scholarly journals Dissociated behavior of low-frequency responses and high-frequency oscillations after systemic morphine administration in conscious rats

Neuroreport ◽  
2010 ◽  
Vol 21 (1) ◽  
pp. 2-7 ◽  
Author(s):  
Guo-Liang Li ◽  
Zhi-Mei Qiao ◽  
Ji-Sheng Han ◽  
Fei Luo
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Conscious Rats ◽  
Frequency Responses ◽  
High Frequency Oscillations ◽  
Morphine Administration

Real Ear Sound Pressure Levels Developed by Three Portable Stereo System Earphones

1992 ◽  
Vol 1 (4) ◽  
pp. 52-55 ◽  
Author(s):  
Gail L. MacLean ◽  
Andrew Stuart ◽  
Robert Stenstrom
Keyword(s):  
High Frequency ◽  
Sound Pressure ◽  
Low Frequency ◽  
Test System ◽  
Output Frequency ◽  
Frequency Effects ◽  
Adult Men ◽  
Frequency Responses ◽  
Significant Difference ◽  
Sound Pressure Levels

Differences in real ear sound pressure levels (SPLs) with three portable stereo system (PSS) earphones (supraaural [Sony Model MDR-44], semiaural [Sony Model MDR-A15L], and insert [Sony Model MDR-E225]) were investigated. Twelve adult men served as subjects. Frequency response, high frequency average (HFA) output, peak output, peak output frequency, and overall RMS output for each PSS earphone were obtained with a probe tube microphone system (Fonix 6500 Hearing Aid Test System). Results indicated a significant difference in mean RMS outputs with nonsignificant differences in mean HFA outputs, peak outputs, and peak output frequencies among PSS earphones. Differences in mean overall RMS outputs were attributed to differences in low-frequency effects that were observed among the frequency responses of the three PSS earphones. It is suggested that one cannot assume equivalent real ear SPLs, with equivalent inputs, among different styles of PSS earphones.

“Eclipse” Bifurcation in a Twinkling Oscillator

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Smruti R. Panigrahi ◽  
Brian F. Feeny ◽  
Alejandro R. Diaz
Keyword(s):  
Bifurcation Point ◽  
High Frequency ◽  
Low Frequency ◽  
Negative Stiffness ◽  
Symmetric System ◽  
Ambient Vibrations ◽  
High Frequency Oscillations ◽  
Mass Chain

This work regards the use of cubic springs with intervals of negative stiffness, in other words, “snap-through” elements, in order to convert low-frequency ambient vibrations into high-frequency oscillations, referred to as “twinkling.” The focus of this paper is on the bifurcation of a two-mass chain that, in the symmetric system, involves infinitely many equilibria at the bifurcation point. The structure of this “eclipse bifurcation” is uncovered, and perturbations of the bifurcation are studied. The energies associated with the equilibria are examined.

Global “Eclipse” Bifurcation in a Twinkling Oscillator

2013 ◽  
Author(s):  
Smruti R. Panigrahi ◽  
Brian F. Feeny ◽  
Alejandro R. Diaz
Keyword(s):  
Bifurcation Point ◽  
High Frequency ◽  
Global Bifurcation ◽  
Low Frequency ◽  
Negative Stiffness ◽  
Symmetric System ◽  
Ambient Vibrations ◽  
High Frequency Oscillations ◽  
Mass Chain

This work regards the use of cubic springs with intervals of negative stiffness, in other words “snap-through” elements, in order to convert low-frequency ambient vibrations into high-frequency oscillations, referred to as “twinkling”. The focus of this paper is on a global bifurcation of a two-mass chain which, in the symmetric system, involves infinitely many equilibria at the bifurcation point. The structure of this “eclipse” bifurcation is uncovered, and perturbations of the bifurcation are studied. The energies associated with the equilibria are examined.

