High Frequency Oscillations Research Articles

Electrode Surface Area Impacts Measurement of High Frequency Oscillations in Human Intracranial EEG.

High-frequency oscillations (HFOs) are a promising prognostic biomarker of surgical outcome in patients with epilepsy. Their rates of occurrence and morphology have been studied extensively using recordings from electrodes of various geometries. While electrode size is a potential confounding factor in HFO studies, it has largely been disregarded due to a lack of consistent evidence. Therefore, we designed an experiment to directly test the impact of electrode size on HFO measurement. We first simulated HFO measurement using a lumped model of the electrode-tissue interaction. Then eight human subjects were each implanted with a high-density 8x8 grid of subdural electrodes. After implantation, the electrode sizes were altered using a technique recently developed by our group, enabling intracranial EEG recordings for three different electrode surface areas from a static brain location. HFOs were automatically detected in the data and their characteristics were calculated. The human subject measurements were consistent with the model. Specifically, HFO rate measured per area of tissue decreased significantly as electrode surface area increased. The smallest electrodes recorded more fast ripples than ripples. Amplitude of detected HFOs also decreased as electrode surface area increased, while duration and peak frequency were unaffected. These results suggest that HFO rates measured using electrodes of different surface areas cannot be compared directly. This has significant implications for HFOs as a tool for surgical planning, particularly for individual patients implanted with electrodes of multiple sizes and comparisons of HFO rate made across patients and studies.

Connectivity of high-frequency bursts as SOZ localization biomarker.

For patients with refractory epilepsy, the seizure onset zone (SOZ) plays an essential role in determining the specific regions of the brain that will be surgically resected. High-frequency oscillations (HFOs) and connectivity-based approaches have been identified among the potential biomarkers to localize the SOZ. However, there is no consensus on how connectivity between HFO events should be estimated, nor on its subject-specific short-term reliability. Therefore, we propose the channel-level connectivity dispersion (CLCD) as a metric to quantify the variability in synchronization between individual electrodes and to identify clusters of electrodes with abnormal synchronization, which we hypothesize to be associated with the SOZ. In addition, we developed a specialized filtering method that reduces oscillatory components caused by filtering broadband artifacts, such as sharp transients, spikes, or direct current shifts. Our connectivity estimates are therefore robust to the presence of these waveforms. To calculate our metric, we start by creating binary signals indicating the presence of high-frequency bursts in each channel, from which we calculate the pairwise connectivity between channels. Then, the CLCD is calculated by combining the connectivity matrices and measuring the variability in each electrode's combined connectivity values. We test our method using two independent open-access datasets comprising intracranial electroencephalography signals from 89 to 15 patients with refractory epilepsy, respectively. Recordings in these datasets were sampled at approximately 1000Hz, and our proposed CLCDs were estimated in the ripple band (80-200Hz). Across all patients in the first dataset, the average ROC-AUC was 0.73, and the average Cohen's d was 1.05, while in the second dataset, the average ROC-AUC was 0.78 and Cohen's d was 1.07. On average, SOZ channels had lower CLCD values than non-SOZ channels. Furthermore, based on the second dataset, which includes surgical outcomes (Engel I-IV), our analysis suggested that higher CLCD interquartile (as a measure of CLCD distribution spread) is associated with favorable outcomes (Engel I). This suggests that CLCD could significantly assist in identifying SOZ clusters and, therefore, provide an additional tool in surgical planning for epilepsy patients.

Automatic Detection of Scalp High-Frequency Oscillations Based on Deep Learning.

Scalp high-frequency oscillations (sHFOs) are a promising non-invasive biomarker of epilepsy. However, the visual marking of sHFOs is a time-consuming and subjective process, existing automatic detectors based on single-dimensional analysis have difficulty with accurately eliminating artifacts and thus do not provide sufficient reliability to meet clinical needs. Therefore, we propose a high-performance sHFOs detector based on a deep learning algorithm. An initial detection module was designed to extract candidate high-frequency oscillations. Then, one-dimensional (1D) and two-dimensional (2D) deep learning models were designed, respectively. Finally, the weighted voting method is used to combine the outputs of the two model. In experiments, the precision, recall, specificity and F1-score were 83.44%, 83.60%, 96.61% and 83.42%, respectively, on average and the kappa coefficient was 80.02%. In addition, the proposed detector showed a stable performance on multi-centre datasets. Our sHFOs detector demonstrated high robustness and generalisation ability, which indicates its potential applicability as a clinical assistance tool. The proposed sHFOs detector achieves an accurate and robust method via deep learning algorithm.

