Closed-loop low-frequency DBS restores thalamocortical relay fidelity in a computational model of the motor loop

2017 ◽  
Author(s):  
Han D. Huang ◽  
Sabato Santaniello
Keyword(s):  
Computational Model ◽  
Closed Loop ◽  
Low Frequency ◽  
Motor Loop

scholarly journals Isotropic Sequence Order Learning

2003 ◽  
Vol 15 (4) ◽  
pp. 831-864 ◽  
Author(s):  
Bernd Porr ◽  
Florentin Wörgötter
Keyword(s):  
Weight Change ◽  
Closed Loop ◽  
Learning Algorithm ◽  
Linear Structure ◽  
Open Loop ◽  
Learning System ◽  
Behavioral Paradigm ◽  
Motor Loop ◽  
Loop Condition ◽  
Spike Time Dependent Plasticity

In this article, we present an isotropic unsupervised algorithm for temporal sequence learning. No special reward signal is used such that all inputs are completely isotropic. All input signals are bandpass filtered before converging onto a linear output neuron. All synaptic weights change according to the correlation of bandpass-filtered inputs with the derivative of the output. We investigate the algorithm in an open- and a closed-loop condition, the latter being defined by embedding the learning system into a behavioral feedback loop. In the open-loop condition, we find that the linear structure of the algorithm allows analytically calculating the shape of the weight change, which is strictly heterosynaptic and follows the shape of the weight change curves found in spike-time-dependent plasticity. Furthermore, we show that synaptic weights stabilize automatically when no more temporal differences exist between the inputs without additional normalizing measures. In the second part of this study, the algorithm is is placed in an environment that leads to closed sensor-motor loop. To this end, a robot is programmed with a prewired retraction reflex reaction in response to collisions. Through isotropic sequence order (ISO) learning, the robot achieves collision avoidance by learning the correlation between his early range-finder signals and the later occurring collision signal. Synaptic weights stabilize at the end of learning as theoretically predicted. Finally, we discuss the relation of ISO learning with other drive reinforcement models and with the commonly used temporal difference learning algorithm. This study is followed up by a mathematical analysis of the closed-loop situation in the companion article in this issue, “ISO Learning Approximates a Solution to the Inverse-Controller Problem in an Unsupervised Behavioral Paradigm” (pp. 865–884).

scholarly journals Selection of stimulus parameters for enhancing slow wave sleep events with a Neural-field theory thalamocortical computational model

2021 ◽  
Author(s):  
Felipe A. Torres ◽  
Patricio Orio ◽  
María-José Escobar
Keyword(s):  
Computational Model ◽  
Slow Wave ◽  
Memory Consolidation ◽  
Closed Loop ◽  
Slow Wave Sleep ◽  
Brain Activity ◽  
Sensory Stimulation ◽  
Sleep Spindles ◽  
Slow Oscillations ◽  
Closed Loop Stimulation

AbstractSlow-wave sleep cortical brain activity, conformed by slow-oscillations and sleep spindles, plays a key role in memory consolidation. The increase of the power of the slow-wave events, obtained by auditory sensory stimulation, positively correlates to memory consolidation performance. However, little is known about the experimental protocol maximizing this effect, which could be induced by the power of slow-oscillation, the number of sleep spindles, or the timing of both events’ co-occurrence. Using a mean-field model of thalamocortical activity, we studied the effect of several stimulation protocols, varying the pulse shape, duration, amplitude, and frequency, as well as a target-phase using a closed-loop approach. We evaluated the effect of these parameters on slow-oscillations (SO) and sleep-spindles (SP), considering: (i) the power at the frequency bands of interest, (ii) the number of SO and SP, (iii) co-occurrences between SO and SP, and (iv) synchronization of SP with the up-peak of the SO. The first three targets are maximized using a decreasing ramp pulse with a pulse duration of 50 ms. Also, we observed a reduction in the number of SO when increasing the stimulus energy by rising its amplitude. To assess the target-phase parameter, we applied closed-loop stimulation at 0º, 45º, and 90º of the phase of the narrow-band filtered ongoing activity, at 0.85 Hz as central frequency. The 0º stimulation produces better results in the power and number of SO and SP than the rhythmic or aleatory stimulation. On the other hand, stimulating at 45º or 90º change the timing distribution of spindles centers but with fewer co-occurrences than rhythmic and 0º phase. Finally, we propose the application of closed-loop stimulation at the rising zero-cross point using pulses with a decreasing ramp shape and 50 ms of duration for future experimental work.Author summaryDuring the non-REM (NREM) phase of sleep, events that are known as slow oscillations (SO) and spindles (SP) can be detected by EEG. These events have been associated with the consolidation of declarative memories and learning. Thus, there is an ongoing interest in promoting them during sleep by non-invasive manipulations such as sensory stimulation. In this paper, we used a computational model of brain activity that generates SO and SP, to investigate which type of sensory stimulus –shape, amplitude, duration, periodicity– would be optimal for increasing the events’ frequency and their co-occurrence. We found that a decreasing ramp of 50 ms duration is the most effective. The effectiveness increases when the stimulus pulse is delivered in a closed-loop configuration triggering the pulse at a target phase of the ongoing SO activity. A desirable secondary effect is to promote SPs at the rising phase of the SO oscillation.

