Synchrony dynamics during initiation, failure, and rescue of the segmentation clock

The "segmentation clock" is thought to coordinate sequential segmentation of the body axis in vertebrate embryos. This clock comprises a multicellular genetic network of synchronized oscillators, coupled by intercellular Delta-Notch signaling. How this synchrony is established and how its loss determines the position of segmentation defects in Delta and Notch mutants are unknown. We analyzed the clock's synchrony dynamics by varying strength and timing of Notch coupling in zebra-fish embryos with techniques for quantitative perturbation of gene function. We developed a physical theory based on coupled phase oscillators explaining the observed onset and rescue of segmentation defects, the clock's robustness against developmental noise, and a critical point beyond which synchrony decays. We conclude that synchrony among these genetic oscillators can be established by simultaneous initiation and self-organization and that the segmentation defect position is determined by the difference between coupling strength and noise.     

The intrinsic electrophysiological properties of mammalian neurons: insights into central nervous system function

This article reviews the electroresponsive properties of single neurons in the mammalian central nervous system (CNS). In some of these cells the ionic conductances responsible for their excitability also endow them with autorhythmic electrical oscillatory properties. Chemical or electrical synaptic contacts between these neurons often result in network oscillations. In such networks, autorhythmic neurons may act as true oscillators (as pacemakers) or as resonators (responding preferentially to certain firing frequencies). Oscillations and resonance in the CNS are proposed to have diverse functional roles, such as (i) determining global functional states (for example, sleep-wakefulness or attention), (ii) timing in motor coordination, and (iii) specifying connectivity during development. Also, oscillation, especially in the thalamo-cortical circuits, may be related to certain neurological and psychiatric disorders. This review proposes that the autorhythmic electrical properties of central neurons and their connectivity form the basis for an intrinsic functional coordinate system that provides internal context to sensory input.     

Entrainment of the circadian clock in the liver by feeding

Circadian rhythms of behavior are driven by oscillators in the brain that are coupled to the environmental light cycle. Circadian rhythms of gene expression occur widely in peripheral organs. It is unclear how these multiple rhythms are coupled together to form a coherent system. To study such coupling, we investigated the effects of cycles of food availability (which exert powerful entraining effects on behavior) on the rhythms of gene expression in the liver, lung, and suprachiasmatic nucleus (SCN). We used a transgenic rat model whose tissues express luciferase in vitro. Although rhythmicity in the SCN remained phase-locked to the light-dark cycle, restricted feeding rapidly entrained the liver, shifting its rhythm by 10 hours within 2 days. Our results demonstrate that feeding cycles can entrain the liver independently of the SCN and the light cycle, and they suggest the need to reexamine the mammalian circadian hierarchy. They also raise the possibility that peripheral circadian oscillators like those in the liver may be coupled to the SCN primarily through rhythmic behavior, such as feeding.     

模糊综合评价的一种神经网络方法

将神经网络理论应用于模糊综合评价，首先引入因素空间的概念，在因素空间中给出了一种基于三层神经元的多用量化模糊综合评价方法，并利用LMS算法及矩方法研究了该模型权重及学习步长的确定方法，实现了权重及学习步长的网络学习，最终实现了等级评价值的计算机输出．较好地解决了传统的综合评价方法中各指标的权数受人为因素的影响这一难点问题．     

From swimming to walking with a salamander robot driven by a spinal cord model

The transition from aquatic to terrestrial locomotion was a key development in vertebrate evolution. We present a spinal cord model and its implementation in an amphibious salamander robot that demonstrates how a primitive neural circuit for swimming can be extended by phylogenetically more recent limb oscillatory centers to explain the ability of salamanders to switch between swimming and walking. The model suggests neural mechanisms for modulation of velocity, direction, and type of gait that are relevant for all tetrapods. It predicts that limb oscillatory centers have lower intrinsic frequencies than body oscillatory centers, and we present biological data supporting this.     

