEG is still a challenging task. The aim of this study was to automatize the detection of ripples in MEG signals reducing the high-frequency noise using beamformer-based virtual sensors (VS) and applying an automatic procedure exploring the time-frequency content of the detected events. APPROACH: 200 seconds of MEG signals and simultaneous iEEG were selected in nine patients with refractory epilepsy...
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
#3
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
#4
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
#5
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
#6
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)...
February 6, 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
#7
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
#8
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
https://www.readbyqxmd.com/read/28226670/computational-modeling-of-high-frequency-oscillations-recorded-with-clinical-intracranial-macroelectrodes
#9
M Shamas, P Benquet, I Merlet, W El Falou, M Khalil, F Wendling, M Shamas, P Benquet, I Merlet, W El Falou, M Khalil, F Wendling, M Khalil, P Benquet, I Merlet, W El Falou, M Shamas, 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/28194133/current-and-emerging-potential-of-magnetoencephalography-in-the-detection-and-localization-of-high-frequency-oscillations-in-epilepsy
#10
REVIEW
Eleonora Tamilia, Joseph R Madsen, Patricia Ellen Grant, Phillip L Pearl, Christos Papadelis
Up to one-third of patients with epilepsy are medically intractable and need resective surgery. To be successful, epilepsy surgery requires a comprehensive preoperative evaluation to define the epileptogenic zone (EZ), the brain area that should be resected to achieve seizure freedom. Due to lack of tools and methods that measure the EZ directly, this area is defined indirectly based on concordant data from a multitude of presurgical non-invasive tests and intracranial recordings. However, the results of these tests are often insufficiently concordant or inconclusive...
2017: Frontiers in Neurology
https://www.readbyqxmd.com/read/28160749/interrater-reliability-of-visually-evaluated-high-frequency-oscillations
#11
Aaron M Spring, Daniel J Pittman, Yahya Aghakhani, Jeffrey Jirsch, Neelan Pillay, Luis E Bello-Espinosa, Colin Josephson, Paolo Federico
OBJECTIVE: High frequency oscillations (HFOs) and interictal epileptiform discharges (IEDs) have been shown to be markers of epileptogenic regions. However, there is currently no 'gold standard' for identifying HFOs. Accordingly, we aimed to formally characterize the interrater reliability of HFO markings to validate the current practices. METHODS: A morphology detector was implemented to detect events (candidate HFOs, lower-threshold events, and distractors) from the intracranial EEG (iEEG) of ten patients...
December 30, 2016: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28115239/high-frequency-oscillations-and-mesial-temporal-lobe-epilepsy
#12
REVIEW
Maxime Lévesque, Zahra Shiri, Li-Yuan Chen, Massimo Avoli
The interest of epileptologists has recently shifted from the macroscopic analysis of interictal spikes and seizures to the microscopic analysis of short events in the EEG that are not visible to the naked eye but are observed once the signal has been filtered in specific frequency bands. With the use of new technologies that allow multichannel recordings at high sampling rates and the development of computer algorithms that permit the automated analysis of extensive amounts of data, it is now possible to extract high-frequency oscillations (HFOs) between 80 and 500Hz from the EEG; HFOs have been further categorised as ripples (80-200Hz) and fast ripples (250-500Hz)...
January 20, 2017: Neuroscience Letters
https://www.readbyqxmd.com/read/28113472/a-spatially-focused-method-for-high-density-electrode-based-functional-brain-mapping-applications
#13
Chih-Wei Chang, Yue-Loong Hsin, Wentai Liu
Mapping the electric field of the brain with electrodes benefits from its superior temporal resolution but is prone to low spatial resolution property comparing with other modalities such as fMRI, which can directly impact the precision of clinical diagnosis. Simulations show that dense arrays with straightforwardly miniaturized electrodes in terms of size and pitch may not improve the spatial resolution but only strengthen the cross coupling between adjacent channels due to volume conduction. We present a new spatially focused method to improve the electrode spatial selectivity and consequently suppress the neural signal coupling from the sources in the vicinity...
March 7, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28113293/automatic-detection-and-classification-of-high-frequency-oscillations-in-depth-eeg-signals
#14
Nisrine Jrad, Amar Kachenoura, Isabelle Merlet, Fabrice Bartolomei, Anca Nica, Arnaud Biraben, Fabrice Wendling
GOAL: Interictal High Frequency Oscillations (HFOs [30-600 Hz]) have proven to be relevant biomarkers in epilepsy. In this paper, four categories of HFOs are considered: Gamma ([30- 80 Hz]), High-Gamma ([80-120 Hz]), Ripples ([120-250 Hz]) and Fast-Ripples ([250-600 Hz]). A universal detector of the four types of HFOs is proposed. It has the advantages of i) classifying HFOs, and thus being robust to inter- and intra-subject variability; ii) rejecting artefacts, thus being specific. METHODS: Gabor atoms are tuned to cover the physiological bands...
