scholarly journals Multitaper Estimates of Phase-Amplitude Coupling

2021 ◽  
Author(s):  
Kyle Q. Lepage ◽  
Cavan N. Fleming ◽  
Mark Witcher ◽  
Sujith Vijayan
Keyword(s):  
High Frequency ◽  
Broad Band ◽  
Low Frequency ◽  
Partial Coherence ◽  
High Frequency Oscillation ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Statistical Measures ◽  
Frequency Components ◽  
Phase Amplitude

AbstractPhase-amplitude coupling (PAC) is the association of the amplitude of a high-frequency oscillation with the phase of a low-frequency oscillation. In neuroscience, this relationship provides a mechanism by which neural activity might be coordinated between distant regions. The dangers and pitfalls of assessing phase-amplitude coupling with existing statistical measures have been well-documented. The limitations of these measures include: (i) response to non-oscillatory, high-frequency, broad-band activity, (ii) response to high-frequency components of the low-frequency oscillation, (iii) adhoc selection of analysis frequency-intervals, and (iv) reliance upon data shuffling to assess statistical significance. In this work, a multitaper phase-amplitude coupling estimator is proposed that addresses issues (i)-(iv) above. Specifically, issue (i) is addressed by replacing the analytic signal envelope estimator computed using the Hilbert transform with a multitaper estimator that down-weights non-sinusoidal activity using a classical, multitaper super-resolution technique. Issue (ii) is addressed by replacing coherence between the low-frequency and high-frequency components in a standard PAC estimator with multitaper partial coherence, while issue (iii) is addressed with a physical argument regarding meaningful neural oscillation. Finally, asymptotic statistical assessment of the multitaper estimator is introduced to address issue (iv).

Analysis of Fast-Scale Bifurcation in Peak Current Controlled Buck-Boost Inverter Based on Unified Averaged Model

2016 ◽  
Vol 26 (05) ◽  
pp. 1650074 ◽  
Author(s):  
Hao Zhang ◽  
Shuai Dong ◽  
Weimin Guan ◽  
Ye Liu
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Period Doubling ◽  
Current Control ◽  
High Frequency Oscillation ◽  
Switching Frequency ◽  
Unified Framework ◽  
Frequency Oscillation ◽  
Peak Current ◽  
Averaged Model

In this paper, a unified averaged modeling method is proposed to investigate the fast-scale period-doubling bifurcation of a full-bridge integrated buck-boost inverter with peak current control. In order to increase the resolution of the conventional classic averaged model to half the switching frequency, sample-and-hold effect of inductor current is absorbed into the averaged model, i.e. the proposed unified averaged model can capture the high-frequency dynamical characteristics of the buck-boost inverter, which is both an extension and a modification of conventional averaged model. Based on the unified mode, fast-scale bifurcation is identified, and the corresponding bifurcation point is predicted with the help of the locus movement of all the poles, and their underlying mechanisms are revealed. Detailed analysis shows that the occurrence of high-frequency oscillation means fast-scale bifurcation, while the occurrence of low-frequency oscillation leads to slow-scale bifurcation. Finally, it is demonstrated that the unified averaged model can provide not only a general method to investigate both the slow- and fast-scale bifurcations in a unified framework but also a quite straightforward design-oriented method which can be directly applicable.

scholarly journals Objective interictal electrophysiology biomarkers optimize prediction of epilepsy surgery outcome

2021 ◽  
Author(s):  
Naoto Kuroda ◽  
Masaki Sonoda ◽  
Makoto Miyakoshi ◽  
Hiroki Nariai ◽  
Jeong-Won Jeong ◽  
...  
Keyword(s):  
Standard Model ◽  
High Frequency ◽  
Classification Accuracy ◽  
Modulation Index ◽  
High Frequency Oscillation ◽  
Frequency Oscillation ◽  
Model Accuracy ◽  
Intracranial Eeg ◽  
Postoperative Seizure ◽  
Phase Amplitude

Abstract Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving postoperative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥ 80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3-4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG, and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across nonepileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the nonepileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League Against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of postoperative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.

Mechanisms of temporal variation in single-nephron blood flow in rats

1993 ◽  
Vol 264 (3) ◽  
pp. F427-F434 ◽  
Author(s):  
K. P. Yip ◽  
N. H. Holstein-Rathlou ◽  
D. J. Marsh
Keyword(s):  
Blood Flow ◽  
High Frequency ◽  
Laser Doppler Velocimetry ◽  
Low Frequency ◽  
Tubuloglomerular Feedback ◽  
High Frequency Oscillation ◽  
Frequency Oscillation ◽  
Acute Hypertension ◽  
Efferent Arteriole ◽  
Single Nephron