STABILITY OF THE INTERFACE OF LIQUIDS OSCILLATING IN A VERTICAL FLAT CHANNEL

The stability of an oscillating interface between two immiscible low-viscosity fluids of different densities in a vertical flat channel with a harmonic change in the liquid flow rate is studied experimentally. The limiting case of high dimensionless oscillation frequencies when the layer width exceeds the thickness of the Stokes layer is considered. It is found that a standing wave with a length significantly exceeding the gap width develops on the oscillating interface upon reaching a critical amplitude. It is shown that the discovered oscillations are gravity-capillary waves similar to Faraday ripples oscillating with the frequency of the driving force. The wavelength is determined by the interface oscillation frequency and the gravity acceleration and agrees well with the wavelength of gravity-capillary oscillations of the interface. A description of a new phenomenon is given.

Fast spatial laser beam modulation for improved process control in Laser Powder Bed Fusion

We report on the implementation of a high frequency beam oscillation (wobbling) strategy for improving process control during laser powder bed fusion of single weld tracks on Inconel 625. Oscillation frequencies ranging from ~ 600 Hz to 7000 Hz, and different oscillation trajectories (circular, parallel or perpendicular to the direction of scanning) were explored. Highspeed imaging was used to elucidate the dynamics of the melt pool induced by the wobble beams, along with in situ absorptivity measurements to substantiate our hypothesis that the dynamic nature of wobble beams reduces absorptive losses due to laser-vapor interactions and results in improved coupling at the melt pool. Operando X-ray radiography was carried out to visualize sub-surface melt flow dynamics, correlate to spatter mechanisms and optimize the window for improving process stability. Our observations indicate that wobble beams increase the aspect ratio of the melt pool by up to 4×, depending on the oscillation frequency and energy input. Highspeed imaging and X-ray radiography reveal an optimized process parameter window for reducing spatter, improving absorptivity and creating a stable melt pool at high (several kHz) oscillation frequencies.

Automated Detection of Interictal High-frequency Oscillations for Epileptogenic Zone Localization

Automated Detection of Interictal High-frequency Oscillations for Epileptogenic Zone Localization

High frequency oscillation network dynamics predict outcome in non-palliative epilepsy surgery.

High frequency oscillations are a promising biomarker of outcome in intractable epilepsy. Prior high frequency oscillation work focused on counting high frequency oscillations on individual channels, and it is still unclear how to translate those results into clinical care. We show that high frequency oscillations arise as network discharges that have valuable properties as predictive biomarkers. Here, we develop a tool to predict patient outcome before surgical resection is performed, based on only prospective information. In addition to determining high frequency oscillation rate on every channel, we performed a correlational analysis to evaluate the functional connectivity of high frequency oscillations in 28 patients with intracranial electrodes. We found that high frequency oscillations were often not solitary events on a single channel, but part of a local network discharge. Eigenvector and outcloseness centrality were used to rank channel importance within the connectivity network, then used to compare patient outcome by comparison with the seizure onset zone or a proportion within the proposed resected channels (critical resection percentage). Combining the knowledge of each patient's seizure onset zone resection plan along with our computed high frequency oscillation network centralities and high frequency oscillation rate, we develop a Naïve Bayes model that predicts outcome (positive predictive value: 100%) better than predicting based upon fully resecting the seizure onset zone (positive predictive value: 71%). Surgical margins had a large effect on outcomes: non-palliative patients in whom most of the seizure onset zone was resected ('definitive surgery', ≥ 80% resected) had predictable outcomes, whereas palliative surgeries (<80% resected) were not predictable. These results suggest that the addition of network properties of high frequency oscillations is more accurate in predicting patient outcome than seizure onset zone alone in patients with most of the seizure onset zone removed and offer great promise for informing clinical decisions in surgery for refractory epilepsy.