Interaction between High Frequency Oscillations and Low Frequency Oscillations in Beam-Plasma System

1967 ◽  
Vol 23 (6) ◽  
pp. 1430-1431 ◽  
Author(s):  
Takaya Kawabe ◽  
Yoshinobu Kawai ◽  
Kazuo Takayama ◽  
Shoji Kojima
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Plasma System ◽  
High Frequency Oscillations ◽  
Low Frequency Oscillations ◽  
Beam Plasma

scholarly journals Recognition of Emotional States using Multiscale Information Analysis of High Frequency EEG Oscillations

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 609 ◽  
Author(s):  
Gao ◽  
Cui ◽  
Wan ◽  
Gu
Keyword(s):  
Emotion Recognition ◽  
High Frequency ◽  
Low Frequency ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Emotional States ◽  
Circumplex Model ◽  
Information Analysis ◽  
Eeg Signals ◽  
High Frequency Oscillations

Exploring the manifestation of emotion in electroencephalogram (EEG) signals is helpful for improving the accuracy of emotion recognition. This paper introduced the novel features based on the multiscale information analysis (MIA) of EEG signals for distinguishing emotional states in four dimensions based on Russell's circumplex model. The algorithms were applied to extract features on the DEAP database, which included multiscale EEG complexity index in the time domain, and ensemble empirical mode decomposition enhanced energy and fuzzy entropy in the frequency domain. The support vector machine and cross validation method were applied to assess classification accuracy. The classification performance of MIA methods (accuracy = 62.01%, precision = 62.03%, recall/sensitivity = 60.51%, and specificity = 82.80%) was much higher than classical methods (accuracy = 43.98%, precision = 43.81%, recall/sensitivity = 41.86%, and specificity = 70.50%), which extracted features contain similar energy based on a discrete wavelet transform, fractal dimension, and sample entropy. In this study, we found that emotion recognition is more associated with high frequency oscillations (51–100Hz) of EEG signals rather than low frequency oscillations (0.3–49Hz), and the significance of the frontal and temporal regions are higher than other regions. Such information has predictive power and may provide more insights into analyzing the multiscale information of high frequency oscillations in EEG signals.

Observation of Turbulent Waves in a Helium Plasma by Optical Spectroscopy

1975 ◽  
Vol 30 (10) ◽  
pp. 1271-1278
Author(s):  
W. R. Rutgers
Keyword(s):  
Energy Density ◽  
Field Strength ◽  
High Frequency ◽  
Low Frequency ◽  
Turbulent Plasma ◽  
Helium Plasma ◽  
High Frequency Oscillations ◽  
Low Frequency Oscillations ◽  
Frequency Domains ◽  
Turbulent Heating

Abstract From the combined Stark-Zeeman pattern of helium allowed and forbidden optical lines the frequency spectrum, the field strength and the dominant polarization of microfields were determined in a turbulent plasma. Two frequency domains of oscillations were found in a turbulent heating experiment: low-frequency oscillations with dominant polarization perpendicular to the current direction and high-frequency oscillations (f~fpe) with random polarization. The r.m.s. field strength of the oscillations is between 2 kV/cm and 10 kV/cm. The energy density of turbulent microfields amounts to 1‰ of the thermal energy density.

scholarly journals Motoneuron firing patterns underlying fast oscillations in phrenic nerve discharge in the rat

2012 ◽  
Vol 108 (8) ◽  
pp. 2134-2143 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Michael G. Z. Ghali ◽  
Robert F. Rogers
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Medium Frequency ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Novel Method ◽  
Frequency Coherence ◽  
Fast Oscillations ◽  
First Time