November 29, 2016: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28107659/high-frequency-oscillations-and-seizure-like-discharges-in-the-entorhinal-cortex-of-the-in-vitro-isolated-guinea-pig-brain
#15
Laura Uva, Davide Boido, Massimo Avoli, Marco de Curtis, Maxime Lévesque
We analyzed the patterns of seizure-like activity and associated high-frequency oscillations (HFOs) induced by the K(+) channel blocker 4-aminopyridine (4AP, 50μM) or the GABAA receptor antagonist bicuculline methiodide (BMI, 50μM) in the in vitro isolated guinea pig brain preparation. Extracellular field recordings were obtained from the medial entorhinal cortex (EC) using glass pipettes or silicon probes; 4AP or BMI were applied through the basilar artery. Ripples (80-200Hz) or fast ripples (250-500Hz) occurred at higher rates shortly before ictal events induced by 4AP or BMI, respectively...
February 2017: Epilepsy Research
https://www.readbyqxmd.com/read/28063789/co-occurrence-of-high-frequency-oscillations-and-delayed-responses-evoked-by-intracranial-electrical-stimulation-in-stereo-eeg-studies
#16
Cristian Donos, Ioana Mîndruţă, Mihai Dragoş Malîia, Alin Raşină, Jean Ciurea, Andrei Barborica
OBJECTIVE: To perform a side-by-side comparison of two epileptogenicity biomarkers, high frequency oscillations (HFOs) and delayed responses (DRs), as a result of single-pulse electrical stimulation. METHODS: We have recorded stimulation-evoked HFOs and DRs in 16 epileptic patients undergoing presurgical evaluation using the stereoelectroencephalographic method. To evaluate converging and complementary information provided by the biomarkers, we analyzed them individually and for logical "and"/"or" combinations between them...
December 18, 2016: Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology
https://www.readbyqxmd.com/read/28060325/interictal-high-frequency-oscillations-detected-with-simultaneous-magnetoencephalography-and-electroencephalography-as-biomarker-of-pediatric-epilepsy
#17
Christos Papadelis, Eleonora Tamilia, Steven Stufflebeam, Patricia E Grant, Joseph R Madsen, Phillip L Pearl, Naoaki Tanaka
Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings...
December 6, 2016: Journal of Visualized Experiments: JoVE
https://www.readbyqxmd.com/read/28043201/physiological-ripples-associated-with-sleep-spindles-differ-in-waveform-morphology-from-epileptic-ripples
#18
Jonas C Bruder, Matthias Dümpelmann, Daniel Lachner Piza, Malenka Mader, Andreas Schulze-Bonhage, Julia Jacobs-Le Van
High frequency oscillations (HFOs, 80-500[Formula: see text]Hz) serve as novel electroencephalography (EEG) markers of epileptic tissue. The differentiation of physiological and epileptic HFO is an important challenge and is complicated by the fact that both types are generated in mesiotemporal structures. This study aimed to identify oscillation features that serve to distinguish physiological ripples associated with sleep spindles and epileptic ripples. We studied 19 patients with chronic intracranial EEG(iEEG) with mesiotemporal implantation and simultaneous scalp EEG...
November 2, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27965619/dynamic-changes-in-spectral-and-spatial-signatures-of-high-frequency-oscillations-in-rat-hippocampi-during-epileptogenesis-in-acute-and-chronic-stages
#19
Pan-Pan Song, Jing Xiang, Li Jiang, Heng-Sheng Chen, Ben-Ke Liu, Yue Hu
OBJECTIVE: To analyze spectral and spatial signatures of high frequency oscillations (HFOs), which include ripples and fast ripples (FRs, >200 Hz) by quantitatively assessing average and peak spectral power in a rat model of different stages of epileptogenesis. METHODS: The lithium-pilocarpine model of temporal lobe epilepsy was used. The acute phase of epilepsy was assessed by recording intracranial electroencephalography (EEG) activity for 1 day after status epilepticus (SE)...
2016: Frontiers in Neurology
https://www.readbyqxmd.com/read/27913322/automatic-detection-and-classification-of-high-frequency-oscillations-in-depth-eeg-signals
#20
Nisrine Jrad, Amar Kachenoura, Isabelle Merlet, Fabrice Bartolomei, Anca Nica, Arnaud Biraben, Fabrice Wendling
GOAL: Interictal High Frequency Oscillations (HFOs [30-600 Hz]) have proven to be relevant biomarkers in epilepsy. In this paper, four categories of HFOs are considered: Gamma ([30- 80 Hz]), High-Gamma ([80-120 Hz]), Ripples ([120-250 Hz]) and Fast-Ripples ([250-600 Hz]). A universal detector of the four types of HFOs is proposed. It has the advantages of i) classifying HFOs, and thus being robust to inter- and intra-subject variability; ii) rejecting artefacts, thus being specific. METHODS: Gabor atoms are tuned to cover the physiological bands...
November 29, 2016: IEEE Transactions on Bio-medical Engineering
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