Norepinephrine reuptake, baroreflex dynamics, and arterial pressure variability in rats

2000 ◽  
Vol 279 (4) ◽  
pp. R1257-R1267 ◽  
Author(s):  
Delphine Bertram ◽  
Christian Barrès ◽  
Yong Cheng ◽  
Claude Julien
Keyword(s):  
Time Delay ◽  
Transfer Function ◽  
Fixed Time ◽  
Baroreceptor Reflex ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Mayer Waves ◽  
Frequency Responses ◽  
Low Pass ◽  
Norepinephrine Reuptake

This study examined the effect of norepinephrine reuptake blockade with desipramine (DMI) on the spontaneous variability of the simultaneously recorded arterial pressure (AP) and renal sympathetic nerve activity (SNA) in conscious rats. Acute DMI administration (2 mg/kg iv) depressed AP Mayer waves (∼0.4 Hz) and increased low-frequency (<0.2 Hz) components of AP variability. DMI decreased renal SNA variability, especially due to the abolition of oscillations related to Mayer waves. To examine whether DMI-induced changes in AP and renal SNA variabilities could be explained by alterations in the dynamic characteristics of the baroreceptor reflex loop, the frequency responses of mean AP to aortic depressor nerve stimulation were studied in urethan-anesthetized rats. DMI accentuated the low-pass filter properties of the transfer function without significantly altering the fixed time delay. The frequency responses of iliac vascular conductance to stimulation of the lumbar sympathetic chain were studied in an additional group of anesthetized rats. DMI did not markedly alter the low-pass filter properties of the transfer function and slightly increased the fixed time delay. These results suggest that the DMI-induced decrease in the dynamic gain of the baroreceptor reflex is responsible for the decreased spontaneous renal SNA variability and the accompanying increased AP variability. The “slowing down” of baroreflex responses cannot be attributed to an effect of DMI at the vascular neuroeffector junction.

ANALYSIS AND IMPROVEMENT TECHNIQUES FOR THE TRANSFER FUNCTION OF A PLANAR LOW - PASS FILTER

2016 ◽  
Vol 15 (12) ◽  
pp. 2579-2586
Author(s):  
Adina Racasan ◽  
Calin Munteanu ◽  
Vasile Topa ◽  
Claudia Pacurar ◽  
Claudia Hebedean
Keyword(s):  
Transfer Function ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

scholarly journals Study of modular transfer function-based optieal low-pass filter evaluation model and experiment

2008 ◽  
Vol 57 (5) ◽  
pp. 2854
Author(s):  
Qi Xun-Jun ◽  
Lin Bin ◽  
Cao Xiang-Qun ◽  
Chen Yu-Qing
Keyword(s):  
Transfer Function ◽  
Evaluation Model ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

Parietal Representation of Hand Velocity in a Copy Task

2005 ◽  
Vol 93 (1) ◽  
pp. 508-518 ◽  
Author(s):  
Bruno B. Averbeck ◽  
Matthew V. Chafee ◽  
David A. Crowe ◽  
Apostolos P. Georgopoulos
Keyword(s):  
Transfer Function ◽  
Linear Model ◽  
Parietal Cortex ◽  
Neural Activity ◽  
Nonlinear Models ◽  
Linear Representation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Filter Width ◽  
Low Pass

We recorded neural activity from ensembles of neurons in areas 5 and 2 of parietal cortex, while two monkeys copied triangles, squares, trapezoids, and inverted triangles and used both linear and nonlinear models to predict the hand velocity from the neural activity of the ensembles. The linear model generally outperformed the nonlinear model, suggesting a reasonably linear relation between the neural activity and the hand velocity. We also found that the average transfer function of the linear model fit to individual cells was a low-pass filter because the neural response had considerable high-frequency power, whereas the hand velocity only had power at frequencies below ∼5 Hz. Increasing the width of the transfer function, up to a width of 700–800 ms, improved the fit of the model. Furthermore, the Rsqr of the linear model improved monotonically with the number of cells in the ensemble, saturating at 60–80% for a filter width of 700 ms. Finally, it was found that including an interaction term, which allowed the transfer function to shift with the eye position, did not improve the fit of the model. Thus ensemble neural responses in superior parietal cortex provide a high-fidelity, linear representation of hand kinematics within our task.

Digital All-Pass Filter Modeling Based on Desired Group Delay Using Advanced Material: A Review on the Signal Processing Part

2015 ◽  
Vol 815 ◽  
pp. 338-342
Author(s):  
Faizah Abu Bakar ◽  
Sohiful Anuar Zainol Murad ◽  
Rizalafande Che Ismail ◽  
Muzamir Isa
Keyword(s):  
Transfer Function ◽  
Group Delay ◽  
Sampling Frequency ◽  
Bilinear Transformation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Phase Type ◽  
Low Pass ◽  
Group Delays ◽  
Delay Variation

This paper presents a review on three types of techniques in designing digital all-pass filters based on group delay. All the three methods use the same basic concept rooting back to the requirement of a stable transfer function of the filter which should be a minimum-phase type, and the denominator group delay. The most optimized of the three is chosen to be implemented in MATLAB in order to decrease the group delay variation of a 5th order Chebyshev low-pass filter with cut-off frequency of 160 MHz. The digital transfer function of the low-pass filter is obtained from the analog transfer function by means of bilinear transformation. The sampling frequency of the digital LPF is 100 times the cut-off ffrequency to retain the response of the analog LPF. Both of the filters are then cascaded together and the overall group delays variations are analyzed. The variations of group delay shows a reduction but the price paid is the increase of the overall group delay of the system.