Continuous and discontinuous perturbations

Perturbations of quantum systems ranging from oscillators to fields can be either continuous or discontinuous functions of the coupling. Even nonrenormalizable fields may now find a natural interpretation.     

Temperature sensing by an olfactory neuron in a circuit controlling behavior of C. elegans

Temperature is an unavoidable environmental cue that affects the metabolism and behavior of any creature on Earth, yet how animals perceive temperature is poorly understood. The nematode Caenorhabditis elegans "memorizes" temperatures, and this stored information modifies its subsequent migration along a temperature gradient. We show that the olfactory neuron designated AWC senses temperature. Calcium imaging revealed that AWC responds to temperature changes and that response thresholds differ depending on the temperature to which the animal was previously exposed. In the mutant with impaired heterotrimeric guanine nucleotide-binding protein (G protein)-mediated signaling, AWC was hyperresponsive to temperature, whereas the AIY interneuron (which is postsynaptic to AWC) was hyporesponsive to temperature. Thus, temperature sensation exhibits a robust influence on a neural circuit controlling a memory-regulated behavior.     

Predictions of viscoelastic behavior of pomegranate using artificial neural network and Maxwell model

Stress relaxation is one of the defined tests to characterize the viscoelastic properties of food and agricultural materials. Stress relaxation data are very important because they provide useful and valuable information such as fruit firmness and ripening, food processing and predicting changes in the material during mechanical loading. Viscoelastic behavior of some varieties of pomegranate that are cultivated in Iran has been studied in current research. For this purpose, stress relaxation test was conducted with three cultivars of pomegranate (Ardestani, Shishekap and Malas) for three sizes (small, medium and large). In this article the potential of artificial neural network (ANN) technique is evaluated as an alternative method for Maxwell model to predict the viscoelastic behavior of pomegranate. Neural stress relaxation models were constructed to describe stress relaxation behavior of pomegranate with respect to time. The neural models were built based upon relaxation time as input network and stress relaxation as output network. The results revealed that both ANN model and Maxwell model have high capability of producing accurate and reliable predictions for stress.     

Superconductivity modulated by quantum size effects

We have fabricated ultrathin lead films on silicon substrates with atomic-scale control of the thickness over a macroscopic area. We observed oscillatory behavior of the superconducting transition temperature when the film thickness was increased by one atomic layer at a time. This oscillating behavior was shown to be a manifestation of the Fabry-Perot interference modes of electron de Broglie waves (quantum well states) in the films, which modulate the electron density of states near the Fermi level and the electron-phonon coupling, which are the two factors that control superconductivity transitions. This result suggests the possibility of modifying superconductivity and other physical properties of a thin film by exploiting well-controlled and thickness-dependent quantum size effects.     

不连续激励函数时滞Cohen-Grossberg神经网络的动力学性质

研究了一类具有不连续激励函数的时滞Cohen-Grossbe神经网络,利用推广的 Lyapunov方法,证明了Filippov意义下解全局收敛到惟一的平衡点.在证明过程中使用了链式法.利用该法则可以计算不可微Lyapunov函数对时间t沿右端不连续微分方程的导数.     

基于神经元晶体管和忆阻器的 Hopfield 神经网络及其在联想记忆中的应用

随着人工智能的高速发展,越来越多的神经元模型相继被提出,现有的神经元电路主要由普通晶体管、运算放大器等高功耗器件构成,存在结构复杂、集成度不高、兼容性差、功耗高、阈值调节难度高的缺点.针对以上不足,首次提出了一种全新的神经元结构,该结构仅由神经元晶体管、忆阻器和普通电阻构成,相比传统神经元电路,不包含复杂的差分运算电路以及电流与电压信号的转换电路,电路结构简单,同时具有良好的电路兼容性,可用于大规模集成.该结构利用神经元晶体管的加权求和特性以及阈值可控功能来模拟神经元信息传导过程,同时利用阈值忆阻器的阈值特性和阻值连续变化能力来设定和更新突触权值,使得该新型神经元结构不仅能实现传统神经元电路功能的同时,还具有能耗低、阈值动态可控、权值可编程的优点,不仅极大地简化了网络结构,还能加强网络性能.其次,还提出了基于这种新型神经元结构的忆阻离散Hopfield神经网络,该忆阻神经网络有助于促进人工神经形态系统的硬件实现,使神经网络系统能耗降低,集成度极大地提高,将这种网络运用在联想记忆和彩色数字图像恢复中,进一步说明了基于全新神经元结构的忆阻离散hopfield神经网络的实用性以及有效性.     

