Small modulation of ongoing cortical dynamics by sensory input during natural vision

During vision, it is believed that neural activity in the primary visual cortex is predominantly driven by sensory input from the environment. However, visual cortical neurons respond to repeated presentations of the same stimulus with a high degree of variability. Although this variability has been considered to be noise owing to random spontaneous activity within the cortex, recent studies show that spontaneous activity has a highly coherent spatio-temporal structure. This raises the possibility that the pattern of this spontaneous activity may shape neural responses during natural viewing conditions to a larger extent than previously thought. Here, we examine the relationship between spontaneous activity and the response of primary visual cortical neurons to dynamic natural-scene and random-noise film images in awake, freely viewing ferrets from the time of eye opening to maturity. The correspondence between evoked neural activity and the structure of the input signal was weak in young animals, but systematically improved with age. This improvement was linked to a shift in the dynamics of spontaneous activity. At all ages including the mature animal, correlations in spontaneous neural firing were only slightly modified by visual stimulation, irrespective of the sensory input. These results suggest that in both the developing and mature visual cortex, sensory evoked neural activity represents the modulation and triggering of ongoing circuit dynamics by input signals, rather than directly reflecting the structure of the input signal itself.     

Direct control of paralysed muscles by cortical neurons

A potential treatment for paralysis resulting from spinal cord injury is to route control signals from the brain around the injury by artificial connections. Such signals could then control electrical stimulation of muscles, thereby restoring volitional movement to paralysed limbs. In previously separate experiments, activity of motor cortex neurons related to actual or imagined movements has been used to control computer cursors and robotic arms, and paralysed muscles have been activated by functional electrical stimulation. Here we show that Macaca nemestrina monkeys can directly control stimulation of muscles using the activity of neurons in the motor cortex, thereby restoring goal-directed movements to a transiently paralysed arm. Moreover, neurons could control functional stimulation equally well regardless of any previous association to movement, a finding that considerably expands the source of control signals for brain-machine interfaces. Monkeys learned to use these artificial connections from cortical cells to muscles to generate bidirectional wrist torques, and controlled multiple neuron-muscle pairs simultaneously. Such direct transforms from cortical activity to muscle stimulation could be implemented by autonomous electronic circuitry, creating a relatively natural neuroprosthesis. These results are the first demonstration that direct artificial connections between cortical cells and muscles can compensate for interrupted physiological pathways and restore volitional control of movement to paralysed limbs.     

Generalization in vision and motor control

Learning is more than memory. It is not simply the building of a look-up table of labelled images, or a phone-directory-like list of motor acts and the corresponding sequences of muscle activation. Central to learning and intelligence is the ability to predict, that is, to generalize to new situations, beyond the memory of specific examples. The key to generalization, in turn, is the architecture of the system, more than the rules of synaptic plasticity. We propose a specific architecture for generalization for both the motor and the visual systems, and argue for a canonical microcircuit underlying visual and motor learning.     

GABA能回路在听皮层神经元频率调谐中的作用

为了解神经抑制在听中枢神经元频率调谐过程中的作用,本研究采用多管玻璃微电极胞外记录单单位反应的方法观察了去r-氨基丁酸能抑制后大棕蝠(Eptesicusfuscus)听皮层神经元频率调谐特性的变化,结果显示:(1)97.9%的神经元频率调谐曲线扩宽,Qn值下降(p<0.0001);(2)绝大部分神经元的最小阈值下降(p<0.0001);(3)兴奋性调谐曲线面积增加(p<0.0001).该结果提供了GABA能回路参与蝙蝠听皮层神经元频率调谐的直接证据.     

发电机励磁控制的Gain Scheduling设计

针对电力系统的非线性特性 ,提出了一种实用的非线性控制设计方法——增益规划 (Gain Scheduling,GS)。选择电磁功率 Pe,机端电压 Vt作为状态划分变量 ,将系统运行域分为若干区 ,在各区内的选定运行点上基于局部线性化模型设计底层控制器 ,如线性最优励磁控制器 (L OEC) ,通过对运行域内其它点实施模糊插值运算 ,得到上层全局的GS控制规律。数字仿真结果表明 ,GSEC能很好地适应系统运行点的变化 ,较固定增益的 L OEC具有更好的控制性能 ;并且可以离线设计 ,在线计算量和存储量均不大 ,利于实际应用     

Quantum control of bosonic modes with superconducting circuits

Bosonic modes have wide applications in various quantum technologies,such as optical photons for quantum communication,magnons in spin ensembles for quantum inf...     