scholarly journals Reduced-Order Computational Model for Low-Frequency Dynamics of Automobiles

2013 ◽  
Vol 5 ◽  
pp. 310362
Author(s):  
A. Arnoux ◽  
C. Soize ◽  
A. Batou ◽  
L. Gagliardini
Keyword(s):  
Computational Model ◽  
Low Frequency ◽  
Reduced Order

scholarly journals Effect of Closed-Loop Vibration Stimulation on Heart Rhythm during Naps

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4136 ◽  
Author(s):  
Sang Ho Choi ◽  
Heenam Yoon ◽  
Hyung Won Jin ◽  
Hyun Bin Kwon ◽  
Seong Min Oh ◽  
...  
Keyword(s):  
High Frequency ◽  
Closed Loop ◽  
Low Frequency ◽  
Heart Rhythm ◽  
Quality Of Sleep ◽  
Stimulation Condition ◽  
Term Basis ◽  
Stimulation System

Sleep plays a primary function for health and sustains physical and cognitive performance. Although various stimulation systems for enhancing sleep have been developed, they are difficult to use on a long-term basis. This paper proposes a novel stimulation system and confirms its feasibility for sleep. Specifically, in this study, a closed-loop vibration stimulation system that detects the heart rate (HR) and applies −n% stimulus beats per minute (BPM) computed on the basis of the previous 5 min of HR data was developed. Ten subjects participated in the evaluation experiment, in which they took a nap for approximately 90 min. The experiment comprised one baseline and three stimulation conditions. HR variability analysis showed that the normalized low frequency (LF) and LF/high frequency (HF) parameters significantly decreased compared to the baseline condition, while the normalized HF parameter significantly increased under the −3% stimulation condition. In addition, the HR density around the stimulus BPM significantly increased under the −3% stimulation condition. The results confirm that the proposed stimulation system could influence heart rhythm and stabilize the autonomic nervous system. This study thus provides a new stimulation approach to enhance the quality of sleep and has the potential for enhancing health levels through sleep manipulation.

Closed-loop system disturbance recovery

2003 ◽  
Vol 217 (6) ◽  
pp. 631-649 ◽  
Author(s):  
R Whalley ◽  
M Ebrahimi
Keyword(s):  
Closed Loop ◽  
Low Frequency ◽  
Closed Loop Control ◽  
Multivariable System ◽  
Closed Loop System ◽  
Outer Loop ◽  
Loop Control ◽  
Passive Network ◽  
Loop Tuning ◽  
Reference Input

The regulation of linearized multivariable system models, following input set point and load disturbance changes, is considered. An inner and outer closed-loop control strategy is outlined, enabling targeted recovery rates, offset attenuation and low steady state interaction to be achieved. Proportional control and passive network compensation alone are employed. Gain ratio selection and outer loop tuning are exercised, ensuring thereby the confinement of output perturbations to low-frequency load disturbances and reference input changes. Application studies are presented for purposes of comparison.

Parallel Cortico-Basal Ganglia Mechanisms for Acquisition and Execution of Visuomotor Sequences—A Computational Approach

2001 ◽  
Vol 13 (5) ◽  
pp. 626-647 ◽  
Author(s):  
Hiroyuki Nakahara ◽  
Kenji Doya ◽  
Okihide Hikosaka
Keyword(s):  
Basal Ganglia ◽  
Computational Model ◽  
Time Course ◽  
Anterior Part ◽  
Experimental Studies ◽  
Procedural Learning ◽  
Motor Area ◽  
Brain Areas ◽  
Motor Loop ◽  
The Coordinator

