Brave new world revisited revisited: Huxley's evolving view of behaviorism
Newman, Bobby
1992-01-01
Aldous Huxley's Brave New World has served as a popular and powerful source of antibehavioral sentiment. Several of Huxley's works are examined in order to ascertain his true thoughts regarding behaviorism. Early in his career Huxley failed to appreciate aspects of behavioral theory (e.g., an appreciation of heredity) or the good ends to which it could be employed. Huxley's later works portrayed behaviorism in a much more positive light, and he believed that behavioral science, along with spi...
Brave new world revisited revisited: Huxley's evolving view of behaviorism.
Newman, B
1992-01-01
Aldous Huxley's Brave New World has served as a popular and powerful source of antibehavioral sentiment. Several of Huxley's works are examined in order to ascertain his true thoughts regarding behaviorism. Early in his career Huxley failed to appreciate aspects of behavioral theory (e.g., an appreciation of heredity) or the good ends to which it could be employed. Huxley's later works portrayed behaviorism in a much more positive light, and he believed that behavioral science, along with spiritual enlightenment, might help save humanity from the Brave New World he predicted.
Spike neural models (part I: The Hodgkin-Huxley model
Directory of Open Access Journals (Sweden)
Johnson, Melissa G.
2017-05-01
Full Text Available Artificial neural networks, or ANNs, have grown a lot since their inception back in the 1940s. But no matter the changes, one of the most important components of neural networks is still the node, which represents the neuron. Within spiking neural networks, the node is especially important because it contains the functions and properties of neurons that are necessary for their network. One important aspect of neurons is the ionic flow which produces action potentials, or spikes. Forces of diffusion and electrostatic pressure work together with the physical properties of the cell to move ions around changing the cell membrane potential which ultimately produces the action potential. This tutorial reviews the Hodkgin-Huxley model and shows how it simulates the ionic flow of the giant squid axon via four differential equations. The model is implemented in Matlab using Euler's Method to approximate the differential equations. By using Euler's method, an extra parameter is created, the time step. This new parameter needs to be carefully considered or the results of the node may be impaired.
Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model
2017-01-01
Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors. PMID:28316842
Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model
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Yihong Wang
2017-01-01
Full Text Available Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors.
Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model.
Wang, Yihong; Wang, Rubin; Xu, Xuying
2017-01-01
Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors.
FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model.
Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid
2014-01-01
A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well.
A correspondence between the models of Hodgkin-Huxley and FitzHugh-Nagumo revisited
Postnikov, Eugene B.; Titkova, Olga V.
2016-11-01
We present the discussion on the possibility to scale the classical dimensionless FitzHugh-Nagumo model of neuronal self-sustained oscillations to the range of variables corresponding to the results, which are provided by the biophysically relevant reduced two-dimensional Hodgkin-Huxley equations (the Rinzel model). It is shown that there exists a relatively simple choice of affine transformation, which results in time-dependent solutions, which reproduce with a high accuracy the time course of the recovery variable and the sharp onsets (intervals of fast motions on a phase trajectories) of the voltage spikes. As for the latter, the reasons for unavoidable difference are discussed as well as a necessity of taking into account applied current values during such a scaling procedure.
Noise-induced synchronization in a lattice Hodgkin-Huxley neural network
Pang, James Christopher S.; Monterola, Christopher P.; Bantang, Johnrob Y.
2014-01-01
We examine how the synchronization of the series of action potentials (APs) of realistic neurons interconnected in a lattice is influenced by variations of both the direction and magnitude of neuron-neuron connectivity in a noisy environment. We first demonstrate the existence of an optimal noise level that brings about the highest average number of APs per unit time, for a single Hodgkin-Huxley neuron. We then show that synchronization, as a collective response of interconnected neurons forming an N×N lattice, is optimal at different noise strengths σc=σc(p), depending on the degree of random-link malfunction parameterized by flipping direction probability p. Thus, even without the scale-free structure of neuronal networks, proper combinations of both randomness in reconnection (flipping) and noisy environment can be beneficial to the collective functioning of neurons.
Daly, Aidan C; Gavaghan, David J; Holmes, Chris; Cooper, Jonathan
2015-12-01
As cardiac cell models become increasingly complex, a correspondingly complex 'genealogy' of inherited parameter values has also emerged. The result has been the loss of a direct link between model parameters and experimental data, limiting both reproducibility and the ability to re-fit to new data. We examine the ability of approximate Bayesian computation (ABC) to infer parameter distributions in the seminal action potential model of Hodgkin and Huxley, for which an immediate and documented connection to experimental results exists. The ability of ABC to produce tight posteriors around the reported values for the gating rates of sodium and potassium ion channels validates the precision of this early work, while the highly variable posteriors around certain voltage dependency parameters suggests that voltage clamp experiments alone are insufficient to constrain the full model. Despite this, Hodgkin and Huxley's estimates are shown to be competitive with those produced by ABC, and the variable behaviour of posterior parametrized models under complex voltage protocols suggests that with additional data the model could be fully constrained. This work will provide the starting point for a full identifiability analysis of commonly used cardiac models, as well as a template for informative, data-driven parametrization of newly proposed models.
Response variance in functional maps: neural darwinism revisited.
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Hirokazu Takahashi
Full Text Available The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.
Response variance in functional maps: neural darwinism revisited.
Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei
2013-01-01
The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.
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Valentino Anthony Simpao
2000-01-01
Full Text Available Herein an enhanced Hodgkin-Huxley (H-H type model of neuron dynamics is solved analytically via formal methods. Our model is a variant of an earlier one by M.A. Mahrous and H.Y. Alkahby [1]. Their modified model is realized by a hyperbolic quasi-linear diffusion operator with time-delay parameters; this compared to the original H-H model with standard parabolic quasi-linear diffusion operator and no time-delay parameters. Besides these features, the present model also incorporates terms describing signal dissipation into the background substrate (e.g., conductance to ground, making it more experimentally amenable. The solutions which results via the present scheme are of traveling-wave profile, which agree qualitatively with those observed in actual electro-physiological measurements made on the neural systems originally studied by H-H These results confirm the physiological soundness of the enhanced model and of the preliminary assumptions which motivated the present solution strategy; the comparison of the present results with actual electro-physiological data displays shall appear in later publications.
The Hodgkin-Huxley heritage: from channels to circuits.
Catterall, William A; Raman, Indira M; Robinson, Hugh P C; Sejnowski, Terrence J; Paulsen, Ole
2012-10-10
The Hodgkin-Huxley studies of the action potential, published 60 years ago, are a central pillar of modern neuroscience research, ranging from molecular investigations of the structural basis of ion channel function to the computational implications at circuit level. In this Symposium Review, we aim to demonstrate the ongoing impact of Hodgkin's and Huxley's ideas. The Hodgkin-Huxley model established a framework in which to describe the structural and functional properties of ion channels, including the mechanisms of ion permeation, selectivity, and gating. At a cellular level, the model is used to understand the conditions that control both the rate and timing of action potentials, essential for neural encoding of information. Finally, the Hodgkin-Huxley formalism is central to computational neuroscience to understand both neuronal integration and circuit level information processing, and how these mechanisms might have evolved to minimize energy cost.
Aldous Huxley: a beginner's guide
O'Hara, Kieron
2012-01-01
Author of Brave New World and The Doors of Perception, and inventor of the term 'psychedelic', Aldous Huxley was a global trend-setter ahead of his time. Charting his transformation from society satirist to Californian guru-mystic, Aldous Huxley: A Beginner's Guide shows how his ideas evolved and why his writing is still vitally relevant today - from detailing the lures of consumerism to exploring individual responsibility in a globalised world. With biographical notes on Huxley's extraordina...
Evolution and Education: Lessons from Thomas Huxley
Lyons, Sherrie Lynne
2010-01-01
Thomas Huxley more than anyone else was responsible for disseminating Darwin's theory in the western world and maintained that investigating the history of life should be regarded as a purely scientific question free of theological speculation. The content and rhetorical strategy of Huxley's defense of evolution is analyzed. Huxley argued that the…
Autonomic neural control of heart rate during dynamic exercise: revisited.
White, Daniel W; Raven, Peter B
2014-06-15
The accepted model of autonomic control of heart rate (HR) during dynamic exercise indicates that the initial increase is entirely attributable to the withdrawal of parasympathetic nervous system (PSNS) activity and that subsequent increases in HR are entirely attributable to increases in cardiac sympathetic activity. In the present review, we sought to re-evaluate the model of autonomic neural control of HR in humans during progressive increases in dynamic exercise workload. We analysed data from both new and previously published studies involving baroreflex stimulation and pharmacological blockade of the autonomic nervous system. Results indicate that the PSNS remains functionally active throughout exercise and that increases in HR from rest to maximal exercise result from an increasing workload-related transition from a 4 : 1 vagal-sympathetic balance to a 4 : 1 sympatho-vagal balance. Furthermore, the beat-to-beat autonomic reflex control of HR was found to be dependent on the ability of the PSNS to modulate the HR as it was progressively restrained by increasing workload-related sympathetic nerve activity. (i) increases in exercise workload-related HR are not caused by a total withdrawal of the PSNS followed by an increase in sympathetic tone; (ii) reciprocal antagonism is key to the transition from vagal to sympathetic dominance, and (iii) resetting of the arterial baroreflex causes immediate exercise-onset reflexive increases in HR, which are parasympathetically mediated, followed by slower increases in sympathetic tone as workloads are increased. © 2014 The Authors. The Journal of Physiology © 2014 The Physiological Society.
Population Encoding With Hodgkin-Huxley Neurons.
Lazar, Aurel A
2010-02-01
The recovery of (weak) stimuli encoded with a population of Hodgkin-Huxley neurons is investigated. In the absence of a stimulus, the Hodgkin-Huxley neurons are assumed to be tonically spiking. The methodology employed calls for 1) finding an input-output (I/O) equivalent description of the Hodgkin-Huxley neuron and 2) devising a recovery algorithm for stimuli encoded with the I/O equivalent neuron(s). A Hodgkin-Huxley neuron with multiplicative coupling is I/O equivalent with an Integrate-and-Fire neuron with a variable threshold sequence. For bandlimited stimuli a perfect recovery of the stimulus can be achieved provided that a Nyquist-type rate condition is satisfied. A Hodgkin-Huxley neuron with additive coupling and deterministic conductances is first-order I/O equivalent with a Project-Integrate-and-Fire neuron that integrates a projection of the stimulus on the phase response curve. The stimulus recovery is formulated as a spline interpolation problem in the space of finite length bounded energy signals. A Hodgkin-Huxley neuron with additive coupling and stochastic conductances is shown to be first-order I/O equivalent with a Project-Integrate-and-Fire neuron with random thresholds. For stimuli modeled as elements of Sobolev spaces the reconstruction algorithm minimizes a regularized quadratic optimality criterion. Finally, all previous recovery results of stimuli encoded with Hodgkin-Huxley neurons with multiplicative and additive coupling, and deterministic and stochastic conductances are extended to stimuli encoded with a population of Hodgkin-Huxley neurons.
[R. Goldschmidt and J. Huxley: creative parallelisms].
Golubovskiĭ, M D; Gall, Ia M
2003-01-01
The comparative analysis of scientific heritage of Richard Goldschmidt and Julian Huxley shows convincingly the resemblance of these two scientists' views over the core problems of evolutionary theory, genetics and development biology. They both contributed to developing a triad "genetics--development--evolution". The problem of a relative growth of animals was the central point in both Goldschmidt's and Huxley's works. Huxley developed a formula of the allometric growth (law of constant differential growth) while Goldschmidt was the first to draw up the broad interpretation of the consequences of that phenomenon. Both scientists belonged to initiators of development genetics and used the "non-morganian" genetics in their efforts of solving problems of macroevolution. Goldschmidt tended toward an idea of an important role of macromutation in the process of macroevolution, though Huxley adhered to more moderate views. But at the same time the concept of preadaptive mutations proposed by Huxley was close to Goldschmidt's idea of macromutants. It is shown that both scientists analyzed profoundly the changes in early stages of embryogenesis in respect to macroevolution. It is not likely to be reasonable to oppose firmly Goldschmidt's saltationism to the evolutionary synthesis of Huxley. They developed the larger biological problems in a similar way, and undoubtedly their works in the field helped to enrich the development of the views over genetics and evolution. The open-minded analysis of Goldschmidt's and Huxley's concepts leads to creating modern and up-to-date views over the theory of evolution where seemingly incompatible things go together rather well and supplement each other. Evo-Devo rediscovered Goldshmidt's Biology and Huxley's Synthesis.
Edge detection based on Hodgkin-Huxley neuron model simulation.
Yedjour, Hayat; Meftah, Boudjelal; Lézoray, Olivier; Benyettou, Abdelkader
2017-04-03
In this paper, we propose a spiking neural network model for edge detection in images. The proposed model is biologically inspired by the mechanisms employed by natural vision systems, more specifically by the biologically fulfilled function of simple cells of the human primary visual cortex that are selective for orientation. Several aspects are studied in this model according to three characteristics: feedforward spiking neural structure; conductance-based model of the Hodgkin-Huxley neuron and Gabor receptive fields structure. A visualized map is generated using the firing rate of neurons representing the orientation map of the visual cortex area. We have simulated the proposed model on different images. Successful computer simulation results are obtained. For comparison, we have chosen five methods for edge detection. We finally evaluate and compare the performances of our model toward contour detection using a public dataset of natural images with associated contour ground truths. Experimental results show the ability and high performance of the proposed network model.
Institute of Scientific and Technical Information of China (English)
李冰; 彭建华; 刘延柱
2005-01-01
基于神经系统微观生理结构,给出具有空间分布随机延时的神经元间耦合,而这种随机延时描述峰电位从突触前神经元到突触后神经元在轴突上传播所需要的时间.记忆由时空发放的神经元集群表达.通过加入并改变噪声的强度,研究了噪声对Hodgkin-Huxley(HH)神经元网络系统联想记忆的作用,在噪声涨落的作用下,系统取得了对不完整输入的记忆恢复,得到与熟知的随机共振完全一致的结果.
Institute of Scientific and Technical Information of China (English)
杜红伟; 王从庆
2007-01-01
HH(Hodgkin-Huxley)神经细胞模型一般被用于研究单个神经细胞的行为和特性,很少被用于构造人工神经系统.考虑神经细胞具有抑制性联结和兴奋性联结,将HH模型进行发展,提出了基于HH模型的神经元群,模拟大脑皮层柱的生理结构及侧抑制特性.分别将皮层柱内及皮层柱间的侧抑制机制应用于神经元群编码、解码,进行位置跟踪;改变解码策略,实现"胜者为王"功能.仿真实验表明了该神经元群模型的有效性,侧抑制特性的应用大大提高了位置跟踪精度、"胜者为王"效果.
On nonclassical symmetries of generalized Huxley equations
Ivanova, Nataliya M
2010-01-01
Nonclassical symmetries of a class of generalized Huxley equations of form $u_t=u_{xx}+k(x)u^2(1-u)$ are found. More precisely, for the class under consideration we completely classify reduction operators with $\\tau=1$ and give a wide number of examples of equations admitting reduction operators with $\\tau=0$.
Unidirectional synchronization of Hodgkin-Huxley neurons
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Cornejo-Perez, Octavio [Division de Matematicas Aplicadas y Sistemas, Computacionales, IPICYT, Apdo. Postal 3-74 Tangamanga, 78231 San Luis Potosi (Mexico)]. E-mail: octavio@ipicyt.edu.mx; Femat, Ricardo [Division de Matematicas Aplicadas y Sistemas, Computacionales, IPICYT, Apdo. Postal 3-74 Tangamanga, 78231 San Luis Potosi (Mexico)]. E-mail: rfemat@ipicyt.edu.mx
2005-07-01
Synchronization dynamics of two noiseless Hodgkin-Huxley (HH) neurons under the action of feedback control is studied. The spiking patterns of the action potentials evoked by periodic external modulations attain synchronization states under the feedback action. Numerical simulations for the synchronization dynamics of regular-irregular desynchronized spiking sequences are displayed. The results are discussed in context of generalized synchronization. It is also shown that the HH neurons can be synchronized in face of unmeasured states.
Beyond perceptual expertise: revisiting the neural substrates of expert object recognition.
Harel, Assaf; Kravitz, Dwight; Baker, Chris I
2013-12-27
Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing primarily on results from functional brain imaging, and propose an interactive framework that incorporates the impact of high-level factors, such as attention and conceptual knowledge, in supporting expertise. This framework contrasts with the perceptual view of object expertise that has concentrated largely on stimulus-driven processing in visual cortex. One prominent version of this perceptual account has almost exclusively focused on the relation of expertise to face processing and, in terms of the neural substrates, has centered on face-selective cortical regions such as the Fusiform Face Area (FFA). We discuss the limitations of this face-centric approach as well as the more general perceptual view, and highlight that expert related activity is: (i) found throughout visual cortex, not just FFA, with a strong relationship between neural response and behavioral expertise even in the earliest stages of visual processing, (ii) found outside visual cortex in areas such as parietal and prefrontal cortices, and (iii) modulated by the attentional engagement of the observer suggesting that it is neither automatic nor driven solely by stimulus properties. These findings strongly support a framework in which object expertise emerges from extensive interactions within and between the visual system and other cognitive systems, resulting in widespread, distributed patterns of expertise-related activity across the entire cortex.
Stimulus-dependent refractoriness in the Frankenhaeuser-Huxley model.
Morse, R P; Allingham, D; Stocks, N G
2015-10-07
Phenomenological neural models, such as the leaky integrate-and-fire model, normally have a fixed refractory time-course that is independent of the stimulus. The recovery of threshold following an action potential is typically based on physiological experiments that use a two-pulse paradigm in which the first pulse is suprathreshold and causes excitation and the second pulse is used to determine the threshold at various intervals following the first. In such experiments, the nerve is completely unstimulated between the two pulses. This contrasts the receptor stimuli in normal physiological systems and the electrical stimuli used by cochlear implants and other neural prostheses. A numerical study of the Frankenhaeuser-Huxley conductance-based model of nerve fibre was therefore undertaken to investigate the effect of stimulation on refractoriness. We found that the application of a depolarizing stimulus during the later part of what is classically regarded as the absolute refractory period could effectively prolong the absolute refractory period, while leaving the refractory time-constants and other refractory parameters largely unaffected. Indeed, long depolarizing pulses, which would have been suprathreshold if presented to a resting nerve fibre, appeared to block excitation indefinitely. Stimulation during what is classically regarded as the absolute refractory period can therefore greatly affect the temporal response of a nerve. We conclude that the classical definition of absolute refractory period should be refined to include only the initial period following an action potential when an ongoing stimulus would not affect threshold; this period was found to be about half as long as the classical absolute refractory period. We further conclude that the stimulus-dependent nature of the relative refractory period must be considered when developing a phenomenological nerve model for complex stimuli.
Heuristics for the Hodgkin-Huxley system.
Hoppensteadt, Frank
2013-09-01
Hodgkin and Huxley (HH) discovered that voltages control ionic currents in nerve membranes. This led them to describe electrical activity in a neuronal membrane patch in terms of an electronic circuit whose characteristics were determined using empirical data. Due to the complexity of this model, a variety of heuristics, including relaxation oscillator circuits and integrate-and-fire models, have been used to investigate activity in neurons, and these simpler models have been successful in suggesting experiments and explaining observations. Connections between most of the simpler models had not been made clear until recently. Shown here are connections between these heuristics and the full HH model. In particular, we study a new model (Type III circuit): It includes the van der Pol-based models; it can be approximated by a simple integrate-and-fire model; and it creates voltages and currents that correspond, respectively, to the h and V components of the HH system.
Singularly perturbed Burger-Huxley equation: Analytical solution ...
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Keywords: Burger-Huxley equation, iteration method, analytical solution, ... dynamics, chemical kinetics and mathematical biology (Albowitz and Clarkson, ... numbers, Navier-Stokes flows with large Reynolds numbers, chemical reactor theory, ...
Whistles, bells, and cogs in machines: Thomas Huxley and epiphenomenalism.
Greenwood, John
2010-01-01
In this paper I try to shed some historical light upon the doctrine of epiphenomenalism, by focusing on the version of epiphenomenalism championed by Thomas Huxley, which is often treated as a classic statement of the doctrine. I argue that it is doubtful if Huxley held any form of metaphysical epiphenomenalism, and that he held a more limited form of empirical epiphenomenalism with respect to consciousness but not with respect to mentality per se. Contrary to what is conventionally supposed, Huxley's empirical epiphenomenalism with respect to consciousness was not simply based upon the demonstration of the neurophysiological basis of conscious mentality, or derived from the extension of mechanistic and reflexive principles of explanation to encompass all forms of animal and human behavior, but was based upon the demonstration of purposive and coordinated animal and human behavior in the absence of consciousness. Given Huxley's own treatment of mentality, his characterization of animals and humans as "conscious automata" was not well chosen.
Remembrance of Hugh E. Huxley, a founder of our field.
Pollard, Thomas D; Goldman, Yale E
2013-09-01
Hugh E. Huxley (1924-2013) carried out structural studies by X-ray fiber diffraction and electron microscopy that established how muscle contracts. Huxley's sliding filament mechanism with an ATPase motor protein taking steps along an actin filament, established the paradigm not only for muscle contraction but also for other motile systems using actin and unconventional myosins, microtubules and dynein and microtubules and kinesin.
Science, Sexuality, and the Novels of Huxley and Houellebecq
2003-01-01
In her article "Science, Sexuality, and the Novels of Huxley and Houellebecq," Angela C. Holzer begins with an introduction to recent discourse about contemporary culture by Francis Fukuyama, notably in his book Our Posthuman Future (2001). Next, Holzer introduces twentieth-century literary representations of genetic engineering. Focusing on Huxley's Brave New World (1932) and on Houellebecq's Les Particules élémentaires (1998), Holzer discusses differences in "utopian" literature when linked...