Modified laser-Doppler velocimetry was used to determine the number of different mechanisms regulating single-nephron blood flow. Two oscillations were identified in star vessel blood flow, one at 20-50 mHz and another at 100-200 mHz. Tubuloglomerular feedback (TGF) mediates the slower oscillation, and the faster one is probably myogenic in origin. Acute hypertension increased autospectral power in the 20-50 mHz and 100-200 mHz frequency bands to 282 +/- 50 and 248 +/- 64%, respectively, of control even though mean single-nephron blood flow was autoregulated. Mean blood flow increased 24.6 +/- 6.1% when TGF was inhibited by intratubular perfusion with furosemide, and it decreased 42.8 +/- 3.9% when TGF was saturated by tubular perfusion with artificial tubular fluid at high rates. Autospectral power in the low-frequency band decreased 50.5 +/- 9.6% during furosemide and decreased 74.9 +/- 5.9% during TGF saturation, consistent with a TGF origin of the slow oscillation. In contrast, autospectral power of the high-frequency oscillation increased 75.4 +/- 23.9% during TGF inhibition and decreased 35.8 +/- 11% when TGF was saturated, suggesting interactions between the two spontaneously oscillating components in efferent arteriole blood flow.

scholarly journals A Time-Series Model of Phase Amplitude Cross Frequency Coupling and Comparison of Spectral Characteristics with Neural Data

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Kyle Q. Lepage ◽  
Sujith Vijayan
Keyword(s):  
Time Series ◽  
High Frequency ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
Time Series Model ◽  
High Frequency Component ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

Stochastic processes that exhibit cross-frequency coupling (CFC) are introduced. The ability of these processes to model observed CFC in neural recordings is investigated by comparison with published spectra. One of the proposed models, based on multiplying a pulsatile function of a low-frequency oscillation (θ) with an unobserved and high-frequency component, yields a process with a spectrum that is consistent with observation. Other models, such as those employing a biphasic pulsatile function of a low-frequency oscillation, are demonstrated to be less suitable. We introduce the full stochastic process time series model as a summation of three component weak-sense stationary (WSS) processes, namely,θ,γ, andη, withηa1/fαnoise process. Theγprocess is constructed as a product of a latent and unobserved high-frequency processxwith a function of the lagged, low-frequency oscillatory component (θ). After demonstrating that the model process is WSS, an appropriate method of simulation is introduced based upon the WSS property. This work may be of interest to researchers seeking to connect inhibitory and excitatory dynamics directly to observation in a model that accounts for known temporal dependence or to researchers seeking to examine what can occur in a multiplicative time-domain CFC mechanism.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

High-Frequency Oscillation and Chronic Lung Disease in Very Low Birth Weight Infants

PEDIATRICS ◽  
2001 ◽  
Vol 108 (1) ◽  
pp. 212-214
Author(s):  
J. P. Shenai; ◽  
P. Rimensberger; ◽  
U. Thome ◽  
F. Pohlandt; ◽  
P. Rimensberger
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Lung Disease ◽  
Chronic Lung Disease ◽  
High Frequency ◽  
Very Low Birth Weight ◽  
High Frequency Oscillation ◽  
Frequency Oscillation ◽  
Low Birth Weight Infants

ANALYSIS OF STAND RESEARCH RESULTS OF AXIAL DYNAMIC FORCE IN DRILLING BY THREE ROLLER CONE BIT

2019 ◽  
pp. 81-93
Author(s):  
В. М. Мойсишин ◽  
M. V. Lyskanych ◽  
R. A. Zhovniruk ◽  
Ye. P. Majkovych
Keyword(s):  
Low Frequency ◽  
Maximum Energy ◽  
Dynamic Force ◽  
Low Frequency Oscillation ◽  
Drilling Tool ◽  
Rock Destruction ◽  
Frequency Components ◽  
Harmonic Components ◽  
Experimental Values ◽  
Harmful Effects

The purpose of the proposed article is to establish the causes of oscillations of drilling tool and the basic laws of the distribution of the total energy of the process of changing the axial dynamic force over frequencies of spectrum. Variable factors during experiments on the classical plan were the rigidity of drilling tool and the hardness of the rock. According to the results of research, the main power of the process of change of axial dynamic force during drilling of three roller cone bits is in the frequency range 0-32 Hz in which three harmonic frequency components are allocated which correspond to the theoretical values of low-frequency and gear oscillations of the chisel and proper oscillations of the bit. The experimental values of frequencies of harmonic components of energy and normalized spectrum as well as the magnitude of the dispersion of the axial dynamic force and its normalized values at these frequencies are presented. It has been found that with decreasing rigidity of the drilling tool maximum energy of axial dynamic force moves from the low-frequency oscillation region to the tooth oscillation area, intensifying the process of rock destruction and, at the same time, protecting the tool from the harmful effects of the vibrations of the bit. Reducing the rigidity of the drilling tool protects the bit from the harmful effects of the vibrations generated by the stand. The energy reductions in these fluctuations range from 47 to 77%.

A Novel Adaptive PET/CT Image Fusion Algorithm

2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
High Frequency ◽  
Malignant Tumors ◽  
Low Frequency ◽  
Combination Method ◽  
Ct Image ◽  
Fusion Algorithm ◽  
Pet Ct ◽  
Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

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