电子线路噪声的二重性与对混沌控制

基于混沌控制理论 ,用外部噪声法控制混沌 ,表明了噪声具有二重性的观点     

基于LabVIEW的实时视觉铝合金脉冲MIG焊测控系统

针对铝合金脉冲MIG焊过程测控的需要,利用LabVIEW虚拟仪器技术设计铝合金脉冲MIG焊过程多数据的同步实时采集及控制系统.考虑脉冲MIG的特点及开发的效率、控制速度等要求,采用"数据采集卡+PC机+实时控制器"的模式,通过选择LabVIEW做为测控系统的信号采集及处理平台,并在硬件平台设计的基础上,通过COM技术的引入,实现了复杂信号处理算法下的电流、电压与视频信号高速数据流的并行处理.实验表明:所建立的平台能正确稳定地实时采集并处理铝合金脉冲MIG焊过程中信息,程序界面友好且可扩展性强.     

利用PSPICE仿真分析PWM控制电路

介绍了利用PSPICE设计分析三相DC/AC逆变器PWM控制电路的方法。重点介绍了正弦波脉宽调制法、准正弦波脉宽调制法和单元调制PWM法的PSPICE实现。给出了基于准正弦波脉宽调制法的DC/AC逆变器的仿真实例,并运用到《电力电子技术》的教学与实验中,取得了良好的效果。     

搅拌设备控制系统的输入信号预处理电路设计

为了提高沥青混凝土搅拌设备计算机控制系统的可靠性，针对其工作环境对输入信号预处理电路的特殊要求，通过比较的方法，论述了温度检测和配料称量等模拟信号及开关量输入信号处理电路设计的依据，并设计了相应的电路。针对变频器输出频率显示信号中的高频噪声，设计了相应的噪声消除电路，给出了进一步提高系统抗干扰能力的措施。将设计的电路应用于LB2000和LB3000型沥青混凝土搅拌设备计算机控制系统，进行了测试。测试结果表明：输出信号稳定，且消除了高频干扰，提高了系统的可靠性和抗干扰能力。     

电液伺服系统的增益自适应滑模变结构控制

为实现对电液伺服系统非线性、不确定性和未建模动态等因素的有效补偿,将系统转换成具有自适应动态递归模糊神经网络(ADRFNN)辨识误差,即二次不确定性的等效线性数学模型,利用增益自适应滑模变结构控制(GASMC)方法对系统进行综合设计.实验结果表明:ADRFNN的高精度在线辨识和GASMC校正项的增益自适应功能使系统具有较强鲁棒性和更高的稳态精度,同时使系统控制量的颤振现象得到有效抑制.     

基于视觉的机器人模糊自适应阻抗控制

对未知环境下具有6个自由度工业机器人的视觉/力反馈混合控制进行研究.首先,建立被跟踪曲线图像特征与机器人关节角度的映射关系;其次,由机器人离散阻抗控制规律描述机器人末端在受限表面移动时与受限表面产生连续接触的条件,并根据接触力的变化对阻抗模型参数进行模糊调节;最后,在未知物体表面对末端固定安装单摄像机和力传感器的6个自由度机器人进行力跟踪试验研究.研究结果表明:该阻抗控制具有较强的未知物体表面曲线跟踪能力和较高的力控制精度,曲线跟踪算法简单,不要求对视觉传感器进行精确标定,模糊控制器实时地调整阻抗参数,使系统稳定而且具有良好的动态品质,是一种有效的视觉/力反馈混合控制方法.     

一类电路混沌系统的追踪控制与反控制

基于线性系统的稳定性理论,巧妙地设计合适的非线性反馈控制器,成功地实现了一类电路混沌系统对给定的参考信号的追踪控制与混沌反控制.数值仿真表明了该方法的有效性与可行性.     