Fast oscillations are ubiquitous throughout the mammalian central nervous system and are especially prominent in respiratory motor outputs, including the phrenic nerves (PhNs). Some investigators have argued for an epiphenomenological basis for PhN high-frequency oscillations because phrenic motoneurons (PhMNs) firing at these same frequencies have never been recorded, although their existence has never been tested systematically. Experiments were performed on 18 paralyzed, unanesthetized, decerebrate adult rats in which whole PhN and individual PhMN activity were recorded. A novel method for evaluating unit-nerve time-frequency coherence was applied to PhMN and PhN recordings. PhMNs were classified according to their maximal firing rate as high, medium, and low frequency, corresponding to the analogous bands in PhN spectra. For the first time, we report the existence of PhMNs firing at rates corresponding to high-frequency oscillations during eupneic motor output. The majority of PhMNs fired only during inspiration, but a small subpopulation possessed tonic activity throughout all phases of respiration. Significant time-varying PhMN-PhN coherence was observed for all PhMN classes. High-frequency, early-recruited units had significantly more consistent onset times than low-frequency, early/middle-recruited and medium-frequency, middle/late-recruited PhMNs. High- and medium-frequency PhMNs had significantly more consistent offset times than low-frequency units. This suggests that startup and termination of PhMNs with higher firing rates are more precisely controlled, which may contribute to the greater PhMN-PhN coherence at the beginning and end of inspiration. Our findings provide evidence that near-synchronous discharge of PhMNs firing at high rates may underlie fast oscillations in PhN discharge.

Generation of quasi-stationary magnetic fields by external electromagnetic radiation in a cold magneto-active plasma

1993 ◽  
Vol 49 (1) ◽  
pp. 51-54 ◽  
Author(s):  
Yu. M. Aliev ◽  
B. M. Jovanović ◽  
A. A. Frolov
Keyword(s):  
Electromagnetic Radiation ◽  
High Frequency ◽  
Low Frequency ◽  
Active Plasma ◽  
Method Of Averaging ◽  
Hydrodynamic Equations ◽  
Cold Electron ◽  
Stationary Magnetic Field ◽  
High Frequency Oscillations ◽  
Space Time Evolution

Starting from the hydrodynamic equations for a cold electron fluid, we develop a theory of the ponderomotive effect of the interaction of high-frequency electromagnetic radiation with a magneto-active plasma. Using the method of averaging on high-frequency oscillations, we obtain expressions for the low- frequency nonlinear currents. We also obtain an equation describing the space–time evolution of a quasi-stationary magnetic field in the plasma.

Selective loss of high-frequency oscillations in phrenic and hypoglossal activity in the decerebrate rat during gasping

2006 ◽  
Vol 291 (5) ◽  
pp. R1414-R1429 ◽  
Author(s):  
Vitaliy Marchenko ◽  
Robert F. Rogers
Keyword(s):  
Power Distribution ◽  
High Frequency ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
High Amplitude ◽  
Medial Branch ◽  
Adult Rats ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Nerve Recordings

Respiratory motor outputs contain medium-(MFO) and high-frequency oscillations (HFO) that are much faster than the fundamental breathing rhythm. However, the associated changes in power spectral characteristics of the major respiratory outputs in unanesthetized animals during the transition from normal eupneic breathing to hypoxic gasping have not been well characterized. Experiments were performed on nine unanesthetized, chemo- and barodenervated, decerebrate adult rats, in which asphyxia elicited hyperpnea, followed by apnea and gasping. A gated fast Fourier transform (FFT) analysis and a novel time-frequency representation (TFR) analysis were developed and applied to whole phrenic and to medial branch hypoglossal nerve recordings. Our results revealed one MFO and one HFO peak in the phrenic output during eupnea, where HFO was prominent in the first two-thirds of the burst and MFO was prominent in the latter two-thirds of the burst. The hypoglossal activity contained broadband power distribution with several distinct peaks. During gasping, two high-amplitude MFO peaks were present in phrenic activity, and this state was characterized by a conspicuous loss in HFO power. Hypoglossal activity showed a significant reduction in power and a shift in its distribution toward lower frequencies during gasping. TFR analysis of phrenic activity revealed the increasing importance of an initial low-frequency “start-up” burst that grew in relative intensity as hypoxic conditions persisted. Significant changes in MFO and HFO rhythm generation during the transition from eupnea to gasping presumably reflect a reconfiguration of the respiratory network and/or alterations in signal processing by the circuitry associated with the two motor pools.

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