Slow Gamma Activity of Local Field Potentials (LFP) in the Freely Moving Rat Relates to Movement

Quantitative assessment of local field potentials by means of Fast Fourier Transformation (FFT) results in the so-called power density spectrum. Within this spectrum particular frequency ranges are defined in order to relate these to behavior. Frequencies above 35 Hz are generally labeled as gamma oscillations, especially as low gamma (40 - 55 Hz) or high gamma (70 - 100 Hz). In order to learn more about this feature, we implanted a set of 4 bipolar concentric steel electrodes in frontal cortex, hippocampus, striatum and midbrain reticular formation of 10 rats. After recovery, field potentials were recorded and wirelessly transmitted to our computer for frequency analysis. At the same time, motion was registered during the whole experimental period of 5.75 hours. Results revealed that low gamma activity only emerged when the animal moved—at least his head. FFT of the data showed—besides other frequencies—a slow gamma activity peaking around 47 Hz pre-dominantly within the striatum, less in frontal cortex and reticular formation and nearly none in the hippocampus. Spectral analysis was performed for single epochs of 4 seconds and all 15 minutes intervals. Correlation analysis of these intervals was done to motion data. All rats showed a highly significant correlation between gamma activity and movement. We therefore conclude from these experiments that this slow gamma activity of the field potentials is not only related to movement, but possibly part of the general neuronal coding of movement.

Hippocampal ischemia causes deficits in local field potential and synaptic plasticity

The long-term enhancement in glutamate receptor mediated excitatory responses has been observed in stroke model. This pathological form of plasticity, termed post-ischemic long-term potentiation （i-LTP）, points to functional reorganization after stroke. Little is known, however, about whether and how this i-LTP would affect subsequent induction of synaptic plasticity. Here, we first directly confirmed that i-LTP was induced in the endothelin-l-induced ischemia model as in other in vitro models. We also demonstrated increased expression of NR2B, CaMKII and p-CaMKII, which are reminiscent of i-LTP. We further induced LTP of field excitatory post- synaptic potentials （fEPSPs） on CA1 hippocampal neurons in peri-infarct regions of the endothelin-l-induced mini-stroke model. We found that LTP of fEPSPs, induced by high-frequency stimulation, displayed a progressive impairment at 12 and 24 hours after ischemia. Moreover, using in vivo multi-channel recording, we found that the local field potential, which represents electrical property of cell ensembles in more restricted regions, was also dam- pened at these two time points. These results suggest that i-LTP elevates the induction threshold of subsequent synap- tic plasticity. Our data helps to deepen the knowledge of meta-synaptic regulation of plasticity after focal ischemia.

Virtual local target method for avoiding local minimum in potential field based robot navigation

A novel robot navigation algorithm with global path generation capability is presented. Local minimum is a most intractable but is an encountered frequently problem in potential field based robot navigation.Through appointing appropriately some virtual local targets on the journey, it can be solved effectively. The key concept employed in this algorithm are the rules that govern when and how to appoint these virtual local targets. When the robot finds itself in danger of local minimum, a virtual local target is appointed to replace the global goal temporarily according to the rules. After the virtual target is reached, the robot continues on its journey by heading towards the global goal. The algorithm prevents the robot from running into local minima anymore. Simulation results showed that it is very effective in complex obstacle environments.

The role of local field potential coupling in epileptic synchronization

This review hopes to clearly explain the following viewpoints： （1） Neuronal synchronization underlies brain functioning, and it seems possible that blocking excessive synchronization in an epileptic neural network could reduce or even control seizures. （2） Local field potential coupling is a very common phenomenon during synchronization in networks. Removal of neurons or neuronal networks that are coupled can significantly alter the extracellular field potential. Interventions of coupling mediated by local field potentials could result in desynchronization of epileptic seizures. （3） The synchronized electrical activity generated by neurons is sensitive to changes in the size of the extracellular space, which affects the efficiency of field potential transmission and the threshold of cell excitability. （4） Manipulations of the field potential fluctuations could help block synchronization at seizure onset.

