Effective suppression of beta oscillation in Parkinsonian state via a noisy direct delayed feedback control scheme

This work explores the function of the noisy direct delayed feedback(NDDF)control strategy in suppressing the pathological oscillations in the basal ganglia(BG)with Parkinson’s disease(PD).Deep brain stimulation(DBS)alleviates the PD state fantastically.However,due to its unclear mechanism and open-loop characteristic,it is challenging to further improve its effects with lower energy expenditure.The noise stimulus performs competitively in alleviating the PD state theoretically,but it cannot adapt to the neural condition timely and automatically due to its open-loop control scheme.The direct delayed feedback(DDF)control strategy is able to disturb excessive synchronous effectively.Therefore,the NDDF control strategy is proposed and researched based on a BG computational model,which can reflect the intrinsic properties of the BG neurons and their connections with thalamic neurons.Simulation results show that the NDDF control strategy with optimal parameters is effective in removing the pathological beta oscillations.By comparison,we find the NDDF control strategy performs more excellent than DDF in alleviating PD state.Additionally,we define the multiple-NDDF control strategy and find that the multiple-NDDF with appropriate parameters performs better than NDDF.The obtained results contribute to the cure for PD symptoms by optimizing the noise-induced improvement of the BG dysfunction.     

Closed-loop control of epileptiform activities in a neural population model using a proportional-derivative controller

Epilepsy is believed to be caused by a lack of balance between excitation and inhibitation in the brain. A promising strategy for the control of the disease is closed-loop brain stimulation. How to determine the stimulation control parameters for effective and safe treatment protocols remains, however, an unsolved question. To constrain the complex dynamics of the biological brain, we use a neural population model(NPM). We propose that a proportional-derivative(PD) type closed-loop control can successfully suppress epileptiform activities. First, we determine the stability of root loci, which reveals that the dynamical mechanism underlying epilepsy in the NPM is the loss of homeostatic control caused by the lack of balance between excitation and inhibition. Then, we design a PD type closed-loop controller to stabilize the unstable NPM such that the homeostatic equilibriums are maintained; we show that epileptiform activities are successfully suppressed. A graphical approach is employed to determine the stabilizing region of the PD controller in the parameter space, providing a theoretical guideline for the selection of the PD control parameters. Furthermore, we establish the relationship between the control parameters and the model parameters in the form of stabilizing regions to help understand the mechanism of suppressing epileptiform activities in the NPM. Simulations show that the PD-type closed-loop control strategy can effectively suppress epileptiform activities in the NPM.     

Pattern transition and regulation in a subthalamopallidal network under electromagnetic effect

Although the significant roles of magnetic induction and electromagnetic radiation in the neural system have been widely studied, their influence on Parkinson's disease (PD) has yet to be well explored. By virtue of the magnetic flux variable, this paper studies the transition of firing patterns induced by magnetic induction and the regulation effect of external magnetic radiation on the firing activities of the subthalamopallidal network in basal ganglia. We find: (i) The network reproduces five typical waveforms corresponding to the severity of symptoms: weak cluster, episodic, continuous cluster, episodic, and continuous wave. (ii) Magnetic induction is a double-edged sword for the treatment of PD. Although the increase of magnetic coefficient may lead the physiological firing activity to transfer to pathological firing activity, it also can regulate the pathological intensity firing activity with excessive β-band power transferring to the physiological firing pattern with weak β-band power. (iii) External magnetic radiation could inhibit continuous tremulous firing and β-band power of subthalamic nucleus (STN), which means the severity of symptoms weakened. Especially, the bi-parameter plane of the regulation region shows that a short pulse period of magnetic radiation and a medium level of pulse percentage can well regulate pathological oscillation. This work helps to understand the firing activity of the subthalamopallidal network under electromagnetic effect. It may also provide insights into the mechanisms behind the electromagnetic therapy of PD-related firing activity.     