Emerging coherence in a population of chemical oscillators

Coherence of interacting oscillating entities has importance in biological, chemical, and physical systems. We report experiments on populations of chemical oscillators and verify a 25-year-old theory of Kuramoto that predicts that global coupling in a set of smooth limit-cycle oscillators with different frequencies produces a phase transition in which some of the elements synchronize. Both the critical point and the predicted dependence of order on coupling are seen in the experiments. We extend the studies both to relaxation and to chaotic oscillators and characterize the quantitative similarities and differences among the types of systems.     

基于MATLAB6.x的BP人工神经网络的土壤环境质量评价方法研究

对基于MATLAB 6．x的BP人工神经网络工具箱进行了简要的介绍，并将BP人工神经网络应用到土壤环境质量现状评价中。编制了基于MATLAB 6．x土壤环境质量评价程序，并对影响评价结果的训练集的构建、隐层神经元数量的选择、训练过程的建立等问题进行了探讨。结果表明，用随机函数rand或线性函数linspace内插生成网络的训练集是可行的，BP网络隐层的传递函数为tansig。神经元数量为5（用rand函数生成训练集）或8（用linspace函数生成训练集），输出层的传递函数为purelin，神经元数量为1。训练集中加入一定的噪声更有利于提高网络的识别能力。在此基础上，将构建的网络应用到实际土壤环境质量评价中，并将评价的结果与其他评价方法得出的结果进行了比较，表明BP人工神经网络应用到土壤环境质量评价中是切实可行的。     

Oscillations and sparsening of odor representations in the mushroom body

In the insect olfactory system, oscillatory synchronization is functionally relevant and reflects the coherent activation of dynamic neural assemblies. We examined the role of such oscillatory synchronization in information transfer between networks in this system. The antennal lobe is the obligatory relay for olfactory afferent signals and generates oscillatory output. The mushroom body is responsible for formation and retrieval of olfactory and other memories. The format of odor representations differs significantly across these structures. Whereas representations are dense, dynamic, and seemingly redundant in the antennal lobe, they are sparse and carried by more selective neurons in the mushroom body. This transformation relies on a combination of oscillatory dynamics and intrinsic and circuit properties that act together to selectively filter and synthesize the output from the antennal lobe. These results provide direct support for the functional relevance of correlation codes and shed some light on the role of oscillatory synchronization in sensory networks.     

n阶非线性时滞微分方程的振动性与渐近性

研究了具有强迫项的ｎ项非线性时滞微分方程的解的振动性与渐近性，获得了某些充分条件，在这些条件下，如ｎ为偶数，方程的所有解振动：如ｎ为奇数，方程的每个解或者振动，或者趋于零，对文（１－２）中的定理作了较大的改进。     

基于BP神经网络的华北落叶松小班蓄积预估模型研究与应用

林分蓄积是衡量小班林分生产力的重要指标。选择华北落叶松人工林小班数据,对以年龄、公顷株数和立地指数为自变量,小班公顷蓄积为因变量的BP (back propagation)神经网络模型和多元回归模型进行研究。研究结果表明:①BP神经网络参数最优组合:三层网络结构包括输入层3个神经元,隐含层10个神经元和1个神经元,输出层1个神经元,R语言算法选用含有动量的自适应梯度下降法,MATLAB软件算法选择Levevberg-Marquardt法;②多元回归模型中,生长理论方程为基础修正函数"Logistic+幂函数"组合的修正模型V=SI~(0.977 2)N~(0.510 3)0.500 1/[1+44.226 1exp(-0.146 6t)]表现最优,其决定系数R~2为0.721 8;③BP模型预测精度最高,其次是多元回归模型和材积表法。基于以上研究,为了提高BP模型的实用性,通过JAVA和R语言编程方式,将构建BP神经网络小班蓄积预估模型存储到收获预估模型的模型库中,在人工林收获预估中实现BP模型的调用,实现从经典的数学模型形式向智能化软件方向发展,提高BP模型在实际生产中的可操作性,为森林经营作业提供决策支持。     