Experimental studies have suggested that many brain areas, including the basal ganglia (BG), contribute to procedural learning. Focusing on the basal ganglia-thalamo-cortical (BG-TC) system, we propose a computational model to explain how different brain areas work together in procedural learning. The BG-TC system is composed of multiple separate loop circuits. According to our model, two separate BG-TC loops learn a visuomotor sequence concurrently but using different coordinates, one visual, and the other motor. The visual loop includes the dorsolateral prefrontal (DLPF) cortex and the anterior part of the BG, while the motor loop includes the supplementary motor area (SMA) and the posterior BG. The concurrent learning in these loops is based on reinforcement signals carried by dopaminergic (DA) neurons that project divergently to the anterior (“visual”) and posterior (“motor”) parts of the striatum. It is expected, however, that the visual loop learns a sequence faster than the motor loop due to their different coordinates. The difference in learning speed may lead to inconsistent outputs from the visual and motor loops, and this problem is solved by a mechanism called a “coordinator,” which adjusts the contribution of the visual and motor loops to a final motor output. The coordinator is assumed to be in the presupplementary motor area (pre-SMA). We hypothesize that the visual and motor loops, with the help of the coordinator, achieve both the quick acquisition of novel sequences and the robust execution of well-learned sequences. A computational model based on the hypothesis is examined in a series of computer simulations, referring to the results of the 2 × 5 task experiments that have been used on both monkeys and humans. We found that the dual mechanism with the coordinator was superior to the single (visual or motor) mechanism. The model replicated the following essential features of the experimental results: (1) the time course of learning, (2) the effect of opposite hand use, (3) the effect of sequence reversal, and (4) the effects of localized brain inactivations. Our model may account for a common feature of procedural learning: A spatial sequence of discrete actions (subserved by the visual loop) is gradually replaced by a robust motor skill (subserved by the motor loop).

Statistical Considerations on Pressure Pulses from a Cavitating Venturi

1986 ◽  
Vol 200 (6) ◽  
pp. 381-387
Author(s):  
S Li ◽  
Y Zhang ◽  
F G Hammitt
Keyword(s):  
Closed Loop ◽  
Pressure Fluctuations ◽  
Low Frequency ◽  
Resonant Interaction ◽  
Statistical Characteristics ◽  
Pressure Pulsations ◽  
Cavitation Inception ◽  
Flow Noise ◽  
Pressure Pulses ◽  
Liquid Portion

Pressure pulses emitted from cavitating venturi flows are measured and investigated statistically. The results show that according to the degree of cavitation, the overall pressure pulsations consist of different combinations of three components, that is basic flow noise, cavitation pulses and low-frequency pressure fluctuations, due primarily to overall loop characteristics. The statistical characteristics are presented and compared. It is believed that the low-frequency fluctuations result from a resonant interaction between the cavitation ‘cloud’ and the liquid portion of the closed loop. They occur near cavitation inception, reach a maximum at a particular cavitation number, σres, then gradually disappear for increased σ. Their frequency is basically constant for all σ. An empirical-theoretical model of this behaviour is presented.

Reduction Methods of Structure Models for Control System Purposes

2016 ◽  
Vol 248 ◽  
pp. 119-126 ◽  
Author(s):  
Andrzej Koszewnik ◽  
Zdzisław Gosiewski
Keyword(s):  
Control System ◽  
High Frequency ◽  
Closed Loop ◽  
Flexible Structures ◽  
Low Frequency ◽  
Point Of View ◽  
Closed Loop Systems ◽  
System A ◽  
Reduction Methods ◽  
The Stability

To design vibration control system for flexible structures their mathematical model should be reduced. In the paper we consider the influence of the model reduction on the dynamics of the real closed-loop system. A simply cantilever beam is an object of consideration since we are able to formulate the exact analytical model of such structure. As a result of reduction the model with low frequency resonances is usually separated from the high frequency dynamics because high frequency part of the model is naturally strong damped. In order to estimate dynamical system for control purposes in the paper we applied a few orthogonal methods such as: modal, Rayleigh-Ritz and Schur decompositions. As it is shown all methods well calculate resonances frequencies but generate different anti-resonances frequencies. From control strategy in point of view of the flexible structures these anti-resonances have significantly influence on the stability and dynamics of the closed-loop systems.

EXPERIMENTAL RESULTS FOR THE SMALL-SIGNAL STUDY OF THE PWM BOOST DC–DC CONVERTER WITH AN INTEGRAL-LEAD CONTROLLER

1995 ◽  
Vol 05 (04) ◽  
pp. 747-755 ◽  
Author(s):  
MARIAN K. KAZIMIERCZUK ◽  
ROBERT C. CRAVENS, II
Keyword(s):  
Closed Loop ◽  
Transfer Functions ◽  
Low Frequency ◽  
Input Voltage ◽  
Open Loop ◽  
Small Signal ◽  
Loop Control ◽  
Pulse Width Modulated ◽  
Bode Plots ◽  
Step Responses

An experimental verification of previously derived small-signal low-frequency open- and closed-loop characteristics and step responses of a voltage-mode-controlled pulse-width-modulated (PWM) boost DC–DC converter is presented. The Bode plots of the voltage transfer function of the control circuit, the converter and the PWM modulator, the open-loop control-to-output and input-to-output transfer functions, the loop gain, and the closed-loop control-to-output and input-to-output transfer functions are measured. The step responses to the changes in the input voltage, the duty cycle, and the reference voltage are measured. The theoretical results were in good agreement with the measured results. The small-signal model of the converter is experimentally verified.

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