A 2nd-Order Continuous Time Delta-Sigma Modulator for Photoplethysmography Analog Front-End

2020 ◽  
Author(s):  
Eka Fitrah Pribadi ◽  
Rajeev Kumar Pandey ◽  
Paul C.-P. Chao
Keyword(s):  
Transfer Function ◽  
Continuous Time ◽  
Supply Voltage ◽  
Signal To Noise Ratio ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Delta Sigma Modulator ◽  
Delta Sigma ◽  
Low Pass ◽  
Order Continuous

Abstract A brief presents a 2nd order continuous-time delta-sigma modulator (CT-DSM) using a low pass filter to reduce the slew rate requirement of the output swing of the first integrator. By adding the low pass filter, the desired transfer function of the CT-DSM is altered. Thus a feed-forward based compensation circuit is introduced to transform the altered transfer function to the original condition. The CT-DSM is designed with a bandwidth of 100 Hz to satisfy the requirement of photoplethysmogram (PPG) detection. The CT-DSM is simulated using CMOS 180 nm technology with the layout area 460 μm × 460 μm. The circuit uses a 1.8 V supply voltage and consumes 35.61 μW. The signal-to-noise ratio of the CT-DSM is 101.2 dB, while the SFDR is 99.1 dB.

Neuronal uptake affects dynamic characteristics of heart rate response to sympathetic stimulation

1999 ◽  
Vol 277 (1) ◽  
pp. R140-R146 ◽  
Author(s):  
Tsutomu Nakahara ◽  
Toru Kawada ◽  
Masaru Sugimachi ◽  
Hiroshi Miyano ◽  
Takayuki Sato ◽  
...  
Keyword(s):  
Heart Rate ◽  
Transfer Function ◽  
Lag Time ◽  
Stimulation Frequency ◽  
Neuronal Uptake ◽  
Sympathetic Stimulation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass ◽  
Dynamic Gain

Recently, studies in our laboratory involving the use of a Gaussian white noise technique demonstrated that the transfer function from sympathetic stimulation frequency to heart rate (HR) response showed dynamic characteristics of a second-order low-pass filter. However, determinants for the characteristics remain to be established. We examined the effect of an increase in mean sympathetic stimulation frequency and that of a blockade of the neuronal uptake mechanism on the transfer function in anesthetized rabbits. We found that increasing mean sympathetic stimulation frequency from 1 to 4 Hz significantly ( P < 0.01) decreased the dynamic gain of the transfer function without affecting other parameters, such as the natural frequency, lag time, or damping coefficient. In contrast, the administration of desipramine (0.3 mg/kg iv), a neuronal uptake blocking agent, significantly ( P < 0.01) decreased both the dynamic gain and the natural frequency and prolonged the lag time. These results suggest that the removal rate of norepinephrine at the neuroeffector junction, rather than the amount of available norepinephrine, plays an important role in determining the low-pass filter characteristics of the HR response to sympathetic stimulation.

scholarly journals Real-time digital signal recovery for a low-pass transfer function system with multiple complex poles

2018 ◽  
Author(s):  
Jhinhwan Lee
Keyword(s):  
Transfer Function ◽  
Real Time ◽  
Digital Signal ◽  
Signal Recovery ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Recovery Method ◽  
Noise Characteristics ◽  
Resonance Frequencies ◽  
Low Pass

In order to solve the problems of waveform distortion and signal delay by many physical and electrical systems with linear low-pass transfer characteristics with multiple complex poles, a general digital-signal-processing (DSP)-based method of real-time recovery of the original source waveform from the distorted output waveform is proposed. From the convolution kernel representation of a multiple-pole low-pass transfer function with an arbitrary denominator polynomial with real valued coefficients, it is shown that the source waveform can be accurately recovered in real time using a particular moving average algorithm with real-valued DSP computations only, even though some or all of the poles are complex. The proposed digital signal recovery method is DC-accurate and unaffected by initial conditions, transient signals, and resonant amplitude enhancement. The noise characteristics of the data recovery shows inverse of the low-pass filter characteristics. This method can be applied to most sensors and amplifiers operating close to their frequency response limits or around their resonance frequencies to accurately deconvolute the multiple-pole characteristics and to improve the overall performances of data acquisition systems and digital feedback control systems.

Bidirectional augmentation of heart rate regulation by autonomic nervous system in rabbits

1996 ◽  
Vol 271 (1) ◽  
pp. H288-H295 ◽  
Author(s):  
T. Kawada ◽  
Y. Ikeda ◽  
M. Sugimachi ◽  
T. Shishido ◽  
O. Kawaguchi ◽  
...  
Keyword(s):  
Heart Rate ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Transfer Function ◽  
Vagal Stimulation ◽  
Dynamic Interaction ◽  
Sympathetic Stimulation ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

Although the characteristics of the static interaction between the sympathetic and parasympathetic nervous systems in regulating heart rate (HR) have been well established, how the dynamic interaction modulates the HR response remains unknown. We therefore investigated dynamic interaction by estimating the transfer function from nerve stimulation to HR using a band-limited Gaussian white-noise technique. The transfer function relating dynamic sympathetic stimulation to HR had characteristics of a second-order low-pass filter. Simultaneous tonic vagal stimulation at 5 and 10 Hz increased gain of the transfer function by 55.0 +/- 40.1 and 80.7 +/- 50.5%, respectively (P < 0.05). The transfer function from dynamic vagal stimulation to HR had characteristics of a first-order low-pass filter. Simultaneous tonic sympathetic stimulation at 5 and 10 Hz increased the gain by 18.2 +/- 17.9 and 24.1 +/- 18.0%, respectively (P < 0.05). Thus interaction augmented dynamic gain bidirectionally, even though it affected mean HR antagonistically. By virtue of this interaction, the autonomic nervous system appears to extend its dynamic range of operation.

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