基于改进果蝇算法优化广义回归神经网络的绿色农产品消费行为预测

针对绿色农产品消费行为具有多变量非线性相互作用的特点，传统统计方法难以准确预测消费行为的问题，提出基于改进果蝇算法优化的广义回归神经网络消费行为预测模型。首先针对果蝇群搜索不均匀所导致果蝇飞行单一的问题，提出一种均匀的果蝇群搜索机制即扇形果蝇优化算法加快搜索能力和效率；其次针对广义回归神经网络的平滑因子易受人为选择的影响，提出改进果蝇算法优化广义回归神经网络参数，实现参数的自动化选择，提高模型的预测能力。运用提出的模型对绿色农产品消费行为预测。结果表明：相较于广义回归神经网络，遗传算法优化广义回归神经网络、粒子群算法优化广义回归神经网络、果蝇算法优化广义回归神经网络和改进果蝇算法优化广义回归神经网络模型在均方根误差指标上分别下降4.45%、1.89%、4.54%和5.03%,表明遗传算法、粒子群算法、果蝇算法和改进果蝇算法能够优化广义回归神经网络模型的平滑因子，提高模型的预测精度。从平均绝对误差、均方误差、均方根误差3个评价指标看，改进果蝇算法优化广义回归神经网络模型比其他6个单一预测模型具有更高预测精度。结果证明了改进果蝇算法优化广义回归神经网络模型在绿色农产品消费行为预测的有效性，...     

In vitro reconstruction of the respiratory central pattern generator of the mollusk Lymnaea

Most rhythmic behaviors such as respiration, locomotion, and feeding are under the control of networks of neurons in the central nervous system known as central pattern generators (CPGs). The respiratory rhythm of the pond snail Lymnaea stagnalis is a relatively simple, CPG-based behavior for which the underlying neural elements have been identified. A three-neuron network capable of generating the respiratory rhythm of this air-breathing mollusk has been reconstructed in culture. The intrinsic and network properties of this neural ensemble have been studied, and the mechanism of postinhibitory rebound excitation was found to be important for the rhythm generation. This in vitro model system enables a better understanding of the neural basis of rhythm generation.     

The cellular basis of a corollary discharge

How do animals discriminate self-generated from external stimuli during behavior and prevent desensitization of their sensory pathways? A fundamental concept in neuroscience states that neural signals, termed corollary discharges or efference copies, are forwarded from motor to sensory areas. Neurons mediating these signals have proved difficult to identify. We show that a single, multisegmental interneuron is responsible for the pre- and postsynaptic inhibition of auditory neurons in singing crickets (Gryllus bimaculatus). Therefore, this neuron represents a corollary discharge interneuron that provides a neuronal basis for the central control of sensory responses.     

Segregation of human neural stem cells in the developing primate forebrain

Many central nervous system regions at all stages of life contain neural stem cells (NSCs). We explored how these disparate NSC pools might emerge. A traceable clone of human NSCs was implanted intraventricularly to allow its integration into cerebral germinal zones of Old World monkey fetuses. The NSCs distributed into two subpopulations: One contributed to corticogenesis by migrating along radial glia to temporally appropriate layers of the cortical plate and differentiating into lamina-appropriate neurons or glia; the other remained undifferentiated and contributed to a secondary germinal zone (the subventricular zone) with occasional members interspersed throughout brain parenchyma. An early neurogenetic program allocates the progeny of NSCs either immediately for organogenesis or to undifferentiated pools for later use in the "postdevelopmental" brain.