基于单片机的温度控制系统的设计

针对单片机温度控制系统采用传统控制方法容易出现响应速度慢、振荡剧烈、控制精度低等问题,对单片机温度控制系统的硬件电路、控制精度、控制算法等方面进行了设计研究。基于以AT89C51单片机为核心运用DS18B20温度传感器的温度控制系统,提出了变论域模糊PID控制算法,将变论域模糊控制和PID控制相结合,结合生猪猪舍温度控制系统对传统PID控制算法以及变论域模糊PID控制进行对比分析。实验结果表明,设计的温度控制系统采用了变论域模糊PID控制算法,提高了控制精度,加快了系统的响应速度,从而增强了温度控制系统的实用性,产生了重要的实际工程意义。     

混沌系统的变论域模糊控制算法研究

混沌运动和混沌控制受到广泛关注,本文利用模糊控制实现混沌系统的控制.针对模糊控制器精度不高,模糊控制中规则数量与控制精度之间的矛盾,提出了一种基于蚁群优化算法的变论域模糊控制器.通过分析变论域模糊控制中的2类伸缩因子,指出其中1类并不能满足广义伸缩因子条件.提出利用蚁群优化算法对伸缩因子智能寻优的方法,在对蚁群算法改进的基础上,构成一种基于蚁群算法的变论域模糊控制,将设计的控制器用于Duffing混沌系统的控制.仿真结果表明,提出的控制算法在收敛速度和稳态性能上要略优于其他控制方式. 关键词： 混沌 变论域模糊控制 伸缩因子 蚁群优化算法     

The variable, fractional-order discrete-time PD controller in the IISv1.3 robot arm control

In this paper, the discrete differentiation order functions of the variable, fractional-order PD controller (VFOPD) are considered. In the proposed VFOPD controller, a variable, fractional-order backward difference is applied to perform closed-loop, system error, discrete-time differentiation. The controller orders functions which may be related to the controller input or output signal or an input and output signal. An example of the VFOPD controller is applied to the robot arm closed-loop control due to system changes in moment of inertia. The close-loop system step responses are presented.     

Intermittent synchronization in a network of bursting neurons

Synchronized oscillations in networks of inhibitory and excitatory coupled bursting neurons are common in a variety of neural systems from central pattern generators to human brain circuits. One example of the latter is the subcortical network of the basal ganglia, formed by excitatory and inhibitory bursters of the subthalamic nucleus and globus pallidus, involved in motor control and affected in Parkinson's disease. Recent experiments have demonstrated the intermittent nature of the phase-locking of neural activity in this network. Here, we explore one potential mechanism to explain the intermittent phase-locking in a network. We simplify the network to obtain a model of two inhibitory coupled elements and explore its dynamics. We used geometric analysis and singular perturbation methods for dynamical systems to reduce the full model to a simpler set of equations. Mathematical analysis was completed using three slow variables with two different time scales. Intermittently, synchronous oscillations are generated by overlapped spiking which crucially depends on the geometry of the slow phase plane and the interplay between slow variables as well as the strength of synapses. Two slow variables are responsible for the generation of activity patterns with overlapped spiking, and the other slower variable enhances the robustness of an irregular and intermittent activity pattern. While the analyzed network and the explored mechanism of intermittent synchrony appear to be quite generic, the results of this analysis can be used to trace particular values of biophysical parameters (synaptic strength and parameters of calcium dynamics), which are known to be impacted in Parkinson's disease.     