Adaptive optimization of virtual synchronous generator based on fuzzy logic control and differential evolution

Maintaining frequency stability in low inertia microgrids with high renewable energy source (RES) penetration is a major problem. To resolve this issue, the use of the virtual synchronous generator (VSG) was proposed in the literature. VSGs can provide damping and inertial response mimicking the operation of synchronous generators, hence the name. However, the damping and inertia coefficients of VSGs are typically fixed which limits the capabilities of VSG in stabilizing the frequency. Higher frequency oscillations may develop due to the fixed damping factor and virtual inertia constants. This paper proposes an optimization method that sets the VSG damping and inertia coefficients in an adaptive manner based on the fuzzy logic controller (FLC). Further, the differential evolution (DE) algorithm is used to solve the formulated multi-objective function to optimize the FLC gains. In this way, the damping and virtual coefficients are continuously and adaptively adjusted to provide optimal frequency stabilization. To verify the efficiency of the proposed optimization and control method, a comprehensive nonlinear simulation analysis was carried out using MATLAB/Simulink to compare the proposed method with the conventional VSG. The simulation was performed under multiple renewable penetration levels. The proposed method showed remarkable performance during disturbances and at varied RES penetration levels with 7.3% less frequency deviation and 46% less rate of change of frequency.

Adaptive second order sliding mode control of an oscillating water column

AbstractThe energy from waves has a vast untapped potential to contribute to renewable energy supply and diversification. For that reason, wave energy conversion systems have been a topical research area in recent years. In particular, harnessing wave energy with an oscillating water column converter has proved to be one suitable solution, which has also seen a number of successful deployments. Nevertheless, additional research is required for this technology in order to reach full commercial maturity and economic performance. This paper proposes an adaptive second order sliding mode controller to maximise the converted energy. In particular, the proposed adaptive control setup maintains the sliding mode robust features, while reducing high frequency oscillations and abrupt control actions produced by fixed‐gain algorithms. A comparison of energy generation performance shows better energy conversion efficiency of the proposed control strategy over standard speed regulation control strategies, even considering air compression dynamics and hydrodynamics in the tests.

Mouse model of focal cortical dysplasia type II generates a wide spectrum of high-frequency activities

High-frequency oscillations (HFOs) represent an electrographic biomarker of endogenous epileptogenicity and seizure-generating tissue that proved clinically useful in presurgical planning and delineating the resection area. In the neocortex, the clinical observations on HFOs are not sufficiently supported by experimental studies stemming from a lack of realistic neocortical epilepsy models that could provide an explanation of the pathophysiological substrates of neocortical HFOs. In this study, we explored pathological epileptiform network phenomena, particularly HFOs, in a highly realistic murine model of neocortical epilepsy due to focal cortical dysplasia (FCD) type II. FCD was induced in mice by the expression of the human pathogenic mTOR gene mutation during embryonic stages of brain development. Electrographic recordings from multiple cortical regions in freely moving animals with FCD and epilepsy demonstrated that the FCD lesion generates HFOs from all frequency ranges, i.e., gamma, ripples, and fast ripples up to 800 Hz. Gamma-ripples were recorded almost exclusively in FCD animals, while fast ripples occurred in controls as well, although at a lower rate. Gamma-ripple activity is particularly valuable for localizing the FCD lesion, surpassing the utility of fast ripples that were also observed in control animals, although at significantly lower rates. Propagating HFOs occurred outside the FCD, and the contralateral cortex also generated HFOs independently of the FCD, pointing to a wider FCD network dysfunction. Optogenetic activation of neurons carrying mTOR mutation and expressing Channelrhodopsin-2 evoked fast ripple oscillations that displayed spectral and morphological profiles analogous to spontaneous oscillations. This study brings experimental evidence that FCD type II generates pathological HFOs across all frequency bands and provides information about the spatiotemporal properties of each HFO subtype in FCD. The study shows that mutated neurons represent a functionally interconnected and active component of the FCD network, as they can induce interictal epileptiform phenomena and HFOs.