Effect of propofol on local field potential in rat prefrontal cortex during working memory task

Propofol may produce memory impairment during anesthesia procedure. Local field potentials (LFPs) are used with increasing frequency in recent years to link neural activity to perception and cognition. In this study, effect of propofol on LFPs in rat’s prefrontal cortex during working memory task was evaluated. Young (approximately 3 month) male Sprague-Dawley rats were divided into two group: propofol rats and control rats. Propofol rats received propofol at 0.9 mg/Kg·min intravenously for 2 h. After 12 h, LFPs of all rats were measured simultaneously from multiple electrodes placed in prefrontal cortex while rats were performing a working memory task in Y-maze. LFPs instantaneous phase were obtained by applying Hilbert transform, and cross-correlation coherence of LFPs was calculated. The results indicate that propofol decreased the correct rate and crosscorrelation coherence of LFPs on the first two days (p 0.05). Our results suggest that propofol can impair cross-correlation coherence of LFPs in the first two days, but not long time.

Effect of focused ultrasound stimulation at different ultrasonic power levels on the local field potential power spectrum

Local field potential(LFP) signals of the rat hippocampus were recorded under noninvasive focused ultrasound stimulation(FUS) with different ultrasonic powers. The LFP mean absolute power was calculated with the Welch algorithm at the delta, theta, alpha, beta, and gamma frequency bands. The experimental results demonstrate that the LFP mean absolute power at different frequency bands increases as the ultrasound power increases.

Mechanistic roles of the subthalamic nucleus and internal globus pallidus:evidence from local field potentials and deep brain stimulation

Deep brain stimulation (DBS) has become an effective therapeutic option for neurological and psychiatric disorders such as Parkinson’s disease (PD), dystonia, and obsessive-compulsive disorder. The subthalamic nucleus (STN) and internal globus pallidus (GPi) are by far the most commonly used targets for DBS in the treatment of PD. However, STN/GPi stimulation sometimes causes side effects, including motor fluctuations, cognitive declines, and worse emotional experience, which affect patients’ postoperative quality of life. Recent invasive electrophysiological studies are driven by the desire to better understand the mechanisms of therapeutic actions and side effects of STN/GPi stimulation. These studies investigated the function of the STN and GPi in motor, cognitive and affective processes by recording single- neuron firing patterns during the surgery or local field potentials after the surgery. Here we review the relevant studies to provide an integrative picture of the functional roles of the STN and GPi within the basal ganglia loops for motor, cognition, and emotion. Previous studies suggested that STN and GPi gamma oscillations encode the strength and speed of voluntary movements (execution), whereas beta oscillations reflect the effort and demand of potential movements (preparation). In the cognitive domain, oscillatory beta activity in the STN is involved when people have to stop an inappropriate action or to suppress salient but task-irrelevant information, whereas theta/delta activity is associated with the adjustment of decision thresholds and cost-benefit trade-off. In the affective domain, STN activity in the alpha band may represent the valence and arousal of emotional information.

Multi-Behavior Fusion Based Potential Field Method for Path Planning of Unmanned Surface Vessel

The problem of the unmanned surface vessel (USV) path planning in static and dynamic obstacle environments is addressed in this paper. Multi-behavior fusion based potential field method is proposed, which contains three behaviors: goal-seeking, boundary-memory following and dynamic-obstacle avoidance. Then, different activation conditions are designed to determine the current behavior. Meanwhile, information on the positions, velocities and the equation of motion for obstacles are detected and calculated by sensor data. Besides, memory information is introduced into the boundary following behavior to enhance cognition capability for the obstacles, and avoid local minima problem caused by the potential field method. Finally, the results of theoretical analysis and simulation show that the collision-free path can be generated for USV within different obstacle environments, and further validated the performance and effectiveness of the presented strategy.

Dynamic collision avoidance for cooperative fixed-wing UAV swarm based on normalized artificial potential field optimization

Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Firstly,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local oscillation.Then,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is proposed.Finally,several simulations are carried out to illustrate superiority and effectiveness.

Local field potentials,spiking activity,and receptive fields in human visual cortex

The concept of receptive field(RF) is central to sensory neuroscience. Neuronal RF properties have been substantially studied in animals,while those in humans remain nearly unexplored. Here, we measured neuronal RFs with intracranial local field potentials(LFPs) and spiking activity in human visual cortex(V1/V2/V3). We recorded LFPs via macro-contacts and discovered that RF sizes estimated from lowfrequency activity(LFA, 0.5–30 Hz) were larger than those estimated from low-gamma activity(LGA, 30–60 Hz) and high-gamma activity(HGA, 60–150 Hz). We then took a rare opportunity to record LFPs and spiking activity via microwires in V1 simultaneously. We found that RF sizes and temporal profiles measured from LGA and HGA closely matched those from spiking activity. In sum, this study reveals that spiking activity of neurons in human visual cortex could be well approximated by LGA and HGA in RF estimation and temporal profile measurement, implying the pivotal functions of LGA and HGA in early visual information processing.

LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.

Local minima-free design of artificial coordinating fields

In order to overcome the drawbacks of conventional artificial potential fields (APF) based methods for the motion planning problems of mobile robots in dynamic uncertain environments, an artificial coordinating fields (ACF) based method has been proposed recently. This paper deals with the reachability problem of the ACF, that is, how to design and choose the parameters of the ACF and how the environment should be such that the robot can reach its goal without being trapped in local minima. Some sufficient conditions for these purposes are developed theoretically. Theoretical analyses show that, the ACF can effectively remove local minima in dynamic uncertain environments with V-shape or U-shape obstacles, and guide the mobile robot to reach its goal with some necessary environment constraints and based on the methods provided in this paper to properly choose the parameters of the ACF. Comparisons between the ACF and APF, and simulations are provided to illustrate the advantages of the ACF.

经颅磁声电刺激对健康与帕金森病大鼠神经回路中beta振荡的影响

背景:经颅磁声电刺激是一种基于磁声耦合电效应的无创、高精度脑神经聚焦刺激方法,可调节神经节律振荡活动,从而影响大脑的运动、认知等功能。目的:探究经颅磁声电刺激对健康与帕金森病大鼠神经回路中beta振荡的影响。方法:①动物实验:采用随机数字表法将24只Wistar大鼠随机分为4组,每组6只:正常对照组不进行任何干预;正常刺激组大脑前额叶皮质接受经颅磁声电刺激(空间峰值脉冲平均强度为13.33 W/cm^(2),基波频率为0.4 MHz,基波周期数为1000,脉冲重复频率为200 Hz);模型对照组、模型刺激组通过腹腔注射1-甲基-4-苯基-1,2,3,6-四氢吡啶建立帕金森病模型,造模成功后,模型对照组大脑前额叶皮质接受经颅磁声电假刺激,模型刺激组大脑前额叶皮质接受经颅磁声电刺激,每天刺激时长2.0 min,刺激结束停留8-10 min后,采集大鼠执行T迷宫过程中局部场电位信号并同时记录行为学正确率,对比分析各组局部场电位信号能量的时频分布情况和行为差异,当大鼠正确率连续3 d高于80%后停止刺激实验和T迷宫实验。②建模仿真实验:构建经颅磁声电刺激下皮质-基底神经节回路模型,分别改变超声发射周期(5,10,20 ms)、超声发射占空比(30%,50%,90%)和感应电流密度(20,50,100μA/cm^(2)),比较不同刺激参数下健康与帕金森病大鼠beta振荡的功率谱密度值。结果与结论:①动物实验:正常对照组大鼠的空间学习能力强于模型对照组(P<0.001),正常刺激组大鼠的空间学习能力强于正常对照组(P<0.05),模型刺激组大鼠的空间学习能力强于模型对照组(P<0.01);正常对照组beta振荡能量分布较为集中,正常刺激组较正常对照组beta振荡信号能量有所降低,模型对照组与模型刺激组beta振荡能量广泛分布且能量值显著高于正常对照组、正常刺激组,并且模型刺激组beta振荡信号能量明显低于模型对照组;②建模仿真实验:不加刺激时,健康大鼠beta频段功率谱密度峰值(30 dB)显著低于帕金森病大鼠(55 dB);施加经颅磁声电刺激后,两组大鼠beta频段功率谱密度值普遍降低;beta频段功率谱密度峰值与超声发射周期呈正相关、与感应电流密度呈负相关,当超声发射占空比为50%时功率谱密度峰值最低;③结果表明:经颅磁声电刺激可抑制健康与帕金森病大鼠的beta振荡,进而改善大鼠的运动功能与决策认知功能。