基于模糊控制的 VSVPWM 中点电位平衡策略

针对中点钳位型(NPC)三电平逆变器存在的直流侧中点电位不平衡问题,提出了一种基于模糊控制 的中点电位平衡策略。该策略重新定义了虚拟空间矢量,使虚拟小矢量不引起中点电位波动,并在虚拟中矢量中 引入了对中点电位不平衡有抑制作用的控制因子 Q。同时,设计了由模糊控制器 A 和 B 构成的组合模糊控制器, 该控制器能够依据中点电位偏移情况调整控制因子 Q,实现对中点电位的闭环控制。仿真和实验结果表明,采用 该策略的 NPC 型三电平逆变器中点电位不平衡问题能得到有效改善。     

变论域模糊控制器单元机组SCR烟气脱硝控制研究

SCR烟气脱硝系统的脱硝率由喷氨量来控制,而喷氨流量控制系统控制喷氨量,因此,优化喷氨流量控制系统能有效提高脱硝率。设计了一种基于变论域的模糊控制器来实现喷氨量的优化控制,并采用 MATLAB 仿真软件对此控制方案进行仿真,并与传统的控制方案的结果进行对比分析。结果表明,基于变论域的模糊控制喷氨流量系统相对于传统的PID控制,其超调小,且鲁棒性较强,有效地提高了控制品质。     

A new quantitative evaluation method of spiral drawing for patients with Parkinson’s disease based on a polar coordinate system with varying origin

Parkinson’s disease (PD) is a common disease of the central nervous system among the elderly, and its complex symptoms bring up challenges for the clinical diagnosis. In this paper, a new method based on a polar coordinate system with varying origin was proposed in order to quantitatively evaluate the performance in spiral drawing tasks for patients with Parkinson’s disease, since this method can assess the movement ability of spiral drawing before and after deep brain stimulation (DBS) among the patients. In this paper, three normal subjects and twelve PD patients participated in spiral drawing experiment. The hand movements of patients, before and after DBS, were recorded by a digitized tablet respectively in this experiment. And the variation of origin, radius, degree and other characteristics of hand movements were evaluated by introducing a set of parameters for feature extraction. The result showed that the proposed polar coordinate system embraced good performance in the quantitative evaluation of spiral drawing. Therefore, the proposed method overcame the limitation of data processes with fixed origin for diagnosis and evaluation, and by combining with extraction and analysis of characteristic parameters it had clinical significance in measuring the effectiveness of operation or treatment for the PD patients.     

神经群模型中癫痫状棘波的闭环控制性能研究

神经群模型可模拟产生癫痫发作间歇期、发作前期和发作期的脑电信号.本文基于代数估计法,给出一种新型的闭环反馈控制策略以消除神经群模型中的癫痫状棘波.代数估计法用以观测模型中的状态以进一步构造控制器.在多个神经群耦合的模型中,通过数值仿真研究了与所给的闭环反馈控制策略相关的一些特性,包括受控神经群的类型与消除棘波的能力之间的关系、受控神经群的数目与控制能量之间的关系、模型的参量和控制能量之间的关系,以期建立合适的控制规则实现利用尽可能小的控制能量消除癫痫状棘波.此外,通过数值仿真对基于代数估计法的闭环反馈控制策略和直接比例反馈控制策略进行比较,结果表明,利用代数估计法进行滤波能减少消除癫痫状棘波所需的控制能量.     

基于自适应模糊控制的分数阶混沌系统同步

本文主要研究了带有未知外界扰动的分数阶混沌系统的同步问题.基于分数阶Lyapunov稳定性理论,构造了分数阶的参数自适应规则以及模糊自适应同步控制器.在稳定性分析中主要使用了平方Lyapunov函数.该控制方法可以实现两分数阶混沌系统的同步,使得同步误差渐近趋于0.最后,数值仿真结果验证了本文方法的有效性.     