High frequency oscillations in relation to interictal spikes in predicting postsurgical seizure freedom

We evaluate whether interictal spikes, epileptiform HFOs and their co-occurrence (Spike + HFO) were included in the resection area with respect to seizure outcome. We also characterise the relationship between high frequency oscillations (HFOs) and propagating spikes. We analysed intracranial EEG of 20 patients that underwent resective epilepsy surgery. The co-occurrence of ripples and fast ripples was considered an HFO event; the co-occurrence of an interictal spike and HFO was considered a Spike + HFO event. HFO distribution and spike onset were compared in cases of spike propagation. Accuracy in predicting seizure outcome was 85% for HFO, 60% for Spikes, and 79% for Spike + HFO. Sensitivity was 57% for HFO, 71% for Spikes and 67% for Spikes + HFO. Specificity was 100% for HFO, 54% for Spikes and 85% for Spikes + HFO. In 2/2 patients with spike propagation, the spike onset included the HFO area. Combining interictal spikes with HFO had comparable accuracy to HFO. In patients with propagating spikes, HFO rate was maximal at the onset of spike propagation.

Laboratory Experiments Qualify Bit Influence on High-Frequency Torsional Oscillations

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 212566, “Qualifying Bit Influence on High-Frequency Torsional Oscillations Based on Full-Scale Laboratory Experiments,” by Armin Kueck, Eliah Everhard, and Xu Huang, Baker Hughes, et al. The paper has not been peer reviewed. _ High-frequency torsional oscillations (HFTOs) generate dynamic loads that can damage drilling tools, resulting in cracks, twistoffs, or broken electronics. Recently, a full-scale drilling test rig was proven to generate verified HFTO behavior under laboratory conditions. This rig allows for a comprehensive study of the influences of bit characteristics on HFTO. The complete paper presents methods to qualify bit features to suppress HFTO. Laboratory Rig Setup Test-Rig Design. The full-scale laboratory test rig drills rocks in a pressurized rock chamber. Rate of penetration (ROP), weight on bit (WOB), rotational speed, pressure, bit type, and rock type can be varied. The simulator consists of an open-loop mud-circulation system with capacity for 200 bbl of fluid, two 1,000-hp triplex pumps capable of up to 500 gal/min, a hoisting mechanism for raising and loading the drillstring up to 10,000 lbf, a 1,000-hp rotary drive capable of up to 10,000 ft-lbf, and a pressure vessel rated to 10,000 psi. High-frequency measurement instrumentation, including in-bit vibration sensors, records the tangential accelerations and dynamic torque at various positions in the BHA. The mounted device can be seen in the top left photo in Fig. 1. Measurement. To initially characterize the frequency response of the system, an impact test was performed on the system in a suspended nonoperating state with roving accelerometers (sensors) positioned as indicated by the blue lines in Fig. 1. Also indicated are the free-end and fixed-end boundary conditions at the bit (left) and drive (right), respectively, as well as the point of reference impact. The data from each pair of sensors are then processed to separate the torsional motions from lateral. Because HFTO is a self-excited vibration, it must be validated that this type of vibration is actually excited in the laboratory setup. To demonstrate that the excitation mechanism is representative for the field, one of the test results was used as a reference. A laboratory investigation showed that the measured vibration matches characteristics of self-excited vibrations. Investigations in the laboratory will, therefore, lead to valid solutions in the field.

High amplitude high frequency oscillations during posttraumatic epileptogenesis

Background: The aim of the present study was to investigate if high amplitude high frequency oscillations (haHFOs) could be a biomarker of posttraumatic epileptogenesis. Methods: After an initial craniotomy of rats and inducement of traumatic brain injury (TBI) through a fluid percussion, recording microelectrodes were implanted bilaterally in different brain areas. Wideband brain electrical activity was recorded intermittently from Day 1 of TBI and continued till week 21. HaHFO analysis was performed during the first 4 weeks to investigate whether the occurrence of this brain activity predicted development of epilepsy or not. Results: Of the 21 rats which received the TBI, 9 became epileptic (E+) and 12 did not (E−). HaHFOs were observed in the prefrontal and perilesional cortices, hippocampus, and striatum in both E+ and E− group. In comparison to the rats in E−, the E+ group showed a significant increase in the rate of haHFO from weeks 1 to 4 after TBI. Conclusion: The results indicate that an increase in the rate of haHFOs after TBI could be an electroencephalographic biomarker of posttraumatic epileptogenesis.