基于CPAC与单目摄像的六自由度机械臂控制模式研究

为解决一般六自由度工业度机械臂的控制器存在的兼容性低、人机界面单一且编程语言差异大的不足,提出一种基于CPAC(Computerized Programmable Automation Controller计算机可编程自动化控制器)控制机械臂的方式,以六自由度机械臂为实验平台,利用CPAC控制器的人机界面中三点法建立与摄像机一致的世界坐标系,通过Harris角点匹配与PnP法获取目标的位姿信息,利用CPAC编程语言OtoStudio的函数库解算各个关节轴转动的角度,并利用“最短行程”加权获得关节轴的最优角度,最终驱动机械臂末端执行器可靠动作并到达目标点,完成预设动作。通过实验可以看出,与一般的控制器相比较,CPAC具有可靠的I/O控制、编程环境标准、人机界面丰富友好的特点,并验证了这种控制模式的可行性,实现了对六自由度机械臂的联合控制,为六自由度机械臂的实时控制模式提供了新的思路。     

PTC元件及其在电气控制线路中的应用初探

PTC元件是一种特珠的正温度系数的热敏电阻元件,其阻值一温度特性具有“延时断开”特性。可以在一些电气控制线路中取代时间继电器,从而简化线路,提高可靠性。给出了PTC元件的应用实例,探讨了应用时的一些问题。     

一种新的双目立体视觉伺服控制模型及实验研究

针对目前手眼视觉伺服系统模型中普遍存在深度信息估计的问题,提出了一种用于双目视觉伺服控制的模型,该模型避免了深度值的测量与估计,提高了系统的控制性能,从而解决了未知物点的深度信息估计的问题。本文应用此模型,单独考虑机器人的运动学特性,设计了机器人末端执行器进行定位控制的控制器,仿真结果验证了该模型与控制算法的有效性;进一步提出了模型使用的改进算法,使该模型更具有宽泛的实用性;并且,进行了基于MOTOMAN UP6型机器人的双目视觉伺服控制实验,实验结果验证了该模型在实际控制工程中的有效性、可行性。     

主动约束层阻尼结构的振动控制

基于弹性、粘弹性和压电材料的本构关系,利用Hamilton原理,推导了主动约束层阻尼板的有限元动力学模型。结合压电材料的机电耦合特性,采用自感电压的位移和速度反馈,对主动约束层阻尼板进行了闭环振动控制,研究了不同控制增益条件下,主动约束层阻尼板的动态特性。研究结果表明:采用自感电压的比例、微分反馈控制,能有效控制约束层阻尼板的振动,增大振动能量耗散,尤其对频率共振峰有明显抑制作用。由于该方法结构简单,容易实现,有很好的工程应用前景。     

Routing of spike series by dynamic circuits in the hippocampus

Recurrent inhibitory loops are simple neuronal circuits found in the central nervous system, yet little is known about the physiological rules governing their activity. Here we use simultaneous somatic and dendritic recordings in rat hippocampal slices to show that during a series of action potentials in pyramidal cells recurrent inhibition rapidly shifts from their soma to the apical dendrites. Two distinct inhibitory circuits are sequentially recruited to produce this shift: one, time-locked with submillisecond precision to the onset of the action potential series, transiently inhibits the somatic and perisomatic regions of pyramidal cells; the other, activated in proportion to the rate of action potentials in the series, durably inhibits the distal apical dendrites. These two operating modes result from the synergy between pre- and postsynaptic properties of excitatory synapses onto recurrent inhibitory neurons with distinct projection patterns. Thus, the onset of a series of action potentials and the rate of action potentials in the series are selectively captured and transformed into different spatial patterns of recurrent inhibition.     

基于视觉的智能车辆模糊滑模横向控制

以采用视觉导航的智能车DLUIV-1为对象,对智能车辆的横向控制方法开展研究.首先,建立基于视觉预瞄距离的车辆横向控制系统模型,利用包含速度等因素在内的预瞄运动学模型确定车辆的横向偏差和方位偏差.其次,针对横向控制的特点,提出了模糊和滑模相结合的智能车辆横向控制策略,综合考虑车辆当前的横向偏差和方位偏差,将二者融合后的综合偏差作为滑模切换函数的参数来设计滑模面,将滑模切换函数作为控制目标,利用模糊控制规则调整控制变量的大小来确保存在和到达条件成立,保证方向盘转动的稳定性.仿真结果表明该横向控制器能够保证智能车辆准确而且稳定地跟踪参考路径,且对模型参数的变化具有较强的鲁棒性.