Analysis of a phase synchronized functional network based on the rhythm of brain activities

Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this paper develops a new method of constructing functional network based on phase synchronization. Electroencephalogram (EEG) data were collected while subjects looking at a green cross in two states, performing an attention task and relaxing with eyes-open. The EEG from these two states was filtered by three band-pass filters to obtain signals of theta (4--7 Hz), alpha (8--13 Hz) and beta (14--30 Hz) bands. Mean resultant length was used to estimate strength of phase synchronization in three bands to construct networks of both states, and mean degree K and cluster coefficient C of networks were calculated as a function of threshold. The result shows higher cluster coefficient in the attention state than in the eyes-open state in all three bands, suggesting that cluster coefficient reflects brain state. In addition, an obvious fronto-parietal network is found in the attention state, which is a well-known attention network. These results indicate that attention modulates the fronto-parietal connectivity in different modes as compared with the eyes-open state. Taken together this method is an objective and important tool to study the properties of neural networks of brain rhythm.     

Dynamics of Parkinsonian tremor during deep brain stimulation

The mechanism by which chronic, high frequency, electrical deep brain stimulation (HF-DBS) suppresses tremor in Parkinson's disease is unknown. Rest tremor in subjects with Parkinson's disease receiving HF-DBS was recorded continuously throughout switching the deep brain stimulator on (at an effective frequency) and off. These data suggest that the stimulation induces a qualitative change in the dynamics, called a Hopf bifurcation, so that the stable oscillations are destabilized. We hypothesize that the periodic stimulation modifies a parameter affecting the oscillation in a time dependent way and thereby induces a Hopf bifurcation. We explore this hypothesis using a schematic network model of an oscillator interacting with periodic stimulation. The mechanism of time-dependent change of a control parameter in the model captures two aspects of the dynamics observed in the data: (1) a gradual increase in tremor amplitude when the stimulation is switched off and a gradual decrease in tremor amplitude when the stimulation is switched on and (2) a time delay in the onset and offset of the oscillations. This mechanism is consistent with these rest tremor transition data and with the idea that HF-DBS acts via the gradual change of a network property. (c) 2001 American Institute of Physics.     

Changes in vocal intensity in Parkinson''s disease following pallidotomy surgery

The present study was designed to examine changes in vocal intensity following unilateral posteroventral pallidotomy (PVP) in a large sample of speakers with Parkinson's disease (PD) that exhibited a range of hypokinetic dysarthria. Twenty-five persons with PD were recorded using a variety of speech tasks, once prior to and once following PVP. The pre-PVP vocal SPL was subtracted from the post-PVP vocal SPL to derive a relative change in vocal SPL. Mildly dysarthric participants had significantly greater relative increases in vocal SPL following PVP than either moderately or severely dysarthric participants who had reduced vocal SPL following PVP. If future results follow those observed in the present data, mildly dysarthric Parkinson's patients may benefit most from unilateral PVP perhaps due to less overall destruction of the basal ganglia sensorimotor control circuits involved in oral facial functions, thus increasing the chances to observe improvements postsurgery.     

Cerebral abnormalities in Wilson''s disease as evaluated by ultra-low-field magnetic resonance imaging and computerized image processing

The cerebral involvement of a 13-yr-old boy with Wilson's disease was serially evaluated during the first 18 mo of D-penicillamine treatment. An ultra-low-field magnetic resonance imaging (ULF MRI) system, operating at 0.02 T, with computerized image processing was used. The half-yr period prior to the clinical diagnosis was set, the patient had showed poor school performance, emotional lability, deteriorating handwriting, progressively slow, gross, and fine motor functions, and a fixed rigid smile. No overt signs of liver disease were found. With D-penicillamine treatment (1–1.5 g/d) a continuous improvement was seen. The pretreatment MRI investigation showed pronounced pathological transformation in the basal ganglia. However, changes were seen also in most other parts of the brain indicating diffuse involvement. During treatment the computerized MR images became gradually more normal. The current magnetic resonance imaging system with computerized image processing is a sensitive and simple method for evaluation of subtle parenchymal changes of the brain.     