Adaptive Distributed Attitude Consensus of a Heterogeneous Multiagent Quadrotor System: Singular Perturbation Approach

Singular perturbations easily cause the problem of high gain control (HGC) of a multi-agent quadrotor system (MAQS), that easily excite hazardous high frequency oscillations in the system states. Without HGC, this work studies the distributed fixed-time attitude consensus control problem of multiple heterogeneous quadrotors in presence of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">unknown Lipschitz input disturbances and directed topology</i> . First, the second order sliding mode, composed of consensus errors of “slow” Euler angles and “fast” angular velocities, is designed to be two-time-scale (TTS). Then, an adaptive super twisting controller is designed to produce an integrated slow-fast control structure, and adjust controller gains in different time scales with respect to the disturbance gradients. On this basis, an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -dependent Lyapunov framework is built for the MAQS on multiple time scales, which provide a rigorous theoretical basis for the fast and robust attitude consensus, and estimate the reaching time subject to singular perturbations. Simulation results on a heterogeneous MAQS consisting of four agents are provided to verify the effectiveness and efficiency of the proposed controller.

High-frequency oscillation network mapping predict prognosis after radiofrequency thermocoagulation for epilepsy

High-frequency oscillation network mapping predict prognosis after radiofrequency thermocoagulation for epilepsy

Multi-Tuned Narrowband Damping for Suppressing MMC High-Frequency Oscillations

Multi-Tuned Narrowband Damping for Suppressing MMC High-Frequency Oscillations

Protective Activity of Novel Hydrophilic Synthetic Neurosteroids on Organophosphate Status Epilepticus-induced Chronic Epileptic Seizures, Non-Convulsive Discharges, High-Frequency Oscillations, and Electrographic Ictal Biomarkers.

Nerve agents and organophosphates (OP) are neurotoxic chemicals that induce acute seizures, status epilepticus (SE), and mortality. Long-term neurologic and neurodegenerative effects manifest months to years after OP exposure. Current benzodiazepine anticonvulsants are ineffective in preventing such long-term neurobehavioral and neuropathological changes. New and effective anticonvulsants are needed for OP intoxication, especially for mitigating the long-term sequelae after acute exposure. We developed neurosteroids as novel anticonvulsants and neuroprotectants in OP exposure models. In this study, we evaluated the long-term efficacy of novel synthetic neurosteroids in preventing the development of chronic epilepsy and hyperexcitable ictal events in a rat OP model of SE. Rats were exposed to the OP nerve agent surrogate diisopropylfluorophosphate (DFP), and the experimental groups were treated with the synthetic neurosteroid valaxanolone (VX) or lysaxanolone (LX) 40 minutes post-exposure in conjunction with midazolam. Video-electroencephalography was monitored for two months to assess spontaneous recurrent seizures (SRS), epileptiform discharges, interictal spikes, and high-frequency oscillations (HFOs). Within 60 days of DFP exposure, rats developed chronic epilepsy characterized by frequent SRS, epileptiform discharges, and HFOs. LX treatment was associated with a dose-dependent reduction of epilepsy occurrence and overall seizure burden with a significant decrease in SRS and epileptiform discharges. It also significantly reduced the occurrence of epileptic biomarkers of HFOs and interictal spikes, indicating potential disease-modifying activity. Similarly, the neurosteroid analog VX also significantly attenuated SRS, discharges, HFOs, and ictal events. These results demonstrate the long-term protective effects of synthetic neurosteroids in the OP-exposed post-SE model, indicating their disease-modifying potential to prevent epilepsy and ictal abnormalities. SIGNIFICANCE STATEMENT: The effects of nerve agents and organophosphate (OP) exposure are persistent, and survivors suffer from a number of devastating, chronic neurological dysfunctions. Currently, there is no specific therapy for preventing this disastrous impact of OP exposure. We propose synthetic neurosteroids that activate tonic inhibition provide viable options for preventing the long-term neurological effects of OP intoxication. The results from this study reveal the disease-modifying potential of two novel synthetic neurosteroids in preventing epileptogenesis and chronic epileptic seizures after OP-induced SE.