Synchronization control of Hodgkin-Huxley neurons exposed to ELF electric field
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Che Yanqiu [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China); Wang Jiang [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)], E-mail: jiangwang@tju.edu.cn; Zhou Sisi; Deng Bin [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2009-05-30
This paper presents an adaptive neural network H{sub {infinity}} control for unidirectional synchronization of modified Hodgkin-Huxley (HH) neurons exposed to extremely low frequency (ELF) electric field. The proposed modified HH neurons exhibit periodic and chaotic dynamics in response to sinusoidal electric field stimulation. Based on the Lyapunov stability theory, we derive the updated laws of neural network for approximating the nonlinear uncertain functions of the error dynamical system. The H{sub {infinity}} design technique makes the controller robust to unmodeled dynamics, disturbances and approximate errors. The proposed controller not only ensures closed-loop stability, but also guarantees an H{sub {infinity}} performance for the synchronization error system. The states of the controlled slave system exponentially synchronize with that of the master one after control. The simulation results demonstrate the validity of the proposed method.
Channel noise effects on first spike latency of a stochastic Hodgkin-Huxley neuron
Maisel, Brenton; Lindenberg, Katja
2017-02-01
While it is widely accepted that information is encoded in neurons via action potentials or spikes, it is far less understood what specific features of spiking contain encoded information. Experimental evidence has suggested that the timing of the first spike may be an energy-efficient coding mechanism that contains more neural information than subsequent spikes. Therefore, the biophysical features of neurons that underlie response latency are of considerable interest. Here we examine the effects of channel noise on the first spike latency of a Hodgkin-Huxley neuron receiving random input from many other neurons. Because the principal feature of a Hodgkin-Huxley neuron is the stochastic opening and closing of channels, the fluctuations in the number of open channels lead to fluctuations in the membrane voltage and modify the timing of the first spike. Our results show that when a neuron has a larger number of channels, (i) the occurrence of the first spike is delayed and (ii) the variation in the first spike timing is greater. We also show that the mean, median, and interquartile range of first spike latency can be accurately predicted from a simple linear regression by knowing only the number of channels in the neuron and the rate at which presynaptic neurons fire, but the standard deviation (i.e., neuronal jitter) cannot be predicted using only this information. We then compare our results to another commonly used stochastic Hodgkin-Huxley model and show that the more commonly used model overstates the first spike latency but can predict the standard deviation of first spike latencies accurately. We end by suggesting a more suitable definition for the neuronal jitter based upon our simulations and comparison of the two models.
Pruessner, Marita; Cullen, Alexis E; Aas, Monica; Walker, Elaine F
2017-02-01
Over the past decade, our understanding of the role of stress in serious mental illness has become more sophisticated. In this paper, we revisit the neural diathesis-stress model of schizophrenia that was initially proposed in 1997 and updated in 2008. In light of cumulative research findings, we must now encompass evidence on the premorbid periods of psychosis, and our more nuanced understanding of hypothalamic-pituitary-adrenal (HPA) axis function and its association with neurodevelopmental, epigenetic, neurotransmitter, and inflammatory processes, as well as brain structure and function. Giving consideration to the methodological complexities that have become more apparent as research in this area has burgeoned, the various indices of HPA axis function, and the different stages of illness, we review relevant research published since the 2008 update of the model. We conclude by proposing an extended neural diathesis-stress model that addresses the broader neurobiological context of stress psychobiology in psychosis progression. Implications of this model for best practice, with regards to both future research and treatment strategies, are discussed.
Temperature Effects on Information Capacity and Energy Efficiency of Hodgkin-Huxley Neuron
Wang, Long-Fei; Liu, Xiao-Zhi; Song, Ya-lei; Yu, Lian-Chun
2015-01-01
Recent experimental and theoretical studies show that energy efficiency, which measures the amount of information processed by a neuron with per unit of energy consumption, plays an important role in the evolution of neural systems. Here, we calculated the information rates and energy efficiencies of the Hodgkin-Huxley (HH) neuron model at different temperatures in a noisy environment. We found that both the information rate and energy efficiency are maximized by certain temperatures. Though the information rate and energy efficiency cannot be maximized simultaneously, the neuron holds a high information processing capacity at the temperature corresponding to maximal energy efficiency. Our results support the idea that the energy efficiency is a selective pressure that influences the evolution of nervous systems.
Rhythmic Oscillations of Excitatory Bursting Hodkin-Huxley Neuronal Network with Synaptic Learning.
Shi, Qi; Han, Fang; Wang, Zhijie; Li, Caiyun
2016-01-01
Rhythmic oscillations of neuronal network are actually kind of synchronous behaviors, which play an important role in neural systems. In this paper, the properties of excitement degree and oscillation frequency of excitatory bursting Hodkin-Huxley neuronal network which incorporates a synaptic learning rule are studied. The effects of coupling strength, synaptic learning rate, and other parameters of chemical synapses, such as synaptic delay and decay time constant, are explored, respectively. It is found that the increase of the coupling strength can weaken the extent of excitement, whereas increasing the synaptic learning rate makes the network more excited in a certain range; along with the increasing of the delay time and the decay time constant, the excitement degree increases at the beginning, then decreases, and keeps stable. It is also found that, along with the increase of the synaptic learning rate, the coupling strength, the delay time, and the decay time constant, the oscillation frequency of the network decreases monotonically.
Temperature Effects on Information Capacity and Energy Efficiency of Hodgkin-Huxley Neuron
Wang, Long-Fei; Jia, Fei; Liu, Xiao-Zhi; Song, Ya-Lei; Yu, Lian-Chun
2015-10-01
Recent experimental and theoretical studies show that energy efficiency, which measures the amount of information processed by a neuron with per unit of energy consumption, plays an important role in the evolution of neural systems. Here, we calculated the information rates and energy efficiencies of the Hodgkin-Huxley (HH) neuron model at different temperatures in a noisy environment. We found that both the information rate and energy efficiency are maximized by certain temperatures. Though the information rate and energy efficiency cannot be maximized simultaneously, the neuron holds a high information processing capacity at the temperature corresponding to maximal energy efficiency. Our results support the idea that the energy efficiency is a selective pressure that influences the evolution of nervous systems.
Wu, Yanan; Gong, Yubing; Wang, Qi
2015-04-01
In this paper, we numerically study the effect of autapse on the synchronization of Newman-Watts small-world Hodgkin-Huxley neuron network. It is found that the neurons exhibit synchronization transitions as autaptic self-feedback delay is varied, and the phenomenon becomes strongest when autaptic self-feedback strength is optimal. This phenomenon also changes with the change of coupling strength and network randomness and become strongest when they are optimal. There are similar synchronization transitions for electrical and chemical autapse, but the synchronization transitions for chemical autapse occur more frequently and are stronger than those for electrical synapse. The underlying mechanisms are briefly discussed in quality. These results show that autaptic activity plays a subtle role in the synchronization of the neuronal network. These findings may find potential implications of autapse for the information processing and transmission in neural systems.
Dynamic Behavior of Artificial Hodgkin-Huxley Neuron Model Subject to Additive Noise.
Kang, Qi; Huang, BingYao; Zhou, MengChu
2016-09-01
Motivated by neuroscience discoveries during the last few years, many studies consider pulse-coupled neural networks with spike-timing as an essential component in information processing by the brain. There also exists some technical challenges while simulating the networks of artificial spiking neurons. The existing studies use a Hodgkin-Huxley (H-H) model to describe spiking dynamics and neuro-computational properties of each neuron. But they fail to address the effect of specific non-Gaussian noise on an artificial H-H neuron system. This paper aims to analyze how an artificial H-H neuron responds to add different types of noise using an electrical current and subunit noise model. The spiking and bursting behavior of this neuron is also investigated through numerical simulations. In addition, through statistic analysis, the intensity of different kinds of noise distributions is discussed to obtain their relationship with the mean firing rate, interspike intervals, and stochastic resonance.
Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons
Glaze, Tera A.; Lewis, Scott; Bahar, Sonya
2016-08-01
Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes.
Dartington: A Principal Source of Inspiration behind Aldous Huxley's "Island".
Parsons, David
1987-01-01
Describes Dartington Hall School in Devon, England, which between the 1920s and 1970s implemented an educational system combining traditional Hindu religious philosophy and ideals of living and Western scientific knowledge and work experience. Considers ways Dartington educationally and socially resembled Aldous Huxley's utopia in…
Huxley College of Environmental Studies, Western Washington University.
Miles, John C.
1987-01-01
Describes the programs of Huxley College (Washington) which were designed to provide an environmental studies thread through all of its academic endeavors. Addresses the development of the curriculum of both the undergraduate and graduate levels. Discusses its research focal points and its prospects for the future. (TW)
Statistical mechanics of the Huxley-Simmons model.
Caruel, M; Truskinovsky, L
2016-06-01
The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971)NATUAS0028-083610.1038/233533a0] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions.
Statistical mechanics of the Huxley-Simmons model
Caruel, M
2016-01-01
The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971)] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power-stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions.
Statistical mechanics of the Huxley-Simmons model
Caruel, M.; Truskinovsky, L.
2016-06-01
The chemomechanical model of Huxley and Simmons (HS) [A. F. Huxley and R. M. Simmons, Nature 233, 533 (1971), 10.1038/233533a0] provides a paradigmatic description of mechanically induced collective conformational changes relevant in a variety of biological contexts, from muscles power stroke and hair cell gating to integrin binding and hairpin unzipping. We develop a statistical mechanical perspective on the HS model by exploiting a formal analogy with a paramagnetic Ising model. We first study the equilibrium HS model with a finite number of elements and compute explicitly its mechanical and thermal properties. To model kinetics, we derive a master equation and solve it for several loading protocols. The developed formalism is applicable to a broad range of allosteric systems with mean-field interactions.
An efficient method for solving fractional Hodgkin–Huxley model
Energy Technology Data Exchange (ETDEWEB)
Nagy, A.M., E-mail: abdelhameed_nagy@yahoo.com [Department of Mathematics, Faculty of Science, Benha University, 13518 Benha (Egypt); Sweilam, N.H., E-mail: n_sweilam@yahoo.com [Department of Mathematics, Faculty of Science, Cairo University, 12613 Giza (Egypt)
2014-06-13
In this paper, we present an accurate numerical method for solving fractional Hodgkin–Huxley model. A non-standard finite difference method (NSFDM) is implemented to study the dynamic behaviors of the proposed model. The Grünwald–Letinkov definition is used to approximate the fractional derivatives. Numerical results are presented graphically reveal that NSFDM is easy to implement, effective and convenient for solving the proposed model. - Highlights: • An accurate numerical method for solving fractional Hodgkin–Huxley model is given. • Non-standard finite difference method (NSFDM) is implemented to the proposed model. • NSFDM can solve differential equations involving derivatives of non-integer order. • NDFDM is very powerful and efficient technique for solving the proposed model.
Parameter estimation of the Huxley cross-bridge muscle model in humans.
Vardy, Alistair N; de Vlugt, Erwin; van der Helm, Frans C T
2012-01-01
The Huxley model has the potential to provide more accurate muscle dynamics while affording a physiological interpretation at cross-bridge level. By perturbing the wrist at different velocities and initial force levels, reliable Huxley model parameters were estimated in humans in vivo using a Huxley muscle-tendon complex. We conclude that these estimates may be used to investigate and monitor changes in microscopic elements of muscle functioning from experiments at joint level.
Chiral Solutions to Generalized Burgers and Burgers-Huxley Equations
Bazeia, D
1998-01-01
We investigate generalizations of the Burgers and Burgers-Huxley equations. The investigations we offer focus attention mainly on presenting explict analytical solutions by means of relating these generalized equations to relativistic 1+1 dimensional systems of scalar fields where topological solutions are known to play a role. Emphasis is given on chiral solutions, that is, on the possibility of finding solutions that travel with velocities determined in terms of the parameters that identify the generalized equation, with a definite sign.
An efficient method for solving fractional Hodgkin-Huxley model
Nagy, A. M.; Sweilam, N. H.
2014-06-01
In this paper, we present an accurate numerical method for solving fractional Hodgkin-Huxley model. A non-standard finite difference method (NSFDM) is implemented to study the dynamic behaviors of the proposed model. The Grünwald-Letinkov definition is used to approximate the fractional derivatives. Numerical results are presented graphically reveal that NSFDM is easy to implement, effective and convenient for solving the proposed model.
EXPONENTIAL TIME DIFFERENCING FOR HODGKIN-HUXLEY-LIKE ODES.
Börgers, Christoph; Nectow, Alexander R
2013-01-01
Several authors have proposed the use of exponential time differencing (ETD) for Hodgkin-Huxley-like partial and ordinary differential equations (PDEs and ODEs). For Hodgkin-Huxley-like PDEs, ETD is attractive because it can deal effectively with the stiffness issues that diffusion gives rise to. However, large neuronal networks are often simulated assuming "space-clamped" neurons, i.e., using the Hodgkin-Huxley ODEs, in which there are no diffusion terms. Our goal is to clarify whether ETD is a good idea even in that case. We present a numerical comparison of first- and second-order ETD with standard explicit time-stepping schemes (Euler's method, the midpoint method, and the classical fourth-order Runge-Kutta method). We find that in the standard schemes, the stable computation of the very rapid rising phase of the action potential often forces time steps of a small fraction of a millisecond. This can result in an expensive calculation yielding greater overall accuracy than needed. Although it is tempting at first to try to address this issue with adaptive or fully implicit time-stepping, we argue that neither is effective here. The main advantage of ETD for Hodgkin-Huxley-like systems of ODEs is that it allows underresolution of the rising phase of the action potential without causing instability, using time steps on the order of one millisecond. When high quantitative accuracy is not necessary and perhaps, because of modeling inaccuracies, not even useful, ETD allows much faster simulations than standard explicit time-stepping schemes. The second-order ETD scheme is found to be substantially more accurate than the first-order one even for large values of Δt.
Action potential initiation in the hodgkin-huxley model.
Directory of Open Access Journals (Sweden)
Lucy J Colwell
2009-01-01
Full Text Available A recent paper of B. Naundorf et al. described an intriguing negative correlation between variability of the onset potential at which an action potential occurs (the onset span and the rapidity of action potential initiation (the onset rapidity. This correlation was demonstrated in numerical simulations of the Hodgkin-Huxley model. Due to this antagonism, it is argued that Hodgkin-Huxley-type models are unable to explain action potential initiation observed in cortical neurons in vivo or in vitro. Here we apply a method from theoretical physics to derive an analytical characterization of this problem. We analytically compute the probability distribution of onset potentials and analytically derive the inverse relationship between onset span and onset rapidity. We find that the relationship between onset span and onset rapidity depends on the level of synaptic background activity. Hence we are able to elucidate the regions of parameter space for which the Hodgkin-Huxley model is able to accurately describe the behavior of this system.
Lutz, J; Brühl, A B; Scheerer, H; Jäncke, L; Herwig, U
2016-09-01
Mindful self-awareness is central to mindfulness meditation and plays a key role in its salutary effects. It has been related to decreased activation in cortical midline structures (CMS) and amygdala, and increased activation in somatosensory regions. However, findings in untrained individuals are contradictory, and scarce in experienced meditators. Using fMRI, we investigated experienced mindfulness meditators (LTM, n=21, average 4652 practice-hours) and matched meditation-naïve participants (MNP, n=19) during short periods of mindful self-awareness (FEEL) and self-referential thinking (THINK). We report somatosensory activations and decreases in CMS during FEEL for both groups, but significantly stronger decreases in prefrontal CMS in LTM. LTM further showed decreases in language-related and amygdala regions, but the latter was not significantly different between groups. Overall, higher activations in amygdala and mid-line regions during FEEL were related to levels of depressiveness. Neural patterns of mindful self-awareness emerge already in MNP but more pronounced in LTM. Specifically, meditation training might reduce self-reference and verbalization during mindful awareness. We further corroborate the suggested link between mindfulness and healthy self-related functions on the neural level. Longitudinal studies need to corroborate these findings.
Theoretical analysis of transcranial magneto-acoustical stimulation with Hodgkin–Huxley neuron model
Directory of Open Access Journals (Sweden)
Yi eYuan
2016-04-01
Full Text Available Transcranial magneto-acoustical stimulation (TMAS is a novel stimulation technology in which an ultrasonic wave within a magnetostatic field generates an electric current in an area of interest in the brain to modulate neuronal activities. As a key part of the neural network, neurons transmit information in the nervous system. However, the effect of TMAS on the neuronal firing rhythm remains unknown. To address this problem, we investigated the stimulatory mechanism of TMAS on neurons with a Hodgkin-Huxley neuron model. The simulation results indicate that the magnetostatic field intensity and ultrasonic power can affect the amplitude and interspike interval of neuronal action potential under continuous wave ultrasound. The simulation results also show that the ultrasonic power, duty cycle and repetition frequency can alter the firing rhythm of neural action potential under pulsed ultrasound. This study can help to reveal and explain the biological mechanism of TMAS and to provide a theoretical basis for TMAS in the treatment or rehabilitation of neuropsychiatric disorders.
Yuan, Yi; Chen, Yudong; Li, Xiaoli
2016-01-01
Transcranial magneto-acoustical stimulation (TMAS) is a novel stimulation technology in which an ultrasonic wave within a magnetostatic field generates an electric current in an area of interest in the brain to modulate neuronal activities. As a key part of the neural network, neurons transmit information in the nervous system. However, the effect of TMAS on the neuronal firing pattern remains unknown. To address this problem, we investigated the stimulatory mechanism of TMAS on neurons, by using a Hodgkin-Huxley neuron model. The simulation results indicated that the magnetostatic field intensity and ultrasonic power affect the amplitude and interspike interval of neuronal action potential under a continuous wave ultrasound. The simulation results also showed that the ultrasonic power, duty cycle and repetition frequency can alter the firing pattern of neural action potential under pulsed wave ultrasound. This study may help to reveal and explain the biological mechanism of TMAS and to provide a theoretical basis for TMAS in the treatment or rehabilitation of neuropsychiatric disorders.
Salzer, Yael; de Hollander, Gilles; Forstmann, Birte U
2017-02-24
The Simon task is one of the most prominent interference tasks and has been extensively studied in experimental psychology and cognitive neuroscience. Despite years of research, the underlying mechanism driving the phenomenon and its temporal dynamics are still disputed. Within the framework of the review, we adopt a model-based cognitive neuroscience approach. We first go over key findings in the literature of the Simon task, discuss competing qualitative cognitive theories and the difficulty of testing them empirically. We then introduce sequential sampling models, a particular class of mathematical cognitive process models. Finally, we argue that the brain architecture accountable for the processing of spatial ('where') and non-spatial ('what') information, could constrain these models. We conclude that there is a clear need to bridge neural and behavioral measures, and that mathematical cognitive models may facilitate the construction of this bridge and work towards revealing the underlying mechanisms of the Simon effect.
Institute of Scientific and Technical Information of China (English)
焦玉洁
2011-01-01
@@ 朱利安·赫胥黎(Julian Huxley),1887年6月生于英国伦敦市,1975年2月去世,是英网著名的动物学家、哲学家、教育家和作家.他曾担任联合国教育科学文化组织第一届总干事,也是世界自然基金会(WWF)创始成员之一.作为生物学家,他提倡自然选择,是现代综合进化论领军人物.
Saïghi, S; Bornat, Y; Tomas, J; Le Masson, G; Renaud, S
2011-02-01
In this paper, we present a library of analog operators used for the analog real-time computation of the Hodgkin-Huxley formalism. These operators make it possible to design a silicon (Si) neuron that is dynamically tunable, and that reproduces different kinds of neurons. We used an original method in neuromorphic engineering to characterize this Si neuron. In electrophysiology, this method is well known as the "voltage-clamp" technique. We also compare the features of an application-specific integrated circuit built with this library with results obtained from software simulations. We then present the complex behavior of neural membrane voltages and the potential applications of this Si neuron.
Yuan, Yi; Pang, Na; Chen, Yudong; Wang, Yi; Li, Xiaoli
2017-01-01
Transcranial magneto-acoustical stimulation (TMAS) uses ultrasonic waves and a static magnetic field to generate electric current in nerve tissues for the purpose of modulating neuronal activities. It has the advantage of high spatial resolution and penetration depth. Neuronal firing rhythms carry and transmit nerve information in neural systems. In this study, we investigated the phase-locking characteristics of neuronal firing rhythms with TMAS based on the Hodgkin-Huxley neuron model. The simulation results indicate that the modulation frequency of ultrasound can affect the phase-locking behaviors. The results of this study may help us to explain the potential firing mechanism of TMAS.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Based on the coupled stochastic Hodgkin-Huxley neurons, we numerically studied the effect of gating currents of ion channels, as well as coupling and the number of neurons, on the collective spiking rate and regularity in the coupled system. It was found, for a given coupling strength and with a relatively large number of neurons, when gating currents are applied, the collective spiking regularity decreases; meanwhile, the collective spiking rate increases, indicating that gating currents can aggravate the de-synchronization of the spikings of all neurons. However, gating currents caused hardly any effect in the spiking of any individual neuron of the coupled system. This result, different from the reduction of the spiking rate by gating currents in a single neuron, provides a new insight into the effect of gating cur-rents on the global information processing and signal transduction in real neural systems.
Institute of Scientific and Technical Information of China (English)
GONG YuBing; XIE YanHang; XU Bo; MA XiaoGuang
2009-01-01
Based on the coupled stochastic Hodgkin-Huxley neurons, we numerically studied the effect of gating currents of ion channels, as well as coupling and the number of neurons, on the collective spiking rate and regularity in the coupled system, it was found, for a given coupling strength and with a relatively large number of neurons, when gating currents are applied, the collective spiking regularity decreases; meanwhile, the collective spiking rate increases, indicating that gating currents can aggravate the de-synchronization of the spikings of all neurons. However, gating currents caused hardly any effect in the spiking of any individual neuron of the coupled system. This result, different from the reduction of the spiking rate by gating currents in a single neuron, provides a new insight into the effect of gating cur-rents on the global information processing and signal transduction in real neural systems.
Phase-locking and chaos in a silent Hodgkin-Huxley neuron exposed to sinusoidal electric field
Energy Technology Data Exchange (ETDEWEB)
Che Yanqiu [School of Electrical Engineering and Automation, Tianjin University, 300072 (China); Wang Jiang [School of Electrical Engineering and Automation, Tianjin University, 300072 (China)], E-mail: jiangwang@tju.edu.cn; Si Wenjie; Fei Xiangyang [School of Electrical Engineering and Automation, Tianjin University, 300072 (China)
2009-01-15
Neuronal firing patterns are related to the information processing in neural system. This paper investigates the response characteristics of a silent Hodgkin-Huxley neuron to the stimulation of externally-applied sinusoidal electric field. The neuron exhibits both p:q phase-locked (i.e. a periodic oscillation defined as p action potentials generated by q cycle stimulations) and chaotic behaviors, depending on the values of stimulus frequencies and amplitudes. In one-parameter space, a rich bifurcation structure including period-adding without chaos and phase-locking alternated with chaos suggests frequency discrimination of the neuronal firing patterns. Furthermore, by mapping out Arnold tongues, we partition the amplitude-frequency parameter space in terms of the qualitative behaviors of the neuron. Thus the neuron's information (firing patterns) encodes the stimulus information (amplitude and frequency), and vice versa.
Wang, Qi; Gong, Yubing
2016-06-01
In this paper, we study the effect of autaptic activity on intrinsic coherence resonance (CR) induced by channel noise in Newman-Watts (NW) networks of stochastic Hodgkin-Huxley (HH) neurons. It is found that autaptic strength and autaptic delay have a big effect on the intrinsic CR. As autaptic strength increases, there is optimal autaptic strength by which the intrinsic CR is most highly enhanced. Autaptic delay can enhance, reduce, or destroy the intrinsic CR, depending on the delay length. Moreover, there are optimal coupling strength and network randomness by which autaptic activity can most highly enhance the intrinsic CR. These results show that autaptic activity has different effects on the intrinsic CR in the neuronal networks, and it can most highly enhance the intrinsic CR at optimal coupling strength and network randomness. These findings could find potential implications of channel noise and autaptic activity for the information processing and transmission in neural systems.
Wang, Qi; Gong, Yubing; Wu, Yanan
2014-08-01
In this paper, we study stochastic resonance (SR) induced by channel noise in adaptive weighted Newman-Watts networks of Hodgkin-Huxley neurons with channel blocking (CB). It is found that the intrinsic SR is dependent on adaptive coupling and is strongly enhanced when the changing rate of adaptive coupling is optimal, and this phenomenon is independent of sodium and potassium CB levels. As CB increases, the channel noise for SR decreases, but the strength of intrinsic SR nearly does not change in the presence of adaptive coupling, which is different from the case for fixed coupling. These results show that intrinsic SR can be enhanced and optimized by adaptive coupling, and CB's effect on the intrinsic SR can be reduced by adaptive coupling. This implies that adaptive coupling could more efficiently improve the time precision of information processing in neural systems.
Modelling spatiotemporal olfactory data in two steps: from binary to Hodgkin-Huxley neurones.
Quenet, Brigitte; Dubois, Rémi; Sirapian, Sevan; Dreyfus, Gérard; Horn, David
2002-01-01
Network models of synchronously updated McCulloch-Pitts neurones exhibit complex spatiotemporal patterns that are similar to activities of biological neurones in phase with a periodic local field potential, such as those observed experimentally by Wehr and Laurent (1996, Nature 384, 162-166) in the locust olfactory pathway. Modelling biological neural nets with networks of simple formal units makes the dynamics of the model analytically tractable. It is thus possible to determine the constraints that must be satisfied by its connection matrix in order to make its neurones exhibit a given sequence of activity (see, for instance, Quenet et al., 2001, Neurocomputing 38-40, 831-836). In the present paper, we address the following question: how can one construct a formal network of Hodgkin-Huxley (HH) type neurones that reproduces experimentally observed neuronal codes? A two-step strategy is suggested in the present paper: first, a simple network of binary units is designed, whose activity reproduces the binary experimental codes; second, this model is used as a guide to design a network of more realistic formal HH neurones. We show that such a strategy is indeed fruitful: it allowed us to design a model that reproduces the Wehr-Laurent olfactory codes, and to investigate the robustness of these codes to synaptic noise.
Biophysical synaptic dynamics in an analog VLSI network of Hodgkin-Huxley neurons.
Yu, Theodore; Cauwenberghs, Gert
2009-01-01
We study synaptic dynamics in a biophysical network of four coupled spiking neurons implemented in an analog VLSI silicon microchip. The four neurons implement a generalized Hodgkin-Huxley model with individually configurable rate-based kinetics of opening and closing of Na+ and K+ ion channels. The twelve synapses implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The implemented models on the chip are fully configurable by 384 parameters accounting for conductances, reversal potentials, and pre/post-synaptic voltage-dependence of the channel kinetics. We describe the models and present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. The 3mm x 3mm microchip consumes 1.29 mW power making it promising for applications including neuromorphic modeling and neural prostheses.
Delay-induced coherence bi-resonance-like behavior in stochastic Hodgkin-Huxley neuron networks
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
In this paper,we study how information transmission delays affect the spiking behavior of electrically coupled stochastic Hodgkin-Huxley (HH) neurons on Newman-Watts networks.It is found that the spiking behavior becomes the most regular at an optimal time delay,indicating the occurrence of delay-induced coherence resonance-like (CR-like) behavior.Interestingly,there are different CR-like types,depending on the membrane patch size of the neuron.For a smaller patch size,only single CR-like behavior occurs;while for a larger patch size,coherence bi-resonance-like (CBR) behavior appears.These findings show that the delay-induced CR-like behavior is closely related to the channel noise strength,and the coupled neurons may exhibit different spiking behaviors under the interplay of the channel noise and time delay.Therefore,the channel noise should be taken into account in the study of time delay-related spiking activity in stochastic HH neurons.This work provides new insight into the role of channel noise and information transmission delays in realistic neural systems.
Stochastic resonance on Newman-Watts networks of Hodgkin-Huxley neurons with local periodic driving
Energy Technology Data Exchange (ETDEWEB)
Ozer, Mahmut [Zonguldak Karaelmas University, Engineering Faculty, Department of Electrical and Electronics Engineering, 67100 Zonguldak (Turkey)], E-mail: mahmutozer2002@yahoo.com; Perc, Matjaz [University of Maribor, Faculty of Natural Sciences and Mathematics, Department of Physics, Koroska cesta 160, SI-2000 Maribor (Slovenia); Uzuntarla, Muhammet [Zonguldak Karaelmas University, Engineering Faculty, Department of Electrical and Electronics Engineering, 67100 Zonguldak (Turkey)
2009-03-02
We study the phenomenon of stochastic resonance on Newman-Watts small-world networks consisting of biophysically realistic Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise via voltage-gated ion channels embedded in neuronal membranes. Importantly thereby, the subthreshold periodic driving is introduced to a single neuron of the network, thus acting as a pacemaker trying to impose its rhythm on the whole ensemble. We show that there exists an optimal intensity of intrinsic ion channel noise by which the outreach of the pacemaker extends optimally across the whole network. This stochastic resonance phenomenon can be further amplified via fine-tuning of the small-world network structure, and depends significantly also on the coupling strength among neurons and the driving frequency of the pacemaker. In particular, we demonstrate that the noise-induced transmission of weak localized rhythmic activity peaks when the pacemaker frequency matches the intrinsic frequency of subthreshold oscillations. The implications of our findings for weak signal detection and information propagation across neural networks are discussed.
Energy and information in Hodgkin-Huxley neurons
Moujahid, A; Torrealdea, F J
2015-01-01
The generation of spikes by neurons is energetically a costly process and the evaluation of the metabolic energy required to maintain the signalling activity of neurons a challenge of practical interest. Neuron models are frequently used to represent the dynamics of real neurons but hardly ever to evaluate the electrochemical energy required to maintain that dynamics. This paper discusses the interpretation of a Hodgkin-Huxley circuit as an energy model for real biological neurons and uses it to evaluate the consumption of metabolic energy in the transmission of information between neurons coupled by electrical synapses, i.e. gap junctions. We show that for a single postsynaptic neuron maximum energy efficiency, measured in bits of mutual information per ATP molecule consumed, requires maximum energy consumption. On the contrary, for groups of parallel postsynaptic neurons we determine values of the synaptic conductance at which the energy efficiency of the transmission presents clear maxima at relatively ver...
Hodgkin-Huxley neurons with defective and blocked ion channels
Pang, James Christopher S.; Bantang, Johnrob Y.
2015-03-01
We utilize the original Hodgkin-Huxley (HH) model to consider the effects of defective ion channels to the temporal response of neurons. Statistics of firing rate and inter-spike interval (ISI) reveal that production of action potentials (APs) in neurons is not sensitive to changes in membrane conductance for sodium and potassium ions, as well as to the reversal potential for sodium ions, as long as the relevant parameters do not exceed 13% from their normal levels. We also found that blockage of a critical fraction of either sodium or potassium channels (dependent on constant input current) respectively limits the firing activity or increases spontaneous spiking activity of neurons. Our model may be used to guide experiment designs related to ion channel control drug development.
Spontaneous spiking in an autaptic Hodgkin-Huxley set up
Li, Yunyun; Hanggi, Peter; Schimansky-Geier, Lutz
2010-01-01
The effect of intrinsic channel noise is investigated for the dynamic response of a neuronal cell with a delayed feedback loop. The loop is based on the so-called autapse phenomenon in which dendrites establish not only connections to neighboring cells but as well to its own axon. The biophysical modeling is achieved in terms of a stochastic Hodgkin-Huxley model containing such a built in delayed feedback. The fluctuations stem from intrinsic channel noise, being caused by the stochastic nature of the gating dynamics of ion channels. The influence of the delayed stimulus is systematically analyzed with respect to the coupling parameter and the delay time in terms of the interspike interval histograms and the average interspike interval. The delayed feedback manifests itself in the occurrence of bursting and a rich multimodal interspike interval distribution, exhibiting a delay-induced reduction of the spontaneous spiking activity at characteristic frequencies. Moreover, a specific frequency-locking mechanism ...
New multi-soliton solutions for generalized Burgers-Huxley equation
Directory of Open Access Journals (Sweden)
Liu Jun
2013-01-01
Full Text Available The double exp-function method is used to obtain a two-soliton solution of the generalized Burgers-Huxley equation. The wave has two different velocities and two different frequencies.
Adolfo Araci
2014-01-01
Desde un punto de vista físico se puede entender la fibra muscular como un motor, es decir, un sistema capaz de transformar la energía química en energía mecánica, que se utiliza para realizar un trabajo. Por lo tanto, para entender cómo ocurre dicho proceso de transformación es necesario conocer la ultraestructura de la fibra muscular. Esta es, sin duda, la principal aportación al acervo científico del recientemente fallecido Hugh Emor Huxley (1924-2013). Huxley se graduó en Física en el Chr...
Adolfo Araci
2014-01-01
Desde un punto de vista físico se puede entender la fibra muscular como un motor, es decir, un sistema capaz de transformar la energía química en energía mecánica, que se utiliza para realizar un trabajo. Por lo tanto, para entender cómo ocurre dicho proceso de transformación es necesario conocer la ultraestructura de la fibra muscular. Esta es, sin duda, la principal aportación al acervo científico del recientemente fallecido Hugh Emor Huxley (1924-2013). Huxley se graduó en Física en el Chr...
Court, Deborah
1999-01-01
Revisits and reviews Imre Lakatos' ideas on "Falsification and the Methodology of Scientific Research Programmes." Suggests that Lakatos' framework offers an insightful way of looking at the relationship between theory and research that is relevant not only for evaluating research programs in theoretical physics, but in the social…
Spikes Synchronization in Neural Networks with Synaptic Plasticity
Borges, Rafael R; Batista, Antonio M; Caldas, Iberê L; Borges, Fernando S; Lameu, Ewandson L
2015-01-01
In this paper, we investigated the neural spikes synchronisation in a neural network with synaptic plasticity and external perturbation. In the simulations the neural dynamics is described by the Hodgkin Huxley model considering chemical synapses (excitatory) among neurons. According to neural spikes synchronisation is expected that a perturbation produce non synchronised regimes. However, in the literature there are works showing that the combination of synaptic plasticity and external perturbation may generate synchronised regime. This article describes the effect of the synaptic plasticity on the synchronisation, where we consider a perturbation with a uniform distribution. This study is relevant to researches of neural disorders control.
[Thomas H.Huxley--the naval doctor who became Darwin's bulldog].
Hauge, A
2000-12-10
Thomas H. Huxley (1825-1895) was an English physician and biologist who had a deep impact on the Victorian age. More than any other at his time he introduced scientifically based values. As a member of London's school board he brought science into the curriculum, encouraging school-children to ask questions and to make their own observations. Huxley came from a lower middle class family with little money. By sheer determination and hard work he managed to get a medical education at Charing Cross Hospital Medical School. He then obtained a posting on H.M.S. Rattlesnake, which gave him a chance to explore the southern seas and to study marine species. The results were published by the Royal Society of which Huxley became a member at the age of 26, and later its president. After several years of uncertainty he secured a position at the Royal School of Mines, which he transformed into the Imperial College of Science. He was a prolific scientist with wide interests, doing valuable work in paleontology, taxonomy and ethnology. Huxley wrote numerous essays on philosophy and scientific subjects. He coined the word agnostic to explain his attitude to Christian dogma. His style was clear and direct, and his essays still read very well. However, Huxley is now mostly, perhaps unfairly, remembered for his defence of Darwin's theory of evolution. In his book Evidence as to man's place in nature, Huxley, in contrast to Darwin, deals with the evolution of humans, mainly based on comparative anatomy. Huxley advocated a firmly held belief that scientific truths will have a liberating effect on the minds of men. His lectures on scientific subjects attracted large audiences of people who had not had the benefit of a higher education.
Stochastic differential equation models for ion channel noise in Hodgkin-Huxley neurons.
Goldwyn, Joshua H; Imennov, Nikita S; Famulare, Michael; Shea-Brown, Eric
2011-04-01
The random transitions of ion channels between conducting and nonconducting states generate a source of internal fluctuations in a neuron, known as channel noise. The standard method for modeling the states of ion channels nonlinearly couples continuous-time Markov chains to a differential equation for voltage. Beginning with the work of R. F. Fox and Y.-N. Lu [Phys. Rev. E 49, 3421 (1994)], there have been attempts to generate simpler models that use stochastic differential equation (SDEs) to approximate the stochastic spiking activity produced by Markov chain models. Recent numerical investigations, however, have raised doubts that SDE models can capture the stochastic dynamics of Markov chain models.We analyze three SDE models that have been proposed as approximations to the Markov chain model: one that describes the states of the ion channels and two that describe the states of the ion channel subunits. We show that the former channel-based approach can capture the distribution of channel noise and its effects on spiking in a Hodgkin-Huxley neuron model to a degree not previously demonstrated, but the latter two subunit-based approaches cannot. Our analysis provides intuitive and mathematical explanations for why this is the case. The temporal correlation in the channel noise is determined by the combinatorics of bundling subunits into channels, but the subunit-based approaches do not correctly account for this structure. Our study confirms and elucidates the findings of previous numerical investigations of subunit-based SDE models. Moreover, it presents evidence that Markov chain models of the nonlinear, stochastic dynamics of neural membranes can be accurately approximated by SDEs. This finding opens a door to future modeling work using SDE techniques to further illuminate the effects of ion channel fluctuations on electrically active cells.
Spontaneous spiking in an autaptic Hodgkin-Huxley setup
Li, Yunyun; Schmid, Gerhard; Hänggi, Peter; Schimansky-Geier, Lutz
2010-12-01
The effect of intrinsic channel noise is investigated for the dynamic response of a neuronal cell with a delayed feedback loop. The loop is based on the so-called autapse phenomenon in which dendrites establish connections not only to neighboring cells but also to its own axon. The biophysical modeling is achieved in terms of a stochastic Hodgkin-Huxley model containing such a built in delayed feedback. The fluctuations stem from intrinsic channel noise, being caused by the stochastic nature of the gating dynamics of ion channels. The influence of the delayed stimulus is systematically analyzed with respect to the coupling parameter and the delay time in terms of the interspike interval histograms and the average interspike interval. The delayed feedback manifests itself in the occurrence of bursting and a rich multimodal interspike interval distribution, exhibiting a delay-induced reduction in the spontaneous spiking activity at characteristic frequencies. Moreover, a specific frequency-locking mechanism is detected for the mean interspike interval.
The ISI distribution of the stochastic Hodgkin-Huxley neuron.
Rowat, Peter F; Greenwood, Priscilla E
2014-01-01
The simulation of ion-channel noise has an important role in computational neuroscience. In recent years several approximate methods of carrying out this simulation have been published, based on stochastic differential equations, and all giving slightly different results. The obvious, and essential, question is: which method is the most accurate and which is most computationally efficient? Here we make a contribution to the answer. We compare interspike interval histograms from simulated data using four different approximate stochastic differential equation (SDE) models of the stochastic Hodgkin-Huxley neuron, as well as the exact Markov chain model simulated by the Gillespie algorithm. One of the recent SDE models is the same as the Kurtz approximation first published in 1978. All the models considered give similar ISI histograms over a wide range of deterministic and stochastic input. Three features of these histograms are an initial peak, followed by one or more bumps, and then an exponential tail. We explore how these features depend on deterministic input and on level of channel noise, and explain the results using the stochastic dynamics of the model. We conclude with a rough ranking of the four SDE models with respect to the similarity of their ISI histograms to the histogram of the exact Markov chain model.
Yu, Lianchun; Liu, Liwei
2014-03-01
The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.
2005-05-01
environment (i.e., culture , class, family, educational 2 Chapter 23 Intelligence Revisited opportunities, gender) shapes our intellect, and there are no...connectivity is going to be rather problematic, to say the least. A single nano-bot cruising this Disneyland of synaptic wonderment is certainly... cultures ). Embodiment – A sense of being anchored to our physical bodies. Agency – A sense of free will, wherein we are in charge of our own
Thomas Huxley and the rat placenta in the early debates on evolution.
Pijnenborg, R; Vercruysse, L
2004-01-01
The 19th century debates on mammalian classification in the light of the new evolutionary thinking led to controversies between Thomas Huxley and Richard Owen concerning the value of the placenta as a representative key organ. As a main point in his argument, Huxley provided a detailed description of a sectioned rat placenta, highlighting the importance of decidualization of the uterus as an argument supporting an evolutionary relationship between rodents, insectivores and primates, an idea hotly contested by Owen. In addition, he illustrated and correctly interpreted the maternal blood supply from uterus to placenta in striking detail. During the succeeding decades the key role of trophoblast in placenta formation was discovered, and the decidua became neglected in later comparative studies. Nevertheless, at the present time trophoblast-decidual interaction is regarded as an extremely important feature of placental development in both primates and rodents, and Huxley can therefore rightfully be considered as an early pioneer in placental research.
Challenging normative orthodoxies in depression: Huxley's Utopia or Dante's Inferno?
Cutcliffe, John R; Lakeman, Richard
2010-04-01
Although there appears to be a widespread consensus that depression is a ubiquitous human experience, definitions of depression, its prevalence, and how mental health services respond to it have changed significantly over time, particularly during recent decades. Epistemological limitations notwithstanding, it is now estimated that approximately 121 million people experience depression. At the same time, it should be acknowledged that the last two decades have seen the widespread acceptance of depression as a chemical imbalance and a massive corresponding increase in the prescription of antidepressants, most notably of selective serotonin reuptake inhibitors (SSRIs). However, questions have been raised about the effectiveness and iatrogenic side effects of antidepressants; related questions have also been asked about whose interests are served by the marketing and sales of these drugs. Accordingly, this article attempts to problematize the normative orthodoxy concerning depression and creates a "space" in which an alternative can be articulated and enacted. In so doing, the article finds that the search for a world where the automatic response to depression is a pharmacological intervention not only ignores the use of alternative efficacious treatment options but may also inhibit the persons' chance to explore the meaning of their experience and thus prevent people from individual growth and personal development. Interestingly, in worlds analogous to this pharmacologically induced depression-free state, such as utopias like that in Huxley's Brave New World, no "properly conditioned citizen" is depressed or suicidal. Yet, in the same Brave New World, no one is free to suffer, to be different, or crucially, to be independent. Copyright 2010 Elsevier Inc. All rights reserved.
Principal Dynamic Mode Analysis of the Hodgkin–Huxley Equations
Eikenberry, Steffen E.; Marmarelis, Vasilis Z.
2015-01-01
We develop an autoregressive model framework based on the concept of Principal Dynamic Modes (PDMs) for the process of action potential (AP) generation in the excitable neuronal membrane described by the Hodgkin–Huxley (H–H) equations. The model's exogenous input is injected current, and whenever the membrane potential output exceeds a specified threshold, it is fed back as a second input. The PDMs are estimated from the previously developed Nonlinear Autoregressive Volterra (NARV) model, and represent an efficient functional basis for Volterra kernel expansion. The PDM-based model admits a modular representation, consisting of the forward and feedback PDM bases as linear filterbanks for the exogenous and autoregressive inputs, respectively, whose outputs are then fed to a static nonlinearity composed of polynomials operating on the PDM outputs and cross-terms of pair-products of PDM outputs. A two-step procedure for model reduction is performed: first, influential subsets of the forward and feedback PDM bases are identified and selected as the reduced PDM bases. Second, the terms of the static nonlinearity are pruned. The first step reduces model complexity from a total of 65 coefficients to 27, while the second further reduces the model coefficients to only eight. It is demonstrated that the performance cost of model reduction in terms of out-of-sample prediction accuracy is minimal. Unlike the full model, the eight coefficient pruned model can be easily visualized to reveal the essential system components, and thus the data-derived PDM model can yield insight into the underlying system structure and function. PMID:25630480
Principal dynamic mode analysis of the Hodgkin-Huxley equations.
Eikenberry, Steffen E; Marmarelis, Vasilis Z
2015-03-01
We develop an autoregressive model framework based on the concept of Principal Dynamic Modes (PDMs) for the process of action potential (AP) generation in the excitable neuronal membrane described by the Hodgkin-Huxley (H-H) equations. The model's exogenous input is injected current, and whenever the membrane potential output exceeds a specified threshold, it is fed back as a second input. The PDMs are estimated from the previously developed Nonlinear Autoregressive Volterra (NARV) model, and represent an efficient functional basis for Volterra kernel expansion. The PDM-based model admits a modular representation, consisting of the forward and feedback PDM bases as linear filterbanks for the exogenous and autoregressive inputs, respectively, whose outputs are then fed to a static nonlinearity composed of polynomials operating on the PDM outputs and cross-terms of pair-products of PDM outputs. A two-step procedure for model reduction is performed: first, influential subsets of the forward and feedback PDM bases are identified and selected as the reduced PDM bases. Second, the terms of the static nonlinearity are pruned. The first step reduces model complexity from a total of 65 coefficients to 27, while the second further reduces the model coefficients to only eight. It is demonstrated that the performance cost of model reduction in terms of out-of-sample prediction accuracy is minimal. Unlike the full model, the eight coefficient pruned model can be easily visualized to reveal the essential system components, and thus the data-derived PDM model can yield insight into the underlying system structure and function.
2010-01-01
Pennebaker hat doch zurückgeblickt. In weiteren fünfundsechzig Minuten zeigt er mit 65 REVISITED neue und ergänzende Facetten von Bob Dylan auf seiner 1965er Tournee durch England aus bisher unveröffentlichtem und digital aufgearbeitetem Material. Couchman (2002, 94) betont, dass Dylan über vierzig Jahre nach DON‘T LOOK BACK (1965) noch immer nichts von seiner enigmatischen Ausstrahlung verloren habe. Das gleiche gilt auch für den Film und für seine Ergänzung.
Dynamic causal modelling revisited.
Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter
2017-02-17
This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Institute of Scientific and Technical Information of China (English)
王宝英; 龚玉兵
2015-01-01
We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin–Huxley neuron network with time delays. It is found that the time delay can induce synchronization transitions at an intermediate and proper channel noise intensity, and the synchronization transitions become strongest when the channel noise intensity is optimal. The neurons can also exhibit synchronization transitions as the channel noise intensity is varied, and this phenomenon is enhanced at around the time delays that can induce the synchronization transitions. It is also found that the synchronization transitions induced by the channel noise are dependent on the coupling strength and the network average degree, and there is an optimal coupling strength or network average degree with which the synchronization transitions become strongest. These results show that by inducing synchronization transitions, the channel noise has a big regulation effect on the synchronization of the neuronal network. These findings could find potential implications for the information transmission in neural systems.
Wang, Bao-Ying; Gong, Yu-Bing
2015-11-01
We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transitions at an intermediate and proper channel noise intensity, and the synchronization transitions become strongest when the channel noise intensity is optimal. The neurons can also exhibit synchronization transitions as the channel noise intensity is varied, and this phenomenon is enhanced at around the time delays that can induce the synchronization transitions. It is also found that the synchronization transitions induced by the channel noise are dependent on the coupling strength and the network average degree, and there is an optimal coupling strength or network average degree with which the synchronization transitions become strongest. These results show that by inducing synchronization transitions, the channel noise has a big regulation effect on the synchronization of the neuronal network. These findings could find potential implications for the information transmission in neural systems. Project supported by the Natural Science Foundation of Shandong Province of China (Grant No. ZR2012AM013).
The "History" of Victorian Scientific Naturalism: Huxley, Spencer and the "End" of natural history.
Lightman, Bernard
2016-08-01
As part of their defence of evolutionary theory, T. H. Huxley and Herbert Spencer argued that natural history was no longer a legitimate scientific discipline. They outlined a secularized concept of life from biology to argue for the validity of naturalism. Despite their support for naturalism, they offered two different responses to the decline of natural history. Whereas Huxley emphasized the creation of a biological discipline, and all that that entailed, Spencer was more concerned with constructing an entire intellectual system based on the idea of evolution. In effect, Spencer wanted to create a new scientific worldview based on evolutionary theory. This had consequences for their understanding of human history, especially of how science had evolved through the ages. It affected their conceptions of human agency, contingency, and directionality in history. Examining Huxley's and Spencer's responses to the "end" of natural history reveals some of the deep divisions within scientific naturalism and the inherent problems of naturalism in general. Whereas Huxley chose to separate the natural and the historical, Spencer opted to fuse them into a single system.
Tunicates: exploring the sea shores and roaming the open ocean. A tribute to Thomas Huxley.
Lemaire, Patrick; Piette, Jacques
2015-06-01
This review is a tribute to the remarkable contributions of Thomas Huxley to the biology of tunicates, the likely sister group of vertebrates. In 1851, the great biologist and philosopher published two landmark papers on pelagic tunicates in the Philosophical Transactions of the Royal Society. They were dedicated to the description of the adult anatomy and life cycle of thaliaceans and appendicularians, the pelagic relatives of ascidians. In the first part of this review, we discuss the novel anatomical observations and evolutionary hypotheses made by Huxley, which would have a lasting influence on tunicate biology. We also briefly comment on the more philosophical reflections of Huxley on individuality. In the second part, we stress the originality and relevance of past and future studies of tunicates in the resolution of major biological issues. In particular, we focus on the complex relationship between genotype and phenotype and the phenomenon of developmental system drift. We propose that more than 150 years after Huxley's papers, tunicate embryos are still worth studying in their own right, independently of their evolutionary proximity to vertebrates, as they provide original and crucial insights into the process of animal evolution. Tunicates are still at the forefront of biological research.
A Collocation Method for Numerical Solution of the Generalized Burgers-Huxley Equation
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Mohammad ZAREBNIA
2014-08-01
Full Text Available In this paper, we use a collocation method to solve the Burgers-Huxley equation. To achieve this aim, we use mesh free technique based on sinc functions. The stability analysis is discussed. Some numerical examples are provided to illustrate the accuracy and fluency of the method.
DEFF Research Database (Denmark)
Pankratova, Evgeniya; Polovinkin, A.V.; Mosekilde, Erik
2005-01-01
The paper considers an excitable Hodgkin-Huxley system subjected to a strong periodic forcing in the presence of random noise. The influence of the forcing frequency on the response of the system is examined in the realm of suprathreshold amplitudes. Our results confirm that the presence of noise...
Wilberforce, Huxley and the Use of History in Teaching about Evolution.
Gauld, Colin
1992-01-01
Author asserts that many historical anecdotes used in science instruction have little basis in reality. The purpose of this paper is to provide a critique of the way in which the "Wilberforce and Huxley debate at Oxford" anecdote is employed in the teaching of evolution and to suggest a more positive role for this incident in science…
The what and where of adding channel noise to the Hodgkin-Huxley equations.
Goldwyn, Joshua H; Shea-Brown, Eric
2011-11-01
Conductance-based equations for electrically active cells form one of the most widely studied mathematical frameworks in computational biology. This framework, as expressed through a set of differential equations by Hodgkin and Huxley, synthesizes the impact of ionic currents on a cell's voltage--and the highly nonlinear impact of that voltage back on the currents themselves--into the rapid push and pull of the action potential. Later studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations or their counterparts. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the equations of Hodgkin-Huxley type. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic equations of Hodgkin-Huxley type as well as to more modern models of ion channel dynamics. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly MATLAB simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.
Is neural Darwinism Darwinism?
van Belle, T
1997-01-01
Neural Darwinism is a theory of cognition developed by Gerald Edelman along with George Reeke and Olaf Sporns at Rockefeller University. As its name suggests, neural Darwinism is modeled after biological Darwinism, and its authors assert that the two processes are strongly analogous. both operate on variation in a population, amplifying the more adaptive individuals. However, from a computational perspective, neural Darwinism is quite different from other models of natural selection, such as genetic algorithms. The individuals of neural Darwinism do not replicate, thus robbing the process of the capacity to explore new solutions over time and ultimately reducing it to a random search. Because neural Darwinism does not have the computational power of a truly Darwinian process, it is misleading to label it as such. to illustrate this disparity in adaptive power, one of Edelman's early computer experiments, Darwin I, is revisited, and it is shown that adding replication greatly improves the adaptive power of the system.
Comparison of Spectral and Differential Quadrature Methods for Solving the Burger-Huxley Equation
Directory of Open Access Journals (Sweden)
Jalal Izadian
2013-06-01
Full Text Available In this paper, the Burger-Huxley equation is solved by two methods: Spectral method and Differential Quadrature Method (DQM. The Chebyshev-Gauss-Lobatto point distribution is utilized in spectral method. The integrity and computational accuracy of the spectral method in solving some test problems are demonstrated through various case studies. The results show that spectral method is more accurate than DQM.
Development of Galerkin Method for Solving the Generalized Burger's-Huxley Equation
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M. El-Kady
2013-01-01
Full Text Available Numerical treatments for the generalized Burger's—Huxley GBH equation are presented. The treatments are based on cardinal Chebyshev and Legendre basis functions with Galerkin method. Gauss quadrature formula and El-gendi method are used to convert the problem into a system of ordinary differential equations. The numerical results are compared with the literatures to show efficiency of the proposed methods.
Thomas Henry Huxley (1825-1895) puts us in our place.
Weiss, Kenneth M
2004-05-15
Thomas Huxley was one of the 19th century's most active defenders of Darwin's idea that life has evolved through natural processes. An anatomist and paleontologist, he extended his energies to science and education policy, the democratization of science, and the broad societal implications of evolution. Since his time the fossil record has greatly improved and the genetic 'revolution' has occurred, deepening our understanding of primate and human evolution in ways that would please Huxley: improved systematics relies heavily on genetic data, and molecular technologies are opening our understanding of the genetic basis of complex traits of traditional anthropological interest-but in ways that are thoroughly dependent on the fact of evolution. A more unified biological synthesis is forming that unites genes, developmental process, structure, and inheritance. But the tempo and mode of evolution remain unresolved. Huxley was one of many who have had trouble accepting Darwin's gradual natural selection as the central evolutionary mechanism, and views spanning the antipodes of gradualism and saltation find advocates even in our genetic era.
SAn Analysis f the theme of “Fard”by Aldous Leonard Huxley
Institute of Scientific and Technical Information of China (English)
野长虹
2014-01-01
奥德斯�李納�赫胥黎是英格兰作家，著名的赫胥黎家族最杰出的成员之一。赫胥黎是一个人文主义者，和平主义者及讽刺作家。他的文章“胭脂”入选了现代大学英语阅读(4)。此文展示了资产阶级对工人阶级的极度剥削，揭露了资产阶级的丑恶灵魂。本论文旨在分析文章题目揭示的深层次主题。%Leonard Huxley was an English writer and a prominent member of the Huxley family.Huxley was a humanist,pacifist and satirist.His article “Fard”has been elected into the Contemporary College English Reading Book IV.It shows the facts of bourG geoisie’s fierce exploitation to the working class and their ugly souls.This thesis aims at analyzing the deeper theme of the article shown by the title.
Extending the conditions of application of an inversion of the Hodgkin-Huxley gating model.
Raba, Ashley E; Cordeiro, Jonathan M; Antzelevitch, Charles; Beaumont, Jacques
2013-05-01
We present an inversion of the Hodgkin-Huxley formalism to estimate initial conditions and model parameters, including functions of voltage, from the solutions of the underlying ordinary differential equation (ODE) subjected to multiple voltage step stimulations. As such, the procedure constitutes a means to estimate the parameters including functions of voltage of an Hodgkin-Huxley formalism from experimental data.The basic idea was developed in a previous communication (SIAM J. Appl. Math. 64:1264-1274, 2009). The inversion in question applies to currents exhibiting activation and inactivation, but the version, as published previously, cannot estimate the unknowns for channels that rapidly inactivate just after a brief opening. In such cases, the amplitude of the current, in a given voltage range, is too small to be detectable by the instrumentation using previously applied experimental protocols. This is, for example, the case for the sodium channels in a number of excitable tissue for potential in the vicinity of the cell resting potential. The current communication extends the inversion procedure in a manner to overcome this limitation.Furthermore, within the inversion framework, we can determine whether the data at the basis of the estimation sufficiently constrains the estimation problem, i.e., whether it is complete. We exploit this element of our method to document a set of stimulation protocols that constitute a complete data set for the purpose of inverting the Hodgkin-Huxley formalism.
Energy Technology Data Exchange (ETDEWEB)
Helama, S.; Holopainen, J.; Eronen, M. [Department of Geology, University of Helsinki, (Finland); Makarenko, N.G. [Russian Academy of Sciences, St. Petersburg (Russian Federation). Pulkovo Astronomical Observatory; Karimova, L.M.; Kruglun, O.A. [Institute of Mathematics, Almaty (Kazakhstan); Timonen, M. [Finnish Forest Research Institute, Rovaniemi Research Unit (Finland); Merilaeinen, J. [SAIMA Unit of the Savonlinna Department of Teacher Education, University of Joensuu (Finland)
2009-07-01
Tree-rings tell of past climates. To do so, tree-ring chronologies comprising numerous climate-sensitive living-tree and subfossil time-series need to be 'transferred' into palaeoclimate estimates using transfer functions. The purpose of this study is to compare different types of transfer functions, especially linear and nonlinear algorithms. Accordingly, multiple linear regression (MLR), linear scaling (LSC) and artificial neural networks (ANN, nonlinear algorithm) were compared. Transfer functions were built using a regional tree-ring chronology and instrumental temperature observations from Lapland (northern Finland and Sweden). In addition, conventional MLR was compared with a hybrid model whereby climate was reconstructed separately for short- and long-period timescales prior to combining the bands of timescales into a single hybrid model. The fidelity of the different reconstructions was validated against instrumental climate data. The reconstructions by MLR and ANN showed reliable reconstruction capabilities over the instrumental period (AD 1802-1998). LCS failed to reach reasonable verification statistics and did not qualify as a reliable reconstruction: this was due mainly to exaggeration of the low-frequency climatic variance. Over this instrumental period, the reconstructed low-frequency amplitudes of climate variability were rather similar by MLR and ANN. Notably greater differences between the models were found over the actual reconstruction period (AD 802-1801). A marked temperature decline, as reconstructed by MLR, from the Medieval Warm Period (AD 931-1180) to the Little Ice Age (AD 1601-1850), was evident in all the models. This decline was approx. 0.5 C as reconstructed by MLR. Different ANN based palaeotemperatures showed simultaneous cooling of 0.2 to 0.5 C, depending on algorithm. The hybrid MLR did not seem to provide further benefit above conventional MLR in our sample. The robustness of the conventional MLR over the calibration
一类广义 Burgers-Huxley 方程的解与其分支%Solutions and Its Bifurcation for a Generalized Burgers-Huxley Equation
Institute of Scientific and Technical Information of China (English)
王勤龙; 邓习军
2010-01-01
运用平面动力系统分支理论和可积性判定方法,研究了一类广义 Burgers-Huxley 方程,首先通过新的算法计算奇点量,解决了其可积性问题,然后进行平衡点类型分析,并讨论了在不同的参数条件下的相图与分支类型,利用 Maple 软件绘出分支相图,最后讨论了各种行波解的存在性及方程的精确解.
Currie-Knight, Kevin
2011-01-01
Jean-Jacques Rousseau (1712-1778) and Thomas Huxley (1852-1895) had different, but substantial, effects on the history of education. Rousseau's educational theories supplied the intellectual foundation for pedagogical progressivism. Huxley's educational writings helped to enlarge the scope of the British curriculum to include such things as…
The neuron physiology and Hodgkin-Huxley and FitzHugh-Nagumo models
2007-01-01
Resumo: Apresentaremos neste trabalho descrições detalhadas da modelagem e conceitos fisiológicos associados aos modelos de Hodgkin-Huxley e Fitzhugh-Nagumo, para em seguida compararmos suas características. Tentaremos justificar a opção pelo modelo de Fitzhugh-Nagumo como objeto de estudo viável pra interações entre neurônios, e em seguida introduziremos um tipo de interação na qual o comportamento do sistema para dois neurônios apresenta fenômenos de comportamento irregular. Para isso, most...
Thermal impact on spiking properties in Hodgkin-Huxley neuron with synaptic stimulus
Indian Academy of Sciences (India)
Shenbing Kuang; Jiafu Wang; Ting Zeng; Aiyin Cao
2008-01-01
The effect of environmental temperature on neuronal spiking behaviors is investigated by numerically simulating the temperature dependence of spiking threshold of the Hodgkin-Huxley neuron subject to synaptic stimulus. We find that the spiking threshold exhibits a global minimum in a specific temperature range where spike initiation needs weakest synaptic strength, which form the engineering perspective indicates the occurrence of optimal use of synaptic transmission in the nervous system. We further explore the biophysical origin of this phenomenon associated with ion channel gating kinetics and also discuss its possible biological relevance in information processing in neuronal systems.
Non-Gaussian Colored Noise Optimized Spatial Coherence of a Hodgkin—Huxley Neuronal Network
Sun, Xiao-Juan; Lu, Qi-Shao
2014-02-01
We numerically study how non-Gaussian colored noise affects the spatial coherence of a Hodgkin—Huxley neuronal network. From the simulation results, we find that there exists some intermediate noise intensities, correlation time of the colored noise, and the deviation from Gaussian colored noise, for which an ordered pattern with a characteristic spatial frequency of the system comes forth in a resonant manner. Namely, under certain conditions, spatial coherence of the studied neuronal network can be optimized by the non-Gaussian colored noise, which indicates the occurrence of spatial coherence resonance.
Unidirectional synchronization of Hodgkin-Huxley neurons exposed to ELF electric field
Energy Technology Data Exchange (ETDEWEB)
Wang Jiang [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)], E-mail: jiangwang@tju.edu.cn; Che Yanqiu; Zhou Sisi; Deng Bin [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
2009-02-15
In this paper, a hybrid control strategy, H{sub {infinity}} variable universe adaptive fuzzy control, is derived and applied to synchronize two Hodgkin-Huxley (HH) neurons exposed to external electric field. Firstly, the modified model of HH neuron exposed to extremely low frequency (ELF) external electric field is established and its periodic and chaotic dynamics in response to sinusoidal electric field stimulation are described. And then the statement of the problem for unidirectional synchronization of two HH neurons is given. Finally H{sub {infinity}} variable universe adaptive fuzzy control is designed to synchronize the HH systems and the simulation results demonstrate the effectiveness of the proposed control method.
Responses of Hodgkin-Huxley Neuronal Systems to Spike-Train Inputs
Institute of Scientific and Technical Information of China (English)
CHANG Wen-Li; WANG Sheng-Jun; WANG Ying-Hai
2007-01-01
We investigate responses of the Hodgkin-Huxley globally neuronal systems to periodic spike-train inputs. The firing activities of the neuronal networks show different rhythmic patterns for different parameters. These rhythmic patterns can be used to explain cycles of firing in real brain. These activity patterns, average activity and coherence measure are affected by two quantities such as the percentage of excitatory couplings and stimulus intensity, in which the percentage of excitatory couplings is more important than stimulus intensity since the transition phenomenon of average activity comes about.
Synchronization of a coupled Hodgkin-Huxley neurons via high order sliding-mode feedback
Energy Technology Data Exchange (ETDEWEB)
Aguilar-Lopez, R. [Division de Ciencias Basicas e Ingenieria, Universidad Autonoma Metropolitana, Av. San Pablo No. 180, Reynosa-Tamaulipas, 02200 Azcapotzalco, Mexico, D.F. (Mexico)], E-mail: raguilar@correo.azc.uam.mx; Martinez-Guerra, R. [Departamento de Control Automatico, CINVESTAV-IPN, Apartado Postal 14-740, Mexico, D.F. C.P. 07360 (Mexico)], E-mail: rguerra@ctrl.cinvestav.mx
2008-07-15
This work deals with the synchronizations of two both coupled Hodgkin-Huxley (H-H) neurons, where the master neuron posses inner noise and the slave neuron is considered in a resting state, (without inner noise) and an exciting state (with inner noise). The synchronization procedure is done via a feedback control, considering a class of high order sliding-mode controller which provides chattering reduction and finite time synchronization convergence, with a satisfactory performance. Theoretical analysis is done in order to show the closed-loop stability of the proposed controller and the calculated finite time for convergence. The main results are illustrated via numerical experiments.
Soliton-like solutions to the generalized Burgers-Huxley equation with variable coefficients
Triki, Houria; Wazwaz, Abdul-Majid
2013-12-01
In this paper, we consider the generalized Burgers-Huxley equation with arbitrary power of nonlinearity and timedependent coefficients. We analyze the traveling wave problem and explicitly find new soliton-like solutions for this extended equation by using the ansatz of Zhao et al. [X. Zhao, D. Tang, L. Wang, Phys. Lett. A 346 (2005) 288-291]. We also employ the solitary wave ansatz method to derive the exact bright and dark soliton solutions for the considered evolution equation. The physical parameters in the soliton solutions are obtained as function of the time-dependent model coefficients. The conditions of existence of solitons are presented. As a result, rich exact travelling wave solutions, which contain new soliton-like solutions, bell-shaped solitons and kink-shaped solitons for the generalized Burgers-Huxley equation with time-dependent coefficients, are obtained. The methods employed here can also be used to solve a large class of nonlinear evolution equations with variable coefficients.
Spiking sychronization regulated by noise in three types of Hodgkin-Huxley neuronal networks
Institute of Scientific and Technical Information of China (English)
Zhang Zheng-Zhen; Zeng Shang-You; Tang Wen-Yan; Hu Jin-Lin; Zeng Shao-Wen; Ning Wei-Lian; Qiu Yi; Wu Hui-Si
2012-01-01
In this paper,we study spiking synchronization in three different types of Hodgkin-Huxley neuronal networks,which are the small-world,regular,and random neuronal networks. All the neurons are subjected to subthreshold stimulus and external noise. It is found that in each of all the neuronal networks there is an optimal strength of noise to induce the maximal spiking synchronization.We further demonstrate that in each of the neuronal networks there is a range of synaptic conductance to induce the effect that an optimal strength of noise maximizes the spiking synchronization.Only when the magnitude of the synaptic conductance is moderate,will the effect be considerable.However,if the synaptic conductance is small or large,the effect vanishes.As the connections between neurons increase,the synaptic conductance to maximize the effect decreases.Therefore,we show quantitatively that the noise-induced maximal synchronization in the Hodgkin-Huxley neuronal network is a general effect,regardless of the specific type of neuronal network.
Directory of Open Access Journals (Sweden)
Adolfo Araci
2014-04-01
Full Text Available Desde un punto de vista físico se puede entender la fibra muscular como un motor, es decir, un sistema capaz de transformar la energía química en energía mecánica, que se utiliza para realizar un trabajo. Por lo tanto, para entender cómo ocurre dicho proceso de transformación es necesario conocer la ultraestructura de la fibra muscular. Esta es, sin duda, la principal aportación al acervo científico del recientemente fallecido Hugh Emor Huxley (1924-2013. Huxley se graduó en Física en el Christ’s College de Cambdrige, tras ver interrumpidos temporalmente sus estudios por su dedicación como operario de radar de la Royal Air Force entre 1943 y 1947, durante la Segunda Guerra Mundial (Pollard y Goldman, 2013; Spudich, 2013. Tras su graduación se incorporó como el primer estudiante de doctorado a una unidad de nueva creación del Medical Research Council, el “Laboratorio de Biología Molecular”, dirigida por Max Perutz y John Kendrew, siendo este último el director de sus tesis doctoral, que fue defendida en 1952 (Spudich, 2013. El uso de la técnicas de difracción de rayos X, que permitían el estudio en niveles de resolución inalcanzables con las técnicas microscópicas del momento, y su aplicación a la descripción de la ultraestructura muscular, fueron el objeto de su tesis doctoral, para el desarrollo de la cual diseñó y construyó sus propios instrumentos. El esclarecimiento de los aspectos estructurales implicados en la contracción muscular se convirtió desde entonces en la pregunta central de su biografía científica.
Xie, Huijuan; Gong, Yubing; Wang, Qi
2016-07-01
In this paper, we numerically study the effect of spike-timing-dependent plasticity (STDP) on coherence resonance (CR) induced by channel noise in adaptive Newman-Watts stochastic Hodgkin-Huxley neuron networks. It is found that STDP can either enhance or suppress the intrinsic CR when the adjusting rate of STDP decreases or increases. STDP can alter the effects of network randomness and network size on the intrinsic CR. Under STDP, for electrical coupling there are optimal network randomness and network size by which the intrinsic CR becomes strongest, however, for chemical coupling the intrinsic CR is always enhanced as network randomness or network size increases, which are different from the results for fixed coupling. These results show that the intrinsic CR of the neuronal networks can be either enhanced or suppressed by STDP, and there are optimal network randomness and network size by which the intrinsic CR becomes strongest. These findings could provide a new insight into the role of STDP for the information processing and transmission in neural systems.
Homoclinic bifurcation in a Hodgkin-Huxley model of thermally sensitive neurons
Energy Technology Data Exchange (ETDEWEB)
Feudel, Ulrike [Department of Physics, University of Potsdam, Potsdam 14415, (Germany); Neiman, Alexander [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States); Pei, Xing [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States); Wojtenek, Winfried [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States); Braun, Hans [Institute of Physiology, University of Marburg, Marburg 35037, (Germany); Huber, Martin [Institute of Physiology, University of Marburg, Marburg 35037, (Germany); Moss, Frank [Center for Neurodynamics, University of Missouri at St. Louis, St. Louis, Missouri 63121 (United States)
2000-03-01
We study global bifurcations of the chaotic attractor in a modified Hodgkin-Huxley model of thermally sensitive neurons. The control parameter for this model is the temperature. The chaotic behavior is realized over a wide range of temperatures and is visualized using interspike intervals. We observe an abrupt increase of the interspike intervals in a certain temperature region. We identify this as a homoclinic bifurcation of a saddle-focus fixed point which is embedded in the chaotic attractors. The transition is accompanied by intermittency, which obeys a universal scaling law for the average length of trajectory segments exhibiting only short interspike intervals with the distance from the onset of intermittency. We also present experimental results of interspike interval measurements taken from the crayfish caudal photoreceptor, which qualitatively demonstrate the same bifurcation structure. (c) 2000 American Institute of Physics.
Strange Nonchaotic Oscillations in The Quasiperiodically Forced Hodgkin-Huxley Neuron
Lim, Woochang; 10.1088/1751-8113/42/26/265103
2011-01-01
We numerically study dynamical behaviors of the quasiperiodically forced Hodgkin-Huxley neuron and compare the dynamical responses with those for the case of periodic stimulus. In the periodically forced case, a transition from a periodic to a chaotic oscillation was found to occur via period doublings in previous numerical and experimental works. We investigate the effect of the quasiperiodic forcing on this period-doubling route to chaotic oscillation. In contrast to the case of periodic forcing, new type of strange nonchaotic (SN) oscillating states (that are geometrically strange but have no positive Lyapunov exponents) are found to exist between the regular and chaotic oscillating states as intermediate ones. Their strange fractal geometry leads to aperiodic "complex" spikings. Various dynamical routes to SN oscillations are identified, as in the quasiperiodically forced logistic map. These SN spikings are expected to be observed in experiments of the quasiperiodically forced squid giant axon.
Identifying generalized Fitzhugh-Nagumo equation from a numerical solution of Hodgkin-Huxley model
Directory of Open Access Journals (Sweden)
Nikola V. Georgiev
2003-01-01
Full Text Available An analytic time series in the form of numerical solution (in an appropriate finite time interval of the Hodgkin-Huxley current clamped (HHCC system of four differential equations, well known in the neurophysiology as an exact empirical model of excitation of a giant axon of Loligo, is presented. Then we search for a second-order differential equation of generalized Fitzhugh-Nagumo (GFN type, having as a solution the given single component (action potential of the numerical solution. The given time series is used as a basis for reconstructing orders, powers, and coefficients of the polynomial right-hand sides of GFN equation approximately governing the process of action potential. For this purpose, a new geometrical method for determining phase space dimension of the unknown dynamical system (GFN equation and a specific modification of least squares method for identifying unknown coefficients are developed and applied.
In-phase and anti-phase synchronization in noisy Hodgkin-Huxley neurons
Schmid, Gerhard; Hanggi, Peter
2013-01-01
We numerically investigate the influence of intrinsic channel noise on the dynamical response of delay-coupling in neuronal systems. The stochastic dynamics of the spiking is modeled within a stochastic modification of the standard Hodgkin-Huxley model wherein the delay-coupling accounts for the finite propagation time of an action potential along the neuronal axon. We quantify this delay-coupling of the Pyragas-type in terms of the difference between corresponding presynaptic and postsynaptic membrane potentials. In case of a single neuron we analyze the spiking activity in presence of an autaptic feedback loop. With vanishing channel noise the interspike interval increases with increasing delay time. For an elementary neuronal network consisting of two coupled neurons we detect characteristic stochastic synchronization patterns which exhibit multiple phase-flip bifurcations: The phase-flip bifurcations occur in form of alternate transitions from an in-phase spiking activity towards an anti-phase spiking act...
Spike trains in Hodgkin-Huxley model and ISIs of acupuncture manipulations
Energy Technology Data Exchange (ETDEWEB)
Wang Jiang [School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072 (China)], E-mail: jiangwang@tju.edu.cn; Si Wenjie; Che Yanqiu; Fei Xiangyang [School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072 (China)
2008-05-15
The Hodgkin-Huxley equations (HH) are parameterized by a number of parameters and shows a variety of qualitatively different behaviors depending on the parameter values. Under stimulation of an external periodic voltage, the ISIs (interspike intervals) of a HH model are investigated in this work, while the frequency of the voltage is taken as the controlling parameter. As well-known, the science of acupuncture and moxibustion is an important component of Traditional Chinese Medicine with a long history. Although there are a number of different acupuncture manipulations, the method for distinguishing them is rarely investigated. With the idea of ISI, we study the electrical signal time series at the spinal dorsal horn produced by three different acupuncture manipulations in Zusanli point and present an effective way to distinguish them.
Directory of Open Access Journals (Sweden)
Kyle G. Horn
2012-01-01
Full Text Available Most models of central pattern generators (CPGs involve two distinct nuclei mutually inhibiting one another via synapses. Here, we present a single-nucleus model of biologically realistic Hodgkin-Huxley neurons with random gap junction coupling. Despite no explicit division of neurons into two groups, we observe a spontaneous division of neurons into two distinct firing groups. In addition, we also demonstrate this phenomenon in a simplified version of the model, highlighting the importance of afterhyperpolarization currents ( to CPGs utilizing gap junction coupling. The properties of these CPGs also appear sensitive to gap junction conductance, probability of gap junction coupling between cells, topology of gap junction coupling, and, to a lesser extent, input current into our simulated nucleus.
Strange nonchaotic oscillations in the quasiperiodically forced Hodgkin-Huxley neuron
Energy Technology Data Exchange (ETDEWEB)
Lim, Woochang; Kim, Sang-Yoon [Department of Physics, Kangwon National University, Chunchon, Kangwon-Do 200-701 (Korea, Republic of)], E-mail: wclim@kangwon.ac.kr, E-mail: sykim@kangwon.ac.kr
2009-07-03
We numerically study dynamical behaviors of the quasiperiodically forced Hodgkin-Huxley neuron and compare the dynamical responses with those for the case of periodic stimulus. In the periodically forced case, a transition from a periodic to a chaotic oscillation was found to occur via period doublings in previous numerical and experimental works. We investigate the effect of the quasiperiodic forcing on this period-doubling route to chaotic oscillation. In contrast to the case of periodic forcing, a new type of strange nonchaotic (SN) oscillating states (that are geometrically strange but have no positive Lyapunov exponents) is found to exist between the regular and chaotic oscillating states as intermediate ones. Their strange fractal geometry leads to aperiodic 'complex' spikings. Various dynamical routes to SN oscillations are identified, as in the quasiperiodically forced logistic map. These SN spikings are expected to be observed in experiments of the quasiperiodically forced squid giant axon.
Dynamic range in small-world networks of Hodgkin-Huxley neurons with chemical synapses
Batista, C. A. S.; Viana, R. L.; Lopes, S. R.; Batista, A. M.
2014-09-01
According to Stevens' law the relationship between stimulus and response is a power-law within an interval called the dynamic range. The dynamic range of sensory organs is found to be larger than that of a single neuron, suggesting that the network structure plays a key role in the behavior of both the scaling exponent and the dynamic range of neuron assemblies. In order to verify computationally the relationships between stimulus and response for spiking neurons, we investigate small-world networks of neurons described by the Hodgkin-Huxley equations connected by chemical synapses. We found that the dynamic range increases with the network size, suggesting that the enhancement of the dynamic range observed in sensory organs, with respect to single neurons, is an emergent property of complex network dynamics.
Delay-enhanced coherence of spiral waves in noisy Hodgkin-Huxley neuronal networks
Energy Technology Data Exchange (ETDEWEB)
Wang Qingyun [State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Aerospace Engineering, College of Engineering, Peking University, Beijing 100871 (China) and School of Statistics and Mathematics, Inner Mongolia Finance and Economics College, Huhhot 010051 (China)], E-mail: nmqingyun@163.com; Perc, Matjaz [Department of Physics, Faculty of Natural Sciences and Mathematics, University of Maribor, Koroska cesta 160, SI-2000 Maribor (Slovenia); Duan Zhisheng [State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Aerospace Engineering, College of Engineering, Peking University, Beijing 100871 (China); Chen Guanrong [State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Aerospace Engineering, College of Engineering, Peking University, Beijing 100871 (China); Department of Electronic Engineering, City University of Hong Kong, Hong Kong (China)
2008-08-25
We study the spatial dynamics of spiral waves in noisy Hodgkin-Huxley neuronal ensembles evoked by different information transmission delays and network topologies. In classical settings of coherence resonance the intensity of noise is fine-tuned so as to optimize the system's response. Here, we keep the noise intensity constant, and instead, vary the length of information transmission delay amongst coupled neurons. We show that there exists an intermediate transmission delay by which the spiral waves are optimally ordered, hence indicating the existence of delay-enhanced coherence of spatial dynamics in the examined system. Additionally, we examine the robustness of this phenomenon as the diffusive interaction topology changes towards the small-world type, and discover that shortcut links amongst distant neurons hinder the emergence of coherent spiral waves irrespective of transmission delay length. Presented results thus provide insights that could facilitate the understanding of information transmission delay on realistic neuronal networks.
Environmental Impacts on Spiking Properties in Hodgkin-Huxley Neuron with Direct Current Stimulus
Institute of Scientific and Technical Information of China (English)
YUAN Chang-Qing; ZHAO Tong-Jun; ZHAN Yong; ZHANG Su-Hua; LIU Hui; ZHANG Yu-Hong
2009-01-01
Based on the well accepted Hodgkin-Huxley neuron model, the neuronal intrinsic excitability is studied when the neuron is subject to varying environmental temperatures, the typical impact for its regulating ways. With computer simulation, it is found that altering environmental temperature can improve or inhibit the neuronal intrinsic excitability so as to influence the neuronal spiking properties. The impacts from environmental factors can be understood that ,the neuronal spiking threshold is essentially influenced by the fluctuations in the environ-ment. With the environmental temperature varying, burst spiking is realized for the neuronal membrane voltage because of the environment-dependent spiking threshold. This burst induced by changes in spiking threshold is different from that excited by input currents or other stimulus.
Studies of phase return map and symbolic dynamics in a periodically driven Hodgkin—Huxley neuron
Ding, Jiong; Zhang, Hong; Tong, Qin-Ye; Chen, Zhuo
2014-02-01
How neuronal spike trains encode external information is a hot topic in neurodynamics studies. In this paper, we investigate the dynamical states of the Hodgkin—Huxley neuron under periodic forcing. Depending on the parameters of the stimulus, the neuron exhibits periodic, quasiperiodic and chaotic spike trains. In order to analyze these spike trains quantitatively, we use the phase return map to describe the dynamical behavior on a one-dimensional (1D) map. According to the monotonicity or discontinuous point of the 1D map, the spike trains are transformed into symbolic sequences by implementing a coarse-grained algorithm — symbolic dynamics. Based on the ordering rules of symbolic dynamics, the parameters of the external stimulus can be measured in high resolution with finite length symbolic sequences. A reasonable explanation for why the nervous system can discriminate or cognize the small change of the external signals in a short time is also presented.
Langevin approach with rescaled noise for stochastic channel dynamics in Hodgkin-Huxley neurons
Huang, Yan-Dong; Xiang, Li; Shuai, Jian-Wei
2015-12-01
The Langevin approach has been applied to model the random open and closing dynamics of ion channels. It has long been known that the gate-based Langevin approach is not sufficiently accurate to reproduce the statistics of stochastic channel dynamics in Hodgkin-Huxley neurons. Here, we introduce a modified gate-based Langevin approach with rescaled noise strength to simulate stochastic channel dynamics. The rescaled independent gate and identical gate Langevin approaches improve the statistical results for the mean membrane voltage, inter-spike interval, and spike amplitude. Project supported by the National Natural Science Foundation for Distinguished Young Scholars of China (Grant No. 11125419), the National Natural Science Foundation of China (Grant No. 10925525), and the Funds for the Leading Talents of Fujian Province, China.
In-phase and anti-phase synchronization in noisy Hodgkin-Huxley neurons.
Ao, Xue; Hänggi, Peter; Schmid, Gerhard
2013-09-01
We numerically investigate the influence of intrinsic channel noise on the dynamical response of delay-coupling in neuronal systems. The stochastic dynamics of the spiking is modeled within a stochastic modification of the standard Hodgkin-Huxley model wherein the delay-coupling accounts for the finite propagation time of an action potential along the neuronal axon. We quantify this delay-coupling of the Pyragas-type in terms of the difference between corresponding presynaptic and postsynaptic membrane potentials. For an elementary neuronal network consisting of two coupled neurons we detect characteristic stochastic synchronization patterns which exhibit multiple phase-flip bifurcations: The phase-flip bifurcations occur in form of alternate transitions from an in-phase spiking activity towards an anti-phase spiking activity. Interestingly, these phase-flips remain robust for strong channel noise and in turn cause a striking stabilization of the spiking frequency.
Energy Technology Data Exchange (ETDEWEB)
Javidi, M. [Department of Mathematics, Iran University of Science and Technology, Narmak, Tehran 16844 (Iran, Islamic Republic of)], E-mail: mo_javidi@yahoo.com; Golbabai, A. [Department of Mathematics, Iran University of Science and Technology, Narmak, Tehran 16844 (Iran, Islamic Republic of)], E-mail: golbabai@iust.ac.ir
2009-01-30
In this study, we use the spectral collocation method using Chebyshev polynomials for spatial derivatives and fourth order Runge-Kutta method for time integration to solve the generalized Burger's-Huxley equation (GBHE). To reduce round-off error in spectral collocation (pseudospectral) method we use preconditioning. Firstly, theory of application of Chebyshev spectral collocation method with preconditioning (CSCMP) and domain decomposition on the generalized Burger's-Huxley equation presented. This method yields a system of ordinary differential algebric equations (DAEs). Secondly, we use fourth order Runge-Kutta formula for the numerical integration of the system of DAEs. The numerical results obtained by this way have been compared with the exact solution to show the efficiency of the method.
Schizophrenia, evolution and the borders of biology: on Huxley et al.'s 1964 paper in Nature.
De Bont, Raf
2010-06-01
In October 1964, Julian Huxley, Ernst Mayr, Humphrey Osmond and Abram Hoffer co-published a controversial paper in Nature, in which they tried to explain the persistence of schizophrenia from an evolutionary perspective. This article will elucidate how the reputed authors composed this paper to make it a strong argument for biological psychiatry. Through a close reading of their correspondence, it will furthermore clarify the elements which remained unspoken in the paper, but which were elementary in its genesis. The first was the dominance of psychoanalytical theory in (American) psychiatry--a dominance which the authors wanted to break. The second was the ongoing discussion on the boundaries of biological determinism and the desirability of a new kind of eugenics. As such, the Huxley et al. paper can be used to study the central issues of psychiatry in a pivotal era of its history.
Optogenetics in Silicon: A Neural Processor for Predicting Optically Active Neural Networks.
Luo, Junwen; Nikolic, Konstantin; Evans, Benjamin D; Dong, Na; Sun, Xiaohan; Andras, Peter; Yakovlev, Alex; Degenaar, Patrick
2016-08-17
We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin-Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon hardware. Our architecture consists of a Field Programmable Gated Array (FPGA) with a custom-built computing data-path, a separate data management system and a memory approach based router. Advancements over previous work include the incorporation of short and long-term calcium and light-dependent ion channels in reconfigurable hardware. Also, the developed processor is computationally efficient, requiring only 0.03 ms processing time per sub-frame for a single neuron and 9.7 ms for a fully connected network of 500 neurons with a given FPGA frequency of 56.7 MHz. It can therefore be utilized for exploration of closed loop processing and tuning of biologically realistic optogenetic circuitry.
Optogenetics in Silicon: A Neural Processor for Predicting Optically Active Neural Networks.
Junwen Luo; Nikolic, Konstantin; Evans, Benjamin D; Na Dong; Xiaohan Sun; Andras, Peter; Yakovlev, Alex; Degenaar, Patrick
2017-02-01
We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin-Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon hardware. Our architecture consists of a Field Programmable Gated Array (FPGA) with a custom-built computing data-path, a separate data management system and a memory approach based router. Advancements over previous work include the incorporation of short and long-term calcium and light-dependent ion channels in reconfigurable hardware. Also, the developed processor is computationally efficient, requiring only 0.03 ms processing time per sub-frame for a single neuron and 9.7 ms for a fully connected network of 500 neurons with a given FPGA frequency of 56.7 MHz. It can therefore be utilized for exploration of closed loop processing and tuning of biologically realistic optogenetic circuitry.
Institute of Scientific and Technical Information of China (English)
Deng Xi-Jun; Yan Zi-Zong; Han Li-Bo
2009-01-01
In this paper,the travelling wave solutions for the generalized Burgers-Huxley equation with nonlinear terms of any order are studied.By using the first integral method,which is based on the divisor theorem,some exact explicit travelling solitary wave solutions for the above equation are obtained.As a result,some minor errors and some known results in the previousl literature are clarified and improved.
Directory of Open Access Journals (Sweden)
Radojka Verčko
2005-12-01
Full Text Available The article addresses the issue of the close relationship between the nexistential concem and the narrative techniques used by English writers Ford Madox Ford, Virginia Woolf and Aldous Huxley to present the general human condition. The selected authors had introduced narrative techniques that influenced the entire development of the modern novel and that are stili highly relevant and widely used in the contemporary novel, including the Slovene modern novel.
Revisiting Okun's Relationship
Dixon, R.; Lim, G.C.; van Ours, Jan
2016-01-01
Our paper revisits Okun's relationship between observed unemployment rates and output gaps. We include in the relationship the effect of labour market institutions as well as age and gender effects. Our empirical analysis is based on 20 OECD countries over the period 1985-2013. We find that the
Mans, U.
2014-01-01
This article introduces a new perspective on city connectivity in order to analyze non-hub cities and their position in the world economy. The author revisits the different approaches discussed in the Global Commodity Chains (GCC), Global Production Networks (GPN) and World City Network (WCN) discou
A Hydrostatic Paradox Revisited
Ganci, Salvatore
2012-01-01
This paper revisits a well-known hydrostatic paradox, observed when turning upside down a glass partially filled with water and covered with a sheet of light material. The phenomenon is studied in its most general form by including the mass of the cover. A historical survey of this experiment shows that a common misunderstanding of the phenomenon…
Bingolbali, Erhan; Monaghan, John
2008-01-01
Concept image and concept definition is an important construct in mathematics education. Its use, however, has been limited to cognitive studies. This article revisits concept image in the context of research on undergraduate students' understanding of the derivative which regards the context of learning as paramount. The literature, mainly on…
Revisiting the Okun relationship
Dixon, R. (Robert); Lim, G.C.; J.C. van Ours (Jan)
2017-01-01
textabstractOur article revisits the Okun relationship between observed unemployment rates and output gaps. We include in the relationship the effect of labour market institutions as well as age and gender effects. Our empirical analysis is based on 20 OECD countries over the period 1985–2013. We
DEFF Research Database (Denmark)
Cornean, Horia; Nenciu, Gheorghe
2009-01-01
This paper is the second in a series revisiting the (effect of) Faraday rotation. We formulate and prove the thermodynamic limit for the transverse electric conductivity of Bloch electrons, as well as for the Verdet constant. The main mathematical tool is a regularized magnetic and geometric...
A Hydrostatic Paradox Revisited
Ganci, Salvatore
2012-01-01
This paper revisits a well-known hydrostatic paradox, observed when turning upside down a glass partially filled with water and covered with a sheet of light material. The phenomenon is studied in its most general form by including the mass of the cover. A historical survey of this experiment shows that a common misunderstanding of the phenomenon…
Vavoulis, Dimitrios V; Straub, Volko A; Aston, John A D; Feng, Jianfeng
2012-01-01
Traditional approaches to the problem of parameter estimation in biophysical models of neurons and neural networks usually adopt a global search algorithm (for example, an evolutionary algorithm), often in combination with a local search method (such as gradient descent) in order to minimize the value of a cost function, which measures the discrepancy between various features of the available experimental data and model output. In this study, we approach the problem of parameter estimation in conductance-based models of single neurons from a different perspective. By adopting a hidden-dynamical-systems formalism, we expressed parameter estimation as an inference problem in these systems, which can then be tackled using a range of well-established statistical inference methods. The particular method we used was Kitagawa's self-organizing state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological data. We showed that the algorithm can be used to estimate a large number of parameters, including maximal conductances, reversal potentials, kinetics of ionic currents, measurement and intrinsic noise, based on low-dimensional experimental data and sufficiently informative priors in the form of pre-defined constraints imposed on model parameters. The algorithm remained operational even when very noisy experimental data were used. Importantly, by combining the self-organizing state-space model with an adaptive sampling algorithm akin to the Covariance Matrix Adaptation Evolution Strategy, we achieved a significant reduction in the variance of parameter estimates. The algorithm did not require the explicit formulation of a cost function and it was straightforward to apply on compartmental models and multiple data sets. Overall, the proposed methodology is particularly suitable for resolving high-dimensional inference problems based on noisy electrophysiological data and, therefore, a potentially useful tool in
Institute of Scientific and Technical Information of China (English)
2008-01-01
Toxins, such as tetraethylammonium (TEA) and tetrodotoxin (TTX), can make potassium or sodium ion channels poisoned, respectively, and hence reduce the number of working ion channels and lead to the diminishment of conductance. In this paper, we have studied by numerical simulations the effects of sodium and potassium ion channel poisoning on the collective spiking activity of an array of coupled stochastic Hodgkin-Huxley (HH) neurons. It is found for a given number of neurons sodium or potas- sium ion channel block can either enhance or reduce the collective spiking regularity, depending on the membrane patch size. For a given smaller or larger patch size, potassium and sodium ion channel block can reduce or enhance the collective spiking regularity, but they have different patch size ranges for the transformation. This result shows that sodium or potassium ion channel block might have dif- ferent effects on the collective spiking activity in coupled HH neurons from the effects for a single neuron, which represents the interplay among the diminishment of maximal conductance and the in- crease of channel noise strength due to the channel blocks, as well as the bi-directional coupling be- tween the neurons.
Response of autaptic Hodgkin-Huxley neuron with noise to subthreshold sinusoidal signals
Wang, Hengtong; Chen, Yong
2016-11-01
In this work, we investigated the response of a stochastic Hodgkin-Huxley (HH) neuron with an autapse to subthreshold sinusoidal signals. It is found that the autapse not only adjusts the stochastic responses, but also improves the detection of subthreshold signals. In the case of weak noise, the autapse facilitates the response of neuron to the subthreshold sinusoidal signals with a small parameter region in tdelay- ω space. The increased noise intensity enlarges this parameter region and increases the corresponding response frequency in such range. As the autaptic intensity increases, however, this parameter region shrunks. We also observed that there is an optimal range of the delay time of autapse, within which the stochastic HH neuron fires action potentials with high frequency. The corresponding response spike train for the optimal delay time is nearly a regular sequence with the interspike intervals approximated to the delay time. The current results reveal a novel resonance phenomenon facilitated by autapse, named autaptic delay-induced coherence resonance.
Bistability and resonance in the periodically stimulated Hodgkin-Huxley model with noise
Borkowski, L S
2010-01-01
We describe general characteristics of the Hodgkin-Huxley neuron's response to a periodic train of short current pulses with Gaussian noise. The deterministic neuron is bistable for antiresonant frequencies. When the stimuli arrive at the resonant frequency the firing rate is a continuous function of the current amplitude $I_0$ and scales as $(I_0-I_{th})^{1/2}$, where $I_{th}$ is an approximate threshold. Intervals of continuous irregular response alternate with integer mode-locked regions with bistable excitation edge. There is an even-all multimodal transition between the 2:1 and 3:1 states in the vicinity of the main resonance, which is analogous to the odd-all transition discovered earlier in the high-frequency regime. For $I_0
Response of the Hodgkin-Huxley neuron to a periodic sequence of biphasic pulses
Borkowski, L S
2013-01-01
We study the response of the Hodgkin-Huxley neuron stimulated periodically by biphasic rectangular current pulses. The optimal response for charge-balanced input is obtained for cathodic-first pulses with an inter-phase gap (IPG) approximately equal 5 ms. For short pulses the topology of the global bifurcation diagram in the period-amplitude plane is approximately invariant with respect to the pulse polarity and shape details. If stimuli are delivered at neuron's resonant frequencies the firing rate is a continuous function of pulse amplitude. At nonresonant frequencies the quiescent state and the firing state coexist over a range of amplitude values and the transition to excitability is a discontinuous one. There is a multimodal odd-all transition between the 2:1 and 3:1 locked-in states. A strong antiresonant effect is found between the states 3:1 and 4:1, where the modes (2+3n):1, $n=0,1,2,...$, are entirely absent. At high frequencies the excitation threshold is a nonmonotonic function of the stimulus and...
Response of a Hodgkin-Huxley neuron to a high-frequency input
Borkowski, L S
2010-01-01
We study the response of a Hodgkin-Huxley neuron stimulated by a periodic sequence of conductance pulses arriving through the synapse in the high frequency regime. In addition to the usual excitation threshold there is a smooth crossover from the firing to the silent regime for increasing pulse amplitude $g_{syn}$. The amplitude of the voltage spikes decreases approximately linearly with $g_{syn}$. In some regions of parameter space the response is irregular, probably chaotic. In the chaotic regime between the mode-locked regions 3:1 and 2:1 near the lower excitation threshold the output interspike interval histogram (ISIH) undergoes a sharp transition. If the driving period is below the critical value, $T_i T^*$ even multiples of $T_i$ also appear in the histogram, starting from the largest values. Near $T^*$ the ISIH scales logarithmically on both sides of the transition. The coefficient of variation of ISIH has a cusp singularity at $T^*$. The average response period has a maximum slightly above $T^*$. Ne...
Strange nonchaotic spiking in the quasiperiodically-forced Hodgkin-Huxley neuron
Energy Technology Data Exchange (ETDEWEB)
Lim, Woochang; Kim, Sangyoon [Kangwon National University, Chunchon (Korea, Republic of)
2010-06-15
We study the transition from a silent state to a spiking state by varying the dc stimulus in the quasiperiodically-forced Hodgkin-Huxley neuron. For this quasiperiodically-forced case, a new type of strange nonchaotic (SN) spiking state is found to appear between the silent state and the chaotic spiking state as intermediate one. Using a rational approximation to the quasiperiodic forcing, we investigate the mechanism for the appearance of such an SN spiking state. We thus find that a smooth torus (corresponding to the silent state) is transformed into an SN spiking attractor via a phase-dependent saddle-node bifurcation. This is in contrast to the periodically-forced case where the silent state transforms directly to a chaotic spiking state. SN spiking states are characterized in terms of the interspike interval, so they are found to be aperiodic complex ones, as in the case of chaotic spiking states. Hence, aperiodic complex spikings may result from two dynamically different states with strange geometry (one is chaotic and the other one is nonchaotic).
Quantification of degeneracy in Hodgkin-Huxley neurons on Newman-Watts small world network.
Man, Menghua; Zhang, Ya; Ma, Guilei; Friston, Karl; Liu, Shanghe
2016-08-07
Degeneracy is a fundamental source of biological robustness, complexity and evolvability in many biological systems. However, degeneracy is often confused with redundancy. Furthermore, the quantification of degeneracy has not been addressed for realistic neuronal networks. The objective of this paper is to characterize degeneracy in neuronal network models via quantitative mathematic measures. Firstly, we establish Hodgkin-Huxley neuronal networks with Newman-Watts small world network architectures. Secondly, in order to calculate the degeneracy, redundancy and complexity in the ensuing networks, we use information entropy to quantify the information a neuronal response carries about the stimulus - and mutual information to measure the contribution of each subset of the neuronal network. Finally, we analyze the interdependency of degeneracy, redundancy and complexity - and how these three measures depend upon network architectures. Our results suggest that degeneracy can be applied to any neuronal network as a formal measure, and degeneracy is distinct from redundancy. Qualitatively degeneracy and complexity are more highly correlated over different network architectures, in comparison to redundancy. Quantitatively, the relationship between both degeneracy and redundancy depends on network coupling strength: both degeneracy and redundancy increase with complexity for small coupling strengths; however, as coupling strength increases, redundancy decreases with complexity (in contrast to degeneracy, which is relatively invariant). These results suggest that the degeneracy is a general topologic characteristic of neuronal networks, which could be applied quantitatively in neuroscience and connectomics.
Bifurcation analysis of delay-induced patterns in a ring of Hodgkin-Huxley neurons.
Kantner, Markus; Yanchuk, Serhiy
2013-09-28
Rings of delay-coupled neurons possess a striking capability to produce various stable spiking patterns. In order to reveal the mechanisms of their appearance, we present a bifurcation analysis of the Hodgkin-Huxley (HH) system with delayed feedback as well as a closed loop of HH neurons. We consider mainly the effects of external currents and communication delays. It is shown that typically periodic patterns of different spatial form (wavenumber) appear via Hopf bifurcations as the external current or time delay changes. The Hopf bifurcations are shown to occur in relatively narrow regions of the external current values, which are independent of the delays. Additional patterns, which have the same wavenumbers as the existing ones, appear via saddle-node bifurcations of limit cycles. The obtained bifurcation diagrams are evidence for the important role of communication delays for the emergence of multiple coexistent spiking patterns. The effects of a short-cut, which destroys the rotational symmetry of the ring, are also briefly discussed.
Channel-noise-induced critical slowing in the subthreshold Hodgkin-Huxley neuron
Bukoski, Alex; Steyn-Ross, D. A.; Steyn-Ross, Moira L.
2015-03-01
The dynamics of a spiking neuron approaching threshold is investigated in the framework of Markov-chain models describing the random state-transitions of the underlying ion-channel proteins. We characterize subthreshold channel-noise-induced transmembrane potential fluctuations in both type-I (integrator) and type-II (resonator) parametrizations of the classic conductance-based Hodgkin-Huxley equations. As each neuron approaches spiking threshold from below, numerical simulations of stochastic trajectories demonstrate pronounced growth in amplitude simultaneous with decay in frequency of membrane voltage fluctuations induced by ion-channel state transitions. To explore this progression of fluctuation statistics, we approximate the exact Markov treatment with a 12-variable channel-based stochastic differential equation (SDE) and its Ornstein-Uhlenbeck (OU) linearization and show excellent agreement between Markov and SDE numerical simulations. Predictions of the OU theory with respect to membrane potential fluctuation variance, autocorrelation, correlation time, and spectral density are also in agreement and illustrate the close connection between the eigenvalue structure of the associated deterministic bifurcations and the observed behavior of the noisy Markov traces on close approach to threshold for both integrator and resonator point-neuron varieties.
Enhancement of spike coherence by the departure from Gaussian noise in a Hodgkin-Huxley neuron
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
Experimental study has shown that non-Gaussian noise exists in sensory systems like neurons.The departure from Gaussian behavior is a characteristic parameter of non-Gaussian noise.In this paper,we have numerically studied the effect of a particular kind of non-Gaussian colored noise(NGN),especially its departure q from Gaussian noise(q = 1),on the spiking activity in a deterministic Hodgkin-Huxley(HH) neuron driven by sub-threshold periodic stimulus.Simulation results show that the departure q can affect the spiking activity induced by noise intensity D.For smaller q values,the minimum in the variation coefficient(CV) as a function of noise intensity(D) becomes smaller,showing that D-induced stochastic resonance(SR) becomes strengthened.Meanwhile,depending on the value of D,q can either enhance or reduce the spiking regularity.Interestingly,CV changes non-monotonously with varying q and passes through a minimum at an intermediate q,representing the presence of "departure-induced SR".This result shows that appropriate departures of the NGN can enhance the spike coherence in the HH neuron.Since the departure of the NGN determines the probability distribution and hence may denote the type of the noise,"departure-induced SR" shows that different types of noise can enhance the spike coherence,and hence may improve the timing precision of sub-threshold signal encoding in the HH neuron.
Effect of autaptic activity on the response of a Hodgkin-Huxley neuron
Wang, Hengtong; Wang, Longfei; Chen, Yueling; Chen, Yong
2014-09-01
An autapse is a special synapse that connects a neuron to itself. In this study, we investigated the effect of an autapse on the responses of a Hodgkin-Huxley neuron to different forms of external stimuli. When the neuron was subjected to a DC stimulus, the firing frequencies and the interspike interval distributions of the output spike trains showed periodic behaviors as the autaptic delay time increased. When the input was a synaptic pulse-like train with random interspike intervals, we observed low-pass and band-pass filtering behaviors. Moreover, the region over which the output ISIs are distributed and the mean firing frequency display periodic behaviors with increasing autaptic delay time. When specific autaptic parameters were chosen, most of the input ISIs could be filtered, and the response spike trains were nearly regular, even with a highly random input. The background mechanism of these observed dynamics has been analyzed based on the phase response curve method. We also found that the information entropy of the output spike train could be modified by the autapse. These results also suggest that the autapse can serve as a regulator of information response in the nervous system.
A study of quantum mechanical probabilities in the classical Hodgkin-Huxley model.
Moradi, N; Scholkmann, F; Salari, V
2015-03-01
The Hodgkin-Huxley (HH) model is a powerful model to explain different aspects of spike generation in excitable cells. However, the HH model was proposed in 1952 when the real structure of the ion channel was unknown. It is now common knowledge that in many ion-channel proteins the flow of ions through the pore is governed by a gate, comprising a so-called "selectivity filter" inside the ion channel, which can be controlled by electrical interactions. The selectivity filter (SF) is believed to be responsible for the selection and fast conduction of particular ions across the membrane of an excitable cell. Other (generally larger) parts of the molecule such as the pore-domain gate control the access of ions to the channel protein. In fact, two types of gates are considered here for ion channels: the "external gate", which is the voltage sensitive gate, and the "internal gate" which is the selectivity filter gate (SFG). Some quantum effects are expected in the SFG due to its small dimensions, which may play an important role in the operation of an ion channel. Here, we examine parameters in a generalized model of HH to see whether any parameter affects the spike generation. Our results indicate that the previously suggested semi-quantum-classical equation proposed by Bernroider and Summhammer (BS) agrees strongly with the HH equation under different conditions and may even provide a better explanation in some cases. We conclude that the BS model can refine the classical HH model substantially.
Institute of Scientific and Technical Information of China (English)
GONG YuBing; XU Bo; MA XiaoGuang; HAN JiQu
2008-01-01
Toxins, such as tetraethylammonium (TEA) and tetrodotoxin (TTX), can make potassium or sodium ion channels poisoned, respectively, and hence reduce the number of working ion channels and lead to the diminishment of conductance. In this paper, we have studied by numerical simulations the effects of sodium and potassium ion channel poisoning on the collective spiking activity of an array of coupled stochastic Hodgkin-Huxley (HH) neurons. It is found for a given number of neurons sodium or potas-sium ion channel block can either enhance or reduce the collective spiking regularity, depending on the membrane patch size. For a given smaller or larger patch size, potassium and sodium ion channel block can reduce or enhance the collective spiking regularity, but they have different patch size ranges for the transformation. This result shows that sodium or potassium ion channel block might have dif-ferent effects on the collective spiking activity in coupled HH neurons from the effects for a single neuron, which represents the interplay among the diminishment of maximal conductance and the in-crease of channel noise strength due to the channel blocks, as well as the bi-directional coupling be-tween the neurons.
Pseudo-Lyapunov exponents and predictability of Hodgkin-Huxley neuronal network dynamics.
Sun, Yi; Zhou, Douglas; Rangan, Aaditya V; Cai, David
2010-04-01
We present a numerical analysis of the dynamics of all-to-all coupled Hodgkin-Huxley (HH) neuronal networks with Poisson spike inputs. It is important to point out that, since the dynamical vector of the system contains discontinuous variables, we propose a so-called pseudo-Lyapunov exponent adapted from the classical definition using only continuous dynamical variables, and apply it in our numerical investigation. The numerical results of the largest Lyapunov exponent using this new definition are consistent with the dynamical regimes of the network. Three typical dynamical regimes-asynchronous, chaotic and synchronous, are found as the synaptic coupling strength increases from weak to strong. We use the pseudo-Lyapunov exponent and the power spectrum analysis of voltage traces to characterize the types of the network behavior. In the nonchaotic (asynchronous or synchronous) dynamical regimes, i.e., the weak or strong coupling limits, the pseudo-Lyapunov exponent is negative and there is a good numerical convergence of the solution in the trajectory-wise sense by using our numerical methods. Consequently, in these regimes the evolution of neuronal networks is reliable. For the chaotic dynamical regime with an intermediate strong coupling, the pseudo-Lyapunov exponent is positive, and there is no numerical convergence of the solution and only statistical quantifications of the numerical results are reliable. Finally, we present numerical evidence that the value of pseudo-Lyapunov exponent coincides with that of the standard Lyapunov exponent for systems we have been able to examine.
Gibson, C H
1999-01-01
A theory of fossil turbulence presented in the 11th Liege Colloquium on Marine turbulence is "revisited" in the 29th Liege Colloquium "Marine Turbulence Revisited". The Gibson (1980) theory applied universal similarity theories of turbulence and turbulent mixing to the vertical evolution of an isolated patch of turbulence in a stratified fluid as it is constrained and fossilized by buoyancy forces. Towed oceanic microstructure measurements of Schedvin (1979) confirmed the predicted universal constants. Universal constants, spectra, hydrodynamic phase diagrams (HPDs) and other predictions of the theory have been reconfirmed by a wide variety of field and laboratory observations. Fossil turbulence theory has many applications; for example, in marine biology, laboratory and field measurements suggest phytoplankton species with different swimming abilities adjust their growth strategies differently by pattern recognition of several days of turbulence-fossil-turbulence dissipation and persistence times above thres...
Lemaire, Koen K; Baan, Guus C; Jaspers, Richard T; van Soest, A J Knoek
2016-04-01
The relationship between mechanical and metabolic behaviour in the widely used Hill muscle-tendon complex (MTC) model is not straightforward, whereas this is an integral part of the Huxley model. In this study, we assessed to what extent Huxley- and Hill-type MTC models yield adequate predictions of mechanical muscle behaviour during stretch-shortening cycles (SSCs). In fully anaesthetized male Wistar rats (N=3), m. soleus was dissected completely free, except for the insertion. Cuff electrodes were placed over the n. ischiadicus. The distal end of the tendon was connected to a servo motor, via a force transducer. The setup allowed for full control over muscle stimulation and length, while force was measured. Quick-release and isovelocity contractions (part 1), and SSCs (part 2) were imposed. Simulations of part 2 were made with both a Hill and a Huxley MTC model, using parameter values determined from part 1. Modifications to the classic two-state Huxley model were made to incorporate series elasticity, activation dynamics, and active and passive force-length relationships. Results were similar for all rats. Fitting of the free parameters to the data of part 1 was near perfect (R(2)>0.97). During SSCs, predicted peak force and force during relaxation deviated from the experimental data for both models. Overall, both models yielded similarly adequate predictions of the experimental data. We conclude that Huxley and Hill MTC models are equally valid with respect to mechanical behaviour.
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2008-01-01
We revisit the deterministic graphical games of Washburn. A deterministic graphical game can be described as a simple stochastic game (a notion due to Anne Condon), except that we allow arbitrary real payoffs but disallow moves of chance. We study the complexity of solving deterministic graphical...... games and obtain an almost-linear time comparison-based algorithm for computing an equilibrium of such a game. The existence of a linear time comparison-based algorithm remains an open problem....
Reverse cholesterol transport revisited
Institute of Scientific and Technical Information of China (English)
Astrid; E; van; der; Velde
2010-01-01
Reverse cholesterol transport was originally described as the high-density lipoprotein-mediated cholesterol flux from the periphery via the hepatobiliary tract to the intestinal lumen, leading to fecal excretion. Since the introduction of reverse cholesterol transport in the 1970s, this pathway has been intensively investigated. In this topic highlight, the classical reverse cholesterol transport concepts are discussed and the subject reverse cholesterol transport is revisited.
Directory of Open Access Journals (Sweden)
Pellegrino Edmund D
2001-04-01
Full Text Available Abstract A decade ago, we reviewed the field of clinical ethics; assessed its progress in research, education, and ethics committees and consultation; and made predictions about the future of the field. In this article, we revisit clinical ethics to examine our earlier observations, highlight key developments, and discuss remaining challenges for clinical ethics, including the need to develop a global perspective on clinical ethics problems.
Revisiting modern portfolio theory
Tenani, Paulo
2016-01-01
This paper revisits Modern Portfolio Theory and derives eleven properties of Efficient Allocations and Portfolios in the presence of leverage. With different degrees of leverage, an Efficient Portfolio is a linear combination of two portfolios that lie in different efficient frontiers - which allows for an attractive reinterpretation of the Separation Theorem. In particular a change in the investor risk-return preferences will leave the allocation between the Minimum Risk and Risk Portfolios ...
Power-Law Dynamics of Membrane Conductances Increase Spiking Diversity in a Hodgkin-Huxley Model.
Teka, Wondimu; Stockton, David; Santamaria, Fidel
2016-03-01
We studied the effects of non-Markovian power-law voltage dependent conductances on the generation of action potentials and spiking patterns in a Hodgkin-Huxley model. To implement slow-adapting power-law dynamics of the gating variables of the potassium, n, and sodium, m and h, conductances we used fractional derivatives of order η≤1. The fractional derivatives were used to solve the kinetic equations of each gate. We systematically classified the properties of each gate as a function of η. We then tested if the full model could generate action potentials with the different power-law behaving gates. Finally, we studied the patterns of action potential that emerged in each case. Our results show the model produces a wide range of action potential shapes and spiking patterns in response to constant current stimulation as a function of η. In comparison with the classical model, the action potential shapes for power-law behaving potassium conductance (n gate) showed a longer peak and shallow hyperpolarization; for power-law activation of the sodium conductance (m gate), the action potentials had a sharp rise time; and for power-law inactivation of the sodium conductance (h gate) the spikes had wider peak that for low values of η replicated pituitary- and cardiac-type action potentials. With all physiological parameters fixed a wide range of spiking patterns emerged as a function of the value of the constant input current and η, such as square wave bursting, mixed mode oscillations, and pseudo-plateau potentials. Our analyses show that the intrinsic memory trace of the fractional derivative provides a negative feedback mechanism between the voltage trace and the activity of the power-law behaving gate variable. As a consequence, power-law behaving conductances result in an increase in the number of spiking patterns a neuron can generate and, we propose, expand the computational capacity of the neuron.
Comparison between Hodgkin-Huxley and Markov formulations of cardiac ion channels.
Carbonell-Pascual, Beatriz; Godoy, Eduardo; Ferrer, Ana; Romero, Lucia; Ferrero, Jose M
2016-06-21
When simulating the macroscopic current flowing through cardiac ion channels, two mathematical formalisms can be adopted: the Hodgkin-Huxley model (HHM) formulation, which describes openings and closings of channel 'gates', or the Markov model (MM) formulation, based on channel 'state' transitions. The latter was first used in 1995 to simulate the effects of mutations in ionic currents and, since then, its use has been extended to wild-type channels also. While the MMs better describe the actual behavior of ion channels, they are mathematically more complex than HHMs in terms of parameter estimation and identifiability and are computationally much more demanding, which can dramatically increase computational time in large-scale (e.g. whole heart) simulations. We hypothesize that a HHM formulation obtained from classical patch-clamp protocols in wild-type and mutant ion channels can be used to correctly simulate cardiac action potentials and their static and dynamic properties. To validate our hypothesis, we selected two pivotal cardiac ionic currents (the rapid delayed rectifier K(+) current, IKr, and the inward Na(+) current, INa) and formulated HHMs for both wild-type and mutant channels (LQT2-linked T474I mutation for IKr and LQT3-linked ΔKPQ mutation for INa). Action potentials were then simulated using the MM and HHM versions of the currents, and the action potential waveforms, biomarkers and action potential duration rate dependence properties were compared in control conditions and in the presence of physiological variability. While small differences between ionic currents were found between the two models (correlation coefficient ρ>0.92), the simulations yielded almost identical action potentials (ρ>0.99), suggesting that HHMs may also be valid to simulate the effects of mutations affecting IKr and INa on the action potential.
Power-Law Dynamics of Membrane Conductances Increase Spiking Diversity in a Hodgkin-Huxley Model.
Directory of Open Access Journals (Sweden)
Wondimu Teka
2016-03-01
Full Text Available We studied the effects of non-Markovian power-law voltage dependent conductances on the generation of action potentials and spiking patterns in a Hodgkin-Huxley model. To implement slow-adapting power-law dynamics of the gating variables of the potassium, n, and sodium, m and h, conductances we used fractional derivatives of order η≤1. The fractional derivatives were used to solve the kinetic equations of each gate. We systematically classified the properties of each gate as a function of η. We then tested if the full model could generate action potentials with the different power-law behaving gates. Finally, we studied the patterns of action potential that emerged in each case. Our results show the model produces a wide range of action potential shapes and spiking patterns in response to constant current stimulation as a function of η. In comparison with the classical model, the action potential shapes for power-law behaving potassium conductance (n gate showed a longer peak and shallow hyperpolarization; for power-law activation of the sodium conductance (m gate, the action potentials had a sharp rise time; and for power-law inactivation of the sodium conductance (h gate the spikes had wider peak that for low values of η replicated pituitary- and cardiac-type action potentials. With all physiological parameters fixed a wide range of spiking patterns emerged as a function of the value of the constant input current and η, such as square wave bursting, mixed mode oscillations, and pseudo-plateau potentials. Our analyses show that the intrinsic memory trace of the fractional derivative provides a negative feedback mechanism between the voltage trace and the activity of the power-law behaving gate variable. As a consequence, power-law behaving conductances result in an increase in the number of spiking patterns a neuron can generate and, we propose, expand the computational capacity of the neuron.
Institute of Scientific and Technical Information of China (English)
YUAN Wu-Jie; LUO Xiao-Shu; JIANG Pin-Qun
2007-01-01
In this paper,we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism.Then we study excitement properties of the model under alternating current (AC) stimulation.The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli,such as refractory period and the brain neural excitement response induced by different intensities of nolse and coupling.The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.
Revisiting and Renegotiating Wars
DEFF Research Database (Denmark)
Gade, Solveig
2014-01-01
Anri Sala’s film 1395 Days Without Red (2011) provides a kind of reenactment of an accidental day during the 1992-95 siege of Sarajevo. Shot in today’s Sarajevo, the film revisits and embodies some of the widely circulated images of the siege, such as inhabitants sprinting across so-called Sniper...... Alley in order to avoid the bullets of the Bosnian Serbian snipers positioned around the city. Based on a close reading of Sala’s work, this article will scrutinize how subjectivating techniques of power, during times of war, affectively work to create boundaries between those excluded from and those...
Osano, Bob
2016-01-01
In this article we revisit the significance of the often debated structural similarity between the equations of electromagnetism and fluid dynamics. Although the matching of the two sets of equations has successfully been done for non-dissipative forms of the equations, little has been done for cases where the dissipative terms are non-negligible. We consider the consequence of non-negligible viscosity and diffusivity, and how the fine-tuning of these parameters could allow fluid dynamics to be used to indirectly study certain properties of magnetic fields.
Reading Neural Encodings using Phase Space Methods
Abarbanel, Henry D I; Abarbanel, Henry D I; Tumer, Evren C.
2003-01-01
Environmental signals sensed by nervous systems are often represented in spike trains carried from sensory neurons to higher neural functions where decisions and functional actions occur. Information about the environmental stimulus is contained (encoded) in the train of spikes. We show how to "read" the encoding using state space methods of nonlinear dynamics. We create a mapping from spike signals which are output from the neural processing system back to an estimate of the analog input signal. This mapping is realized locally in a reconstructed state space embodying both the dynamics of the source of the sensory signal and the dynamics of the neural circuit doing the processing. We explore this idea using a Hodgkin-Huxley conductance based neuron model and input from a low dimensional dynamical system, the Lorenz system. We show that one may accurately learn the dynamical input/output connection and estimate with high precision the details of the input signals from spike timing output alone. This form of "...
Reframing in dentistry: Revisited
Directory of Open Access Journals (Sweden)
Sivakumar Nuvvula
2013-01-01
Full Text Available The successful practice of dentistry involves a good combination of technical skills and soft skills. Soft skills or communication skills are not taught extensively in dental schools and it can be challenging to learn and at times in treating dental patients. Guiding the child′s behavior in the dental operatory is one of the preliminary steps to be taken by the pediatric dentist and one who can successfully modify the behavior can definitely pave the way for a life time comprehensive oral care. This article is an attempt to revisit a simple behavior guidance technique, reframing and explain the possible psychological perspectives behind it for better use in the clinical practice.
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Klas Olof Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2012-01-01
Starting from Zermelo’s classical formal treatment of chess, we trace through history the analysis of two-player win/lose/draw games with perfect information and potentially infinite play. Such chess-like games have appeared in many different research communities, and methods for solving them......, such as retrograde analysis, have been rediscovered independently. We then revisit Washburn’s deterministic graphical games (DGGs), a natural generalization of chess-like games to arbitrary zero-sum payoffs. We study the complexity of solving DGGs and obtain an almost-linear time comparison-based algorithm...... for finding optimal strategies in such games. The existence of a linear time comparison-based algorithm remains an open problem....
Chiodi, Filippo; Claudin, Philippe
2012-01-01
The river bar instability is revisited, using a hydrodynamical model based on Reynolds averaged Navier-Stokes equations. The results are contrasted with the standard analysis based on shallow water Saint-Venant equations. We first show that the stability of both transverse modes (ripples) and of small wavelength inclined modes (bars) predicted by the Saint-Venant approach are artefacts of this hydrodynamical approximation. When using a more reliable hydrodynamical model, the dispersion relation does not present any maximum of the growth rate when the sediment transport is assumed to be locally saturated. The analysis therefore reveals the fundamental importance of the relaxation of sediment transport towards equilibrium as it it is responsible for the stabilisation of small wavelength modes. This dynamical mechanism is characterised by the saturation number, defined as the ratio of the saturation length to the water depth Lsat/H. This dimensionless number controls the transition from ripples (transverse patte...
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2004-01-01
The derivation of the life quality index (LQI) is revisited for a revision. This revision takes into account the unpaid but necessary work time needed to stay alive in clean and healthy conditions to be fit for effective wealth producing work and to enjoyable free time. Dimension analysis...... consistency problems with the standard power function expression of the LQI are pointed out. It is emphasized that the combination coefficient in the convex differential combination between the relative differential of the gross domestic product per capita and the relative differential of the expected life...... at birth should not vary between countries. Finally the distributional assumptions are relaxed as compared to the assumptions made in an earlier work by the author. These assumptions concern the calculation of the life expectancy change due to the removal of an accident source. Moreover a simple public...
Lorentz violation naturalness revisited
Belenchia, Alessio; Liberati, Stefano
2016-01-01
We revisit here the naturalness problem of Lorentz invariance violations on a simple toy model of a scalar field coupled to a fermion field via a Yukawa interaction. We first review some well-known results concerning the low-energy percolation of Lorentz violation from high energies, presenting some details of the analysis not explicitly discussed in the literature and discussing some previously unnoticed subtleties. We then show how a separation between the scale of validity of the effective field theory and that one of Lorentz invariance violations can hinder this low-energy percolation. While such protection mechanism was previously considered in the literature, we provide here a simple illustration of how it works and of its general features. Finally, we consider a case in which dissipation is present, showing that the dissipative behaviour does not percolate generically to lower mass dimension operators albeit dispersion does. Moreover, we show that a scale separation can protect from unsuppressed low-en...
Firewall Configuration Errors Revisited
Wool, Avishai
2009-01-01
The first quantitative evaluation of the quality of corporate firewall configurations appeared in 2004, based on Check Point FireWall-1 rule-sets. In general that survey indicated that corporate firewalls were often enforcing poorly written rule-sets, containing many mistakes. The goal of this work is to revisit the first survey. The current study is much larger. Moreover, for the first time, the study includes configurations from two major vendors. The study also introduce a novel "Firewall Complexity" (FC) measure, that applies to both types of firewalls. The findings of the current study indeed validate the 2004 study's main observations: firewalls are (still) poorly configured, and a rule-set's complexity is (still) positively correlated with the number of detected risk items. Thus we can conclude that, for well-configured firewalls, ``small is (still) beautiful''. However, unlike the 2004 study, we see no significant indication that later software versions have fewer errors (for both vendors).
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Klas Olof Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2012-01-01
Starting from Zermelo’s classical formal treatment of chess, we trace through history the analysis of two-player win/lose/draw games with perfect information and potentially infinite play. Such chess-like games have appeared in many different research communities, and methods for solving them......, such as retrograde analysis, have been rediscovered independently. We then revisit Washburn’s deterministic graphical games (DGGs), a natural generalization of chess-like games to arbitrary zero-sum payoffs. We study the complexity of solving DGGs and obtain an almost-linear time comparison-based algorithm...... for finding optimal strategies in such games. The existence of a linear time comparison-based algorithm remains an open problem....
Revisiting the Lambert's Problem
Izzo, Dario
2014-01-01
The orbital boundary value problem, also known as Lambert Problem, is revisited. Building upon Lancaster and Blanchard approach, new relations are revealed and a new variable representing all problem classes, under L-similarity, is used to express the time of flight equation. In the new variable, the time of flight curves have two oblique asymptotes and they mostly appear to be conveniently approximated by piecewise continuous lines. We use and invert such a simple approximation to provide an efficient initial guess to an Householder iterative method that is then able to converge, for the single revoltuion case, in only two iterations. The resulting algorithm is compared to Gooding's procedure revealing to be numerically as accurate, while having a smaller computational complexity.
Klein's double discontinuity revisited
DEFF Research Database (Denmark)
Winsløw, Carl; Grønbæk, Niels
2014-01-01
mathematics courses which are mandatory to become a high school teacher of mathematics. To what extent does the “advanced” experience enable them to approach the high school calculus in a deeper and more autonomous way ? To what extent can “capstone” courses support such an approach ? How could it be hindered......Much effort and research has been invested into understanding and bridging the ‘gaps’ which many students experience in terms of contents and expectations as they begin university studies with a heavy component of mathematics, typically in the form of calculus courses. We have several studies...... of bridging measures, success rates and many other aspects of these “entrance transition” problems. In this paper, we consider the inverse transition, experienced by university students as they revisit core parts of high school mathematics (in particular, calculus) after completing the undergraduate...
DEFF Research Database (Denmark)
Grønbæk, Kaj; Whitehead, Jim; De Bra, Paul
2002-01-01
It has been 15 years since the original presentation by Frank Halasz at Hypertext'87 on seven issues for the next generation of hypertext systems. These issues are: Search and Query Composites Virtual Structures Computation in/over hypertext network Versioning Collaborative Work Extensibility...... and Tailorability Since that time, these issues have formed the nucleus of multiple research agendas within the Hypertext community. Befitting this direction-setting role, the issues have been revisited several times, by Halasz in his 1991 Hypertext keynote talk, and by Randy Trigg in his 1996 Hypertext keynote...... five years later. Additionally, over the intervening 15 years, many research systems have addressed the original seven issues, and new research avenues have opened up. The goal of this panel is to begin the process of developing a new set of seven issues for the next generation of hypertext system...
Directory of Open Access Journals (Sweden)
K. Usha
2016-09-01
Full Text Available This paper evaluates the change in metabolic energy required to maintain the signalling activity of neurons in the presence of an external electric field. We have analysed the Hodgkin–Huxley type conductance based fast spiking neuron model as electrical circuit by changing the frequency and amplitude of the applied electric field. The study has shown that, the presence of electric field increases the membrane potential, electrical energy supply and metabolic energy consumption. As the amplitude of applied electric field increases by keeping a constant frequency, the membrane potential increases and consequently the electrical energy supply and metabolic energy consumption increases. On increasing the frequency of the applied field, the peak value of membrane potential after depolarization gradually decreases as a result electrical energy supply decreases which results in a lower rate of hydrolysis of ATP molecules.
Vaccaro, S R
2016-01-01
The Na+ current in nerve and muscle membranes may be described in terms of the activation variable m(t) and the inactivation variable h(t), which are dependent on the transitions of S4 sensors in each of the ion channel domains DI to DIV. The time-dependence of the Na+ current and the rate equations satisfied by m(t) and h(t) may be derived from the solution to a master equation which describes the coupling between two activation sensors regulating the Na+ channel conductance and a two stage inactivation process. The voltage dependence of the rate functions for inactivation and recovery from inactivation are consistent with the empirically determined Hodgkin-Huxley expressions, and exhibit saturation for both depolarized and hyperpolarized clamp potentials.
Borges, R. R.; Borges, F. S.; Lameu, E. L.; Batista, A. M.; Iarosz, K. C.; Caldas, I. L.; Viana, R. L.; Sanjuán, M. A. F.
2016-05-01
In this paper, we study the effects of spike timing-dependent plasticity on synchronisation in a network of Hodgkin-Huxley neurons. Neuron plasticity is a flexible property of a neuron and its network to change temporarily or permanently their biochemical, physiological, and morphological characteristics, in order to adapt to the environment. Regarding the plasticity, we consider Hebbian rules, specifically for spike timing-dependent plasticity (STDP), and with regard to network, we consider that the connections are randomly distributed. We analyse the synchronisation and desynchronisation according to an input level and probability of connections. Moreover, we verify that the transition for synchronisation depends on the neuronal network architecture, and the external perturbation level.
Ribeiro, Felipe Bezerra; Buckup, Ludwig; Gomes, Kelly Martinez; Araujo, Paula Beatriz
2016-08-30
Two new species of Parastacus Huxley, 1879 are described from material collected in the state of Rio Grande do Sul, southern Brazil: Parastacus fluviatilis sp. nov. from highland streams and Parastacus caeruleodactylus sp. nov. from wetlands. Parastacus fluviatilis sp. nov. is distinguished mainly by large chelipeds with dense setae cover on the cutting edge of fingers, telson subtriangular with two lateral blunt spines and strongly concave ventral surface of lateral process of thoracic sternites 6 and 7. Parastacus caeruleodactylus sp. nov. is distinguished mainly by blue cheliped fingers and a large gap between them, reduced abdomen, dorsal and ventral margins of dactylus, propodus and carpus of second pair of pereiopods with tufts of long setae and mid-dorsal carina of exopod of uropods unarmed. According to IUCN Red List criteria both species are considered endangered. Habitat characterization and a method for defining the shape of second abdominal pleura are also provided.
Directory of Open Access Journals (Sweden)
Felipe Bezerra Ribeiro
Full Text Available Abstract In this contribution we describe a new species of burrowing crayfish of the genus Parastacus Huxley, 1879 from a swamp forest in southern Brazil and determine its conservation status. The distinction of the new species is based on morphology and the mitochondrial DNA marker 16S rRNA. The extinction risk was assessed according to the sub-criterion B1 of IUCN that estimates the Extent of Occurrence (EOO. Parastacus tuerkayi sp. nov. is morphologically distinguishable from all species of Parastacus by having three lines of verrucous tubercles on the dorsomesial margin of the cheliped propodus and a suborbital angle exceeding 90°. The EOO comprises 647,674 km², and the species is classified as “endangered”. Phylogenetic relationships indicate the distinct position of this new species in relation to the already described species.
Lorentz violation naturalness revisited
Energy Technology Data Exchange (ETDEWEB)
Belenchia, Alessio; Gambassi, Andrea; Liberati, Stefano [SISSA - International School for Advanced Studies, via Bonomea 265, 34136 Trieste (Italy); INFN, Sezione di Trieste, via Valerio 2, 34127 Trieste (Italy)
2016-06-08
We revisit here the naturalness problem of Lorentz invariance violations on a simple toy model of a scalar field coupled to a fermion field via a Yukawa interaction. We first review some well-known results concerning the low-energy percolation of Lorentz violation from high energies, presenting some details of the analysis not explicitly discussed in the literature and discussing some previously unnoticed subtleties. We then show how a separation between the scale of validity of the effective field theory and that one of Lorentz invariance violations can hinder this low-energy percolation. While such protection mechanism was previously considered in the literature, we provide here a simple illustration of how it works and of its general features. Finally, we consider a case in which dissipation is present, showing that the dissipative behaviour does not percolate generically to lower mass dimension operators albeit dispersion does. Moreover, we show that a scale separation can protect from unsuppressed low-energy percolation also in this case.
Revisiting energy efficiency fundamentals
Energy Technology Data Exchange (ETDEWEB)
Perez-Lombard, L.; Velazquez, D. [Grupo de Termotecnia, Escuela Superior de Ingenieros, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Seville (Spain); Ortiz, J. [Building Research Establishment (BRE), Garston, Watford, WD25 9XX (United Kingdom)
2013-05-15
Energy efficiency is a central target for energy policy and a keystone to mitigate climate change and to achieve a sustainable development. Although great efforts have been carried out during the last four decades to investigate the issue, focusing into measuring energy efficiency, understanding its trends and impacts on energy consumption and to design effective energy efficiency policies, many energy efficiency-related concepts, some methodological problems for the construction of energy efficiency indicators (EEI) and even some of the energy efficiency potential gains are often ignored or misunderstood, causing no little confusion and controversy not only for laymen but even for specialists. This paper aims to revisit, analyse and discuss some efficiency fundamental topics that could improve understanding and critical judgement of efficiency stakeholders and that could help in avoiding unfounded judgements and misleading statements. Firstly, we address the problem of measuring energy efficiency both in qualitative and quantitative terms. Secondly, main methodological problems standing in the way of the construction of EEI are discussed, and a sequence of actions is proposed to tackle them in an ordered fashion. Finally, two key topics are discussed in detail: the links between energy efficiency and energy savings, and the border between energy efficiency improvement and renewable sources promotion.
Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks
Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.
2017-01-01
Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under
Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks.
Naveros, Francisco; Garrido, Jesus A; Carrillo, Richard R; Ros, Eduardo; Luque, Niceto R
2017-01-01
Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under
Ingram, A L; Parker, A R
2008-07-27
The photonic structures of butterfly wings are among the most anatomically diverse of all those in nature, giving rise to an unrivalled display of structural colours. These have recently become the focus of research by workers in a variety of disciplines, stimulated by their potential applications to technology ('biomimetics'). This interest, together with the discovery of unpublished electron micrographs taken by the late Dr John Huxley (Natural History Museum, London), prompted this review of butterfly photonics in general. The current work provides a synopsis of the literature to date, covering the diversity and evolution of these optical structures and incorporating Huxley's work, which represents an important biomimetic and evolutionary database on its own. This review deals with butterfly photonic devices according to the parts of the butterfly scales on which they occur. In this way, the information is ripe for evolutionary study.
Benjamin Franklin and Mesmerism, revisited.
McConkey, Kevin M; Perry, Campbell
2002-10-01
The authors revisit and update their previous historiographical note (McConkey & Perry, 1985) on Benjamin Franklin's involvement with and investigation of animal magnetism or mesmerism. They incorporate more recent literature and offer additional comment about Franklin's role in and views about mesmerism. Franklin had a higher degree of personal involvement with and a more detailed opinion of mesmerism than has been previously appreciated.
Leadership and Management Theories Revisited
DEFF Research Database (Denmark)
Madsen, Mona Toft
2001-01-01
The goal of the paper is to revisit and analyze key contributions to the understanding of leadership and management. As a part of the discussion a role perspective that allows for additional and/or integrated leader dimensions, including a change-centered, will be outlined. Seemingly, a major...
A remote coal deposit revisited
DEFF Research Database (Denmark)
Bojesen-Kofoed, Jørgen A.; Kalkreuth, Wolfgang; Petersen, Henrik I.
2012-01-01
In 1908, members of the “Danmark Expedition” discovered a coal deposit in a very remote area in western Germania Land, close to the margin of the inland ice in northeast Greenland. The deposit was, however, neither sampled nor described, and was revisited in 2009 for the first time since its disc...
Revisiting Inter-Genre Similarity
DEFF Research Database (Denmark)
Sturm, Bob L.; Gouyon, Fabien
2013-01-01
We revisit the idea of ``inter-genre similarity'' (IGS) for machine learning in general, and music genre recognition in particular. We show analytically that the probability of error for IGS is higher than naive Bayes classification with zero-one loss (NB). We show empirically that IGS does...
ORAL GLUCOSE TOLERANCE TEST REVISITED
African Journals Online (AJOL)
Determinant for the usefulness or otherwise of oral glucose tolerance test for the diagnosis ... personnel, poverty and poor economic management, 8'9 that are known to .... Symptoms of diabetes plus casual plasma glucose ... WHO 2-hr plasma glucose criteria of 1l.1mmol/L .... Diagnostic criteria and performance revisited.
Indian Academy of Sciences (India)
H Kheiri; M R Moghaddam; V Vafaei
2011-06-01
In this work, we present travelling wave solutions for the Burgers, Burgers–Huxley and modiﬁed Burgers–KdV equations. The (′/)-expansion method is used to determine travelling wave solutions of these sets of equations. The travelling wave solutions are expressed by the hyperbolic functions, the trigonometric functions and the rational functions. It is shown that the proposed method is direct, effective and can be used for many other nonlinear evolution equations in mathematical physics.
Burns, J. A.; Sharma, I.
2000-10-01
Motivated by the recent detection of complex rotational states for several asteroids and comets, as well as by the ongoing and planned spacecraft missions to such bodies, which should allow their rotational states to be accurately determined, we revisit the problem of the nutational damping of small solar system bodies. The nutational damping of asteroids has been approximately analyzed by Prendergast (1958), Burns and Safronov (1973), and Efroimsky and Lazarian (2000). Many other similar dynamical studies concern planetary wobble decay (e.g., Peale 1973; Yoder and Ward 1979), interstellar dust grain alignment (e.g., Purcell 1979; Lazarian and Efroimsky 1999) and damping of Earth's Chandler wobble (Lambeck 1980). Recall that rotational energy loss for an isolated body aligns the body's angular momentum vector with its axis of maximum inertia. Assuming anelastic dissipation, simple dimensional analysis determines a functional form of the damping timescale, on which all the above authors agree. However, the numerical coefficients of published results are claimed to differ by orders of magnitude. Differences have been ascribed to absent physics, to solutions that fail to satisfy boundary conditions perfectly, and to unphysical choices for the Q parameter. The true reasons for the discrepancy are unclear since, despite contrary claims, the full 3D problem (nutational damping of an anelastic ellipsoid) is analytically intractable so far. To move the debate forward, we compare the solution of a related 2D problem to the expressions found previously, and we present results from a finite element model. On this basis, we feel that previous rates for the decay of asteroidal tumbling (Harris 1994), derived from Burns and Safronov (1973), are likely to be accurate, at least to a factor of a few. Funded by NASA.
A Survey of Neural Front End Amplifiers and Their Requirements toward Practical Neural Interfaces
Directory of Open Access Journals (Sweden)
Eric Bharucha
2014-11-01
Full Text Available When designing an analog front-end for neural interfacing, it is hard to evaluate the interplay of priority features that one must upkeep. Given the competing nature of design requirements for such systems a good understanding of these trade-offs is necessary. Low power, chip size, noise control, gain, temporal resolution and safety are the salient ones. There is a need to expose theses critical features for high performance neural amplifiers as the density and performance needs of these systems increases. This review revisits the basic science behind the engineering problem of extracting neural signal from living tissue. A summary of architectures and topologies is then presented and illustrated through a rich set of examples based on the literature. A survey of existing systems is presented for comparison based on prevailing performance metrics.
Wang, Qing-Yun; Zheng, Yan-Hong
2011-12-01
In this paper, we investigate the evolution of spatiotemporal patterns and synchronization transitions in dependence on the information transmission delay and ion channel blocking in scale-free neuronal networks. As the underlying model of neuronal dynamics, we use the Hodgkin-Huxley equations incorporating channel blocking and intrinsic noise. It is shown that delays play a significant yet subtle role in shaping the dynamics of neuronal networks. In particular, regions of irregular and regular propagating excitatory fronts related to the synchronization transitions appear intermittently as the delay increases. Moreover, the fraction of working sodium and potassium ion channels can also have a significant impact on the spatiotemporal dynamics of neuronal networks. As the fraction of blocked sodium channels increases, the frequency of excitatory events decreases, which in turn manifests as an increase in the neuronal synchrony that, however, is dysfunctional due to the virtual absence of large-amplitude excitations. Expectedly, we also show that larger coupling strengths improve synchronization irrespective of the information transmission delay and channel blocking. The presented results are also robust against the variation of the network size, thus providing insights that could facilitate understanding of the joint impact of ion channel blocking and information transmission delay on the spatiotemporal dynamics of neuronal networks.
Hernández, Oscar E; Zurek, Eduardo E
2013-05-15
We present a software tool called SENB, which allows the geometric and biophysical neuronal properties in a simple computational model of a Hodgkin-Huxley (HH) axon to be changed. The aim of this work is to develop a didactic and easy-to-use computational tool in the NEURON simulation environment, which allows graphical visualization of both the passive and active conduction parameters and the geometric characteristics of a cylindrical axon with HH properties. The SENB software offers several advantages for teaching and learning electrophysiology. First, SENB offers ease and flexibility in determining the number of stimuli. Second, SENB allows immediate and simultaneous visualization, in the same window and time frame, of the evolution of the electrophysiological variables. Third, SENB calculates parameters such as time and space constants, stimuli frequency, cellular area and volume, sodium and potassium equilibrium potentials, and propagation velocity of the action potentials. Furthermore, it allows the user to see all this information immediately in the main window. Finally, with just one click SENB can save an image of the main window as evidence. The SENB software is didactic and versatile, and can be used to improve and facilitate the teaching and learning of the underlying mechanisms in the electrical activity of an axon using the biophysical properties of the squid giant axon.
Vaccaro, S. R.
2016-11-01
The Na+ current in nerve and muscle membranes may be described in terms of the activation variable m (t ) and the inactivation variable h (t ) , which are dependent on the transitions of S4 sensors of each of the Na+ channel domains DI to DIV. The time-dependence of the Na+ current and the rate equations satisfied by m (t ) and h (t ) may be derived from the solution to a master equation that describes the coupling between two or three activation sensors regulating the Na+ channel conductance and a two-stage inactivation process. If the inactivation rate from the closed or open states increases as the S4 sensors activate, a more general form of the Hodgkin-Huxley expression for the open-state probability may be derived where m (t ) is dependent on both activation and inactivation processes. The voltage dependence of the rate functions for inactivation and recovery from inactivation are consistent with the empirically determined expressions and exhibit saturation for both depolarized and hyperpolarized clamp potentials.
Ding, Shaojie; Qian, Min; Qian, Hong; Zhang, Xuejuan
2016-12-01
The stochastic Hodgkin-Huxley model is one of the best-known examples of piecewise deterministic Markov processes (PDMPs), in which the electrical potential across a cell membrane, V(t), is coupled with a mesoscopic Markov jump process representing the stochastic opening and closing of ion channels embedded in the membrane. The rates of the channel kinetics, in turn, are voltage-dependent. Due to this interdependence, an accurate and efficient sampling of the time evolution of the hybrid stochastic systems has been challenging. The current exact simulation methods require solving a voltage-dependent hitting time problem for multiple path-dependent intensity functions with random thresholds. This paper proposes a simulation algorithm that approximates an alternative representation of the exact solution by fitting the log-survival function of the inter-jump dwell time, H(t), with a piecewise linear one. The latter uses interpolation points that are chosen according to the time evolution of the H(t), as the numerical solution to the coupled ordinary differential equations of V(t) and H(t). This computational method can be applied to all PDMPs. Pathwise convergence of the approximated sample trajectories to the exact solution is proven, and error estimates are provided. Comparison with a previous algorithm that is based on piecewise constant approximation is also presented.
Yu, Haitao; Galán, Roberto F.; Wang, Jiang; Cao, Yibin; Liu, Jing
2017-04-01
The random transitions of ion channels between open and closed states are a major source of noise in neurons. In this study, we investigate the stochastic dynamics of a single Hodgkin-Huxley (HH) neuron with realistic, physiological channel noise, which depends on the channel number and the voltage potential of the membrane. Without external input, the stochastic HH model can generate spontaneous spikes induced by ion-channel noise, and the variability of inter-spike intervals attains a minimum for an optimal membrane area, a phenomenon known as coherence resonance. When a subthreshold periodic input current is added, the neuron can optimally detect the input frequency for an intermediate membrane area, corresponding to the phenomenon of stochastic resonance. We also investigate spike timing reliability of neuronal responses to repeated presentations of the same stimulus with different realizations of channel noise. We show that, with increasing membrane area, the reliability of neuronal response decreases for subthreshold periodic inputs, and attains a minimum for suprathreshold inputs. Furthermore, Arnold tongues of high reliability arise in a two-dimensional plot of frequency and amplitude of the sinusoidal input current, resulting from the resonance effect of spike timing reliability.
Guo, Xinmeng; Wang, Jiang; Liu, Jing; Yu, Haitao; Galán, Roberto F.; Cao, Yibin; Deng, Bin
2017-02-01
Channel noise, which is generated by the random transitions of ion channels between open and closed states, is distinguished from external sources of physiological variability such as spontaneous synaptic release and stimulus fluctuations. This inherent stochasticity in ion-channel current can lead to variability of the timing of spikes occurring both spontaneously and in response to stimuli. In this paper, we investigate how intrinsic channel noise affects the response of stochastic Hodgkin-Huxley (HH) neuron to external fluctuating inputs with different amplitudes and correlation time. It is found that there is an optimal correlation time of input fluctuations for the maximal spiking coherence, where the input current has a fluctuating rate approximately matching the inherent oscillation of stochastic HH model and plays a dominating role in the timing of spike firing. We also show that the reliability of spike timing in the model is very sensitive to the properties of the current input. An optimal time scale of input fluctuations exists to induce the most reliable firing. The channel-noise-induced unreliability can be mostly overridden by injecting a fluctuating current with an appropriate correlation time. The spiking coherence and reliability can also be regulated by the size of channel stochasticity. As the membrane area (or total channel number) of the neuron increases, the spiking coherence decreases but the spiking reliability increases.
Bigman, Fran
2016-12-01
Accounts that take Aldous Huxley's Brave New World (1932) as representative of interwar reproductive dystopia fail to recognise that the novel expresses both an interest and an anxiety about the possibility of new reproductive technologies to transform sex, gender, and the family that were widely shared by writers in different genres and perhaps expressed best by those likely to be most affected: women. This article explores three earlier works-Charlotte Haldane's Man's World (1926), Vera Brittain's Halcyon, or the Future of Monogamy (1929), and Naomi Mitchison's Comments on Birth Control (1930)-in which pregnancy, instead of figuring as illness or debility, becomes a form of resistance to the status quo. These works engage with biomedicine, however, rather than abjuring it. Through a reading of these works, this article argues that the intersection of medical humanities and science fiction (SF) can enrich both: medical humanities can push SF to go beyond the canon, and SF can challenge any characterisation of literature in the medical humanities as purely fantastical by demonstrating how it responds to the hopes and anxieties of a particular time. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Institute of Scientific and Technical Information of China (English)
Qing-Yun Wang; Yan-Hong Zheng
2011-01-01
In this paper,we investigate the evolution of spatiotemporal patterns and synchronization transitions in dependence on the information transmission delay and ion channel blocking in scale-free neuronal networks.As the underlying model of neuronal dynamics,we use the HodgkinHuxley equations incorporating channel blocking and intrinsic noise.It is shown that delays play a significant yet subtle role in shaping the dynamics of neuronal networks.In particular,regions of irregular and regular propagating excitatory fronts related to the synchronization transitions appear intermittently as the delay increases.Moreover,the fraction of working sodium and potassium ion channels can also have a significant impact on the spatiotemporal dynamics of neuronal networks.As the fraction of blocked sodium channels increases,the frequency of excitatory events decreases,which in turn manifests as an increase in the neuronal synchrony that,however,is dysfunctional due to the virtual absence of large-amplitude excitations.Expectedly,we also show that larger coupling strengths improve synchronization irrespective of the information transmission delay and channel blocking.The presented results are also robust against the variation of the network size,thus providing insights that could facilitate understanding of the joint impact of ion channel blocking and information transmission delay on the spatiotemporal dynamics of neuronal networks.
一类Hodgkin-Huxley模型的分支研究%Bifurcation Analysis of a Hodgkin-Huxley-Type Model
Institute of Scientific and Technical Information of China (English)
李敏; 刘宣亮; 刘深泉
2013-01-01
This paper consider the Hodgkin-Huxley model in muscels, by using the bifurcation theory of differential equations and mumerical simulation, we discuss the one-parameter and two-parameter bifurcations of the model. The Bogdanov-Takens bifurcation are also discussed. We obtain the saddle-node bifurcation curve, the Hopf bifurcation curve and the Homoclinic bifurcation curve near the Bogdanov-Takens point.%考虑一类描述肌细胞膜电位变化的Hodgkin-Huxley模型的分支问题.利用常微分方程的分支理论,结合数值模拟结果,对模型的单参数分支与双参数分支进行了讨论.分析了Bogdanov-Takens分支,得到了相应的鞍结点分支曲线, Hopf分支曲线与同宿分支曲线.
Vaccaro, S R
2016-11-01
The Na^{+} current in nerve and muscle membranes may be described in terms of the activation variable m(t) and the inactivation variable h(t), which are dependent on the transitions of S4 sensors of each of the Na^{+} channel domains DI to DIV. The time-dependence of the Na^{+} current and the rate equations satisfied by m(t) and h(t) may be derived from the solution to a master equation that describes the coupling between two or three activation sensors regulating the Na^{+} channel conductance and a two-stage inactivation process. If the inactivation rate from the closed or open states increases as the S4 sensors activate, a more general form of the Hodgkin-Huxley expression for the open-state probability may be derived where m(t) is dependent on both activation and inactivation processes. The voltage dependence of the rate functions for inactivation and recovery from inactivation are consistent with the empirically determined expressions and exhibit saturation for both depolarized and hyperpolarized clamp potentials.
Ding, Shaojie; Qian, Min; Qian, Hong; Zhang, Xuejuan
2016-12-28
The stochastic Hodgkin-Huxley model is one of the best-known examples of piecewise deterministic Markov processes (PDMPs), in which the electrical potential across a cell membrane, V(t), is coupled with a mesoscopic Markov jump process representing the stochastic opening and closing of ion channels embedded in the membrane. The rates of the channel kinetics, in turn, are voltage-dependent. Due to this interdependence, an accurate and efficient sampling of the time evolution of the hybrid stochastic systems has been challenging. The current exact simulation methods require solving a voltage-dependent hitting time problem for multiple path-dependent intensity functions with random thresholds. This paper proposes a simulation algorithm that approximates an alternative representation of the exact solution by fitting the log-survival function of the inter-jump dwell time, H(t), with a piecewise linear one. The latter uses interpolation points that are chosen according to the time evolution of the H(t), as the numerical solution to the coupled ordinary differential equations of V(t) and H(t). This computational method can be applied to all PDMPs. Pathwise convergence of the approximated sample trajectories to the exact solution is proven, and error estimates are provided. Comparison with a previous algorithm that is based on piecewise constant approximation is also presented.
Energy Technology Data Exchange (ETDEWEB)
Ozer, Mahmut [Zonguldak Karaelmas University, Engineering Faculty, Department of Electrical and Electronics Engineering, 67100 Zonguldak (Turkey); Laboratory of Neurophysics and Physiology, UMR 8119 CNRS, Universite Paris Descartes, 45 rue des Saint-Peres, 75006 Paris (France)], E-mail: mahmutozer2002@yahoo.com; Uzuntarla, Muhammet [Zonguldak Karaelmas University, Engineering Faculty, Department of Electrical and Electronics Engineering, 67100 Zonguldak (Turkey); Kayikcioglu, Temel [Karadeniz Technical University, Department of Electrical and Electronics Engineering, Trabzon (Turkey); Graham, Lyle J. [Laboratory of Neurophysics and Physiology, UMR 8119 CNRS, Universite Paris Descartes, 45 rue des Saint-Peres, 75006 Paris (France)
2008-10-20
We study the collective temporal coherence of a small-world network of coupled stochastic Hodgkin-Huxley neurons. Previous reports have shown that network coherence in response to a subthreshold periodic stimulus, thus subthreshold signal encoding, is maximal for a specific range of the fraction of randomly added shortcuts relative to all possible shortcuts, p, added to an initially locally connected network. We investigated this behavior further as a function of channel noise, stimulus frequency and coupling strength. We show that temporal coherence peaks when the frequency of the external stimulus matches that of the intrinsic subthreshold oscillations. We also find that large values of the channel noise, corresponding to small cell sizes, increases coherence for optimal values of the stimulus frequency and the topology parameter p. For smaller values of the channel noise, thus larger cell sizes, network coherence becomes insensitive to these parameters. Finally, the degree of coupling between neurons in the network modulates the sensitivity of coherence to topology, such that for stronger coupling the peak coherence is achieved with fewer added short cuts.
Moresi, Louis
2015-04-01
Dynamic Topography Revisited Dynamic topography is usually considered to be one of the trinity of contributing causes to the Earth's non-hydrostatic topography along with the long-term elastic strength of the lithosphere and isostatic responses to density anomalies within the lithosphere. Dynamic topography, thought of this way, is what is left over when other sources of support have been eliminated. An alternate and explicit definition of dynamic topography is that deflection of the surface which is attributable to creeping viscous flow. The problem with the first definition of dynamic topography is 1) that the lithosphere is almost certainly a visco-elastic / brittle layer with no absolute boundary between flowing and static regions, and 2) the lithosphere is, a thermal / compositional boundary layer in which some buoyancy is attributable to immutable, intrinsic density variations and some is due to thermal anomalies which are coupled to the flow. In each case, it is difficult to draw a sharp line between each contribution to the overall topography. The second definition of dynamic topography does seem cleaner / more precise but it suffers from the problem that it is not measurable in practice. On the other hand, this approach has resulted in a rich literature concerning the analysis of large scale geoid and topography and the relation to buoyancy and mechanical properties of the Earth [e.g. refs 1,2,3] In convection models with viscous, elastic, brittle rheology and compositional buoyancy, however, it is possible to examine how the surface topography (and geoid) are supported and how different ways of interpreting the "observable" fields introduce different biases. This is what we will do. References (a.k.a. homework) [1] Hager, B. H., R. W. Clayton, M. A. Richards, R. P. Comer, and A. M. Dziewonski (1985), Lower mantle heterogeneity, dynamic topography and the geoid, Nature, 313(6003), 541-545, doi:10.1038/313541a0. [2] Parsons, B., and S. Daly (1983), The
Enceladus' tidal dissipation revisited
Tobie, Gabriel; Behounkova, Marie; Choblet, Gael; Cadek, Ondrej; Soucek, Ondrej
2016-10-01
A series of chemical and physical evidence indicates that the intense activity at Enceladus' South Pole is related to a subsurface salty water reservoir underneath the tectonically active ice shell. The detection of a significant libration implies that this water reservoir is global and that the average ice shell thickness is about 20-25km (Thomas et al. 2016). The interpretation of gravity and topography data further predicts large variations in ice shell thickness, resulting in a shell potentially thinner than 5 km in the South Polar Terrain (SPT) (Cadek et al. 2016). Such an ice shell structure requires a very strong heat source in the interior, with a focusing mechanism at the SPT. Thermal diffusion through the ice shell implies that at least 25-30 GW is lost into space by passive diffusion, implying a very efficient dissipation mechanism in Enceladus' interior to maintain such an ocean/ice configuration thermally stable.In order to determine in which conditions such a large dissipation power may be generated, we model the tidal response of Enceladus including variable ice shell thickness. For the rock core, we consider a wide range of rheological parameters representative of water-saturated porous rock materials. We demonstrate that the thinning toward the South Pole leads to a strong increase in heat production in the ice shell, with a optimal thickness obtained between 1.5 and 3 km, depending on the assumed ice viscosity. Our results imply that the heat production in the ice shell within the SPT may be sufficient to counterbalance the heat loss by diffusion and to power eruption activity. However, outside the SPT, a strong dissipation in the porous core is required to counterbalance the diffusive heat loss. We