Vibration suppression control of smart piezoelectric rotating truss structure by parallel neuro-fuzzy control with genetic algorithm tuning

The main goal of this paper is to develop a novel approach for vibration control on a piezoelectric rotating truss structure. This study will analyze the dynamics and control of a flexible structure system with multiple degrees of freedom, represented in this research as a clamped–free–free–free truss type plate rotated by motors. The controller has two separate feedback loops for tracking and damping, and the vibration suppression controller is independent of position tracking control. In addition to stabilizing the actual system, the proposed proportional–derivative (PD) control, based on genetic algorithm (GA) to seek the primary optimal control gain, must supplement a fuzzy control law to ensure a stable nonlinear system. This is done by using an intelligent fuzzy controller based on adaptive neuro-fuzzy inference system (ANFIS) with GA tuning to increase the efficiency of fuzzy control. The PD controller, in its assisting role, easily stabilized the linear system. The fuzzy controller rule base was then constructed based on PD performance-related knowledge. Experimental validation for such a structure demonstrates the effectiveness of the proposed controller. The broad range of problems discussed in this research will be found useful in civil, mechanical, and aerospace engineering, for flexible structures with multiple degree-of-freedom motion.     

Occupational prolonged organic solvent exposure in shoemakers: brain MR spectroscopy findings

Our purpose was to investigate, by magnetic resonance (MR) spectroscopy, the metabolite changes in the brains of subjects in the shoemaking industry who had been chronically exposed to organic solvents. A total of 49 male subjects and 30 age-matched healthy volunteers underwent detailed neurological and psychiatric examinations. All subjects had long-echo [repetition time (TR) 2000 ms, echo time (TE) 136 ms] single-voxel MR spectroscopy. Voxels (15 x 15 x 15 mm(3)) were placed in the parietal white matter, thalamus, and basal ganglia. N-acetylaspartate (NAA)/creatine (Cr) and choline (Cho)/Cr ratios were calculated. There was no significant difference between the study subjects and the control group in NAA/Cr ratios obtained from thalamus, basal ganglia, and parietal white matter. Cho/Cr ratios in thalamus, basal ganglia, and parietal white matter were found to be significantly increased compared to controls. There was a positive correlation between basal ganglia Cho/Cr ratio and duration of exposure (r = 0.63). MR spectroscopy should be performed to reveal metabolite changes and determine the degree of brain involvement in solvent-related industry workers.     

Iron in typical and atypical parkinsonism – Mössbauer spectroscopy and MRI studies

Iron may play important role in neurodegeneration. The results of comparative studies of human brain areas (control and pathological) performed by Mössbauer spectroscopy (MS) and magnetic resonance imaging (MRI) techniques are presented. Mössbauer spectroscopy demonstrated a higher concentration of iron in atypical parkinsonism (progressive supranuclear palsy PSP) in the brain areas Substantia Nigra (SN) and Globus Pallidus (GP) involved in this pathological process, compared to control, while the concentration of iron in pathological tissues in typical parkinsonism (Parkinson’s disease - PD) did not differ from that in control. These results were compared with the changes in 1/T1 and 1/T2 (T1 and T2 being the relaxation times determined by MRI). A good linear correlation curve was found between the concentration of iron as determined by MS in different areas of control human brains and between 1/T1 and 1/T2. Whereas the finding in PSP-GP (the brain area involved in PSP) also fitted to such a correlation, this was not so for the correlation between pathological SN – the brain area involved in both diseases – and 1/T2, indicating a dependence of T2 on other factors than just the concentration of iron.     

Cosmological implications of observable neutron-antineutron oscillations

A wide class of gauge theoretical models allowing for observable neutron-antineutron oscillations predict no baryon asymmetry in the present universe. This is to be traced back to the existence of baryon-violating interactions in equilibrium at the characteristic mass scale of neutron-antineutron oscillations. Then, we show how these models can be modified in such a way that a very late cosmological baryon asymmetry survives in the today universe. Specifically, we consider two recently proposed baryon-production mechanisms, one of which can be naturally embedded in a grand unification scheme and can lead to observable nucleon decay processes occurring only throughB-L violating butB+L conserving channels.