Pathological and Physiological High-frequency Oscillations on Electroencephalography in Patients with Epilepsy.

High-frequency oscillations (HFOs) encompass ripples (80Hz-200Hz) and fast ripples (200Hz-600Hz), serving as a promising biomarker for localizing the epileptogenic zone in epilepsy. Spontaneous fast ripples are always pathological, while ripples may be physiological or pathological. Distinguishing physiological from pathological ripples is important not only for designating epileptogenic brain regions, but also for investigations that study ripples in the context of memory encoding, consolidation, and recall in patients with epilepsy. Many studies have sought to identify distinguishing features between pathological and physiological ripples over the past two decades. Physiological and pathological ripples differ with respect to their spatial location, cellular mechanisms, morphology, and coupling with background electroencephalographic activity. Retrospective studies have demonstrated that differentiating between pathological and physiological ripples can improve surgical outcome prediction. In this review, we summarize the characteristics, differences, and applications of pathological and physiological HFOs and discuss strategies for their clinical translation.

Light‐fueled self‐oscillation of liquid crystal polymer network: Effect of photostabilizers

AbstractThe quest for harnessing light‐induced oscillatory motion, inspired by natural oscillations, has become a focus of scientific attention. Researchers are exploring the use of liquid crystal network (LCN) polymers and their integration with compatible materials as soft actuators. Of particular interest is the utilization of photostabilizers, which play a pivotal role in preserving the polymer against photodegradation. For this, three distinct derivatives of Tinuvin were chosen to explore their influence on the light‐fueled oscillatory motion of LCN polymers when exposed to polarized light to examine the impact of molecular orientation on the resultant motion. The research includes a comprehensive analysis of morphology, FT‐IR spectra, and elastic modulus assessments. The findings indicate that the Tinuvin derivatives along with light polarization have an impact on the resulting oscillatory characteristics. The findings include oscillation frequencies spanning from 8.95 to 14.96 Hz and oscillation amplitudes ranging from 0.47 to 1.73 mm. The dipole moment of Tinuvin types influences the oscillation frequency by altering the elastic modulus of the LCN, while its impact on surface roughness and structural configuration affects the resulting oscillation amplitude. Notably, the highest oscillation frequency is observed when all oriented molecules within the LCN respond to 45° polarized light. Investigating the impact of utilized photostabilizers on the polymer structural configuration was although possible through the examination of related FT‐IR specra.

Interaction of interictal epileptiform activity with sleep spindles is associated with cognitive deficits and adverse surgical outcome in pediatric focal epilepsy.

Temporal coordination between oscillations enables intercortical communication and is implicated in cognition. Focal epileptic activity can affect distributed neural networks and interfere with these interactions. Refractory pediatric epilepsies are often accompanied by substantial cognitive comorbidity, but mechanisms and predictors remain mostly unknown. Here, we investigate oscillatory coupling across large-scale networks in the developing brain. We analyzed large-scale intracranial electroencephalographic recordings in children with medically refractory epilepsy undergoing presurgical workup (n = 25, aged 3-21 years). Interictal epileptiform discharges (IEDs), pathologic high-frequency oscillations (HFOs), and sleep spindles were detected. Spatiotemporal metrics of oscillatory coupling were determined and correlated with age, cognitive function, and postsurgical outcome. Children with epilepsy demonstrated significant temporal coupling of both IEDs and HFOs to sleep spindles in discrete brain regions. HFOs were associated with stronger coupling patterns than IEDs. These interactions involved tissue beyond the clinically identified epileptogenic zone and were ubiquitous across cortical regions. Increased spatial extent of coupling was most prominent in older children. Poor neurocognitive function was significantly correlated with high IED-spindle coupling strength and spatial extent; children with strong pathologic interactions additionally had decreased likelihood of postoperative seizure freedom. Our findings identify pathologic large-scale oscillatory coupling patterns in the immature brain. These results suggest that such intercortical interactions could predict risk for adverse neurocognitive and surgical outcomes, with the potential to serve as novel therapeutic targets to restore physiologic development.