基于偏转角抑制的改进人工势场法路径规划

针对传统人工势场法在实际应用中存在的局部最极小值、目标不可达以及路径震荡等问题,文种提出了一种基于偏转角抑制的改进人工势场法。该方法以传统人工势场法为基础,采用改进斥力势场函数保证目标点为全局势能最低点。在路径解算中引入偏转角抑制因子来抑制无人车行驶过程中过大的偏转角,在无人车陷入局部极小值点后每一步的路径解算中都添加新的虚拟目标点,直至无人车累积一定的偏转角摆脱障碍物群。仿真实验结果表明,该算法可以在不影响无人车避障的情况下减少规划路径的震荡性,并能够使无人车逃脱复杂障碍物群顺利到达目标点,规划出一条有效、简短以及震荡较少的路径。

基于改进势场法的智能车超车动态路径规划

为了改进人工势场法(artificial potential field,APF)在智能车高速超车状态下规划出的轨迹规范性差、安全性得不到保障、以及路径不平滑的问题。设计用于指引智能车换道的换道引力势场,以保证换道轨迹的规范性;构建异向分布结构的障碍车斥力势场提高换道的安全性;并建立带有转向缺口的道路中心线斥力势场和设计平滑代价函数优化规划出的轨迹点,使规划出的路径更加平滑。基于线性二次型调节器(linear quadratic regulator,LQR)设计路径跟踪控制器跟踪规划出的路径。通过Simulink与Carsim联合仿真,结果表明:所改进的APF算法能规划出更加合理的路径,设计的LQR路径跟踪控制器跟踪误差趋近于零,能够较好地控制车辆完成超车换道。

基于改进人工势场法的通用航空路径规划

通用航空飞机在飞行过程除了要面对障碍物和天气系统的威胁,同时也受到飞行空域的限制,往往飞机只能在一块固定的空域或狭小的飞行走廊内飞行,一旦飞出限制空域,则有可能引发飞行冲突,甚至发生严重的安全事故。针对这些问题,在人工势场法斥力势场函数中添加航空器和目标点之间的相对距离函数,首先解决传统人工势场法存在的目标不可达问题和局部极小点问题,然后在算法中加入航路边界斥力影响因子,使飞机避障后在边界斥力的作用下重回航路中心。经过MATLAB仿真验证,试验结果表明,改进后的人工势场法能够实现主动避障和飞机航迹的规划。

基于视野和速度引导的无人机集群避障算法

在未来的多无人机(unmanned aerial vehicle,UAV)空中作战中,无人机集群在未知空域中安全飞行是集群研究中的重要内容。针对无人机集群避障以及集群形态保持问题,提出了一种基于视野和速度引导(visual field and velocity guidance,VFVG)的集群避撞算法。基于视野法设计集群自适应通讯拓扑机制,结合远吸近斥势力原则及一致性方法,在保持集群形态的同时,加速了集群无人机个体间的避障信息的传递。在此基础上,提出将极限环与人工势场法相结合构造避障速度引导项,解决了集群遇障分群困难、避障徘徊停滞等问题。引入避障时间指标,验证了算法的避障效率。仿真结果表明,该方法能够使多无人机以良好的集群形态安全快速平稳地通过复杂障碍区域,有效提高了集群避障成功率和避障效率。

基于改进人工势场法的内河应急抢险船舶路径规划

针对应急抢险船舶在极端洪涝灾害时的路径规划问题,提出一种改进人工势场法的路径规划算法,实现内河应急抢险船舶的快速精准救援。由于传统人工势场法中存在局部极小点、目标不可达等影响应急抢险船舶救援的安全问题,通过改进斥力势场函数解决了船舶在靠近障碍物的救援点时的目标不可达问题;引入逃逸力避免了局部极小点问题。通过数值仿真试验对比验证,改进后的人工势场法能够帮助应急抢险船舶在复杂的内河航道环境中安全到达救援点。

基于改进人工势场法的医疗配送机器人路径规划

随着科技的高速发展和近几年新冠疫情的影响,医疗配送机器人开始逐步出现在各大医疗机构中,然而传统医疗配送机器人在使用人工势场算法进行路径规划时存在局部最优解和目标不可达问题。因此,针对局部最优解问题,提出了设计虚拟目标点的方法,将机器人从局部最优状态解救出来;针对目标不可达问题,在障碍物斥力势场函数中引入了目标距离函数对障碍物斥力进行限制,从而解决目标不可达问题。最后将该方法在多种复杂环境中与传统算法进行比较验证,实验结果表明,该改进算法能够解决传统算法存在的局部最优解和目标不可达问题,在算法效率上也提高了5%~9%,并且能够有效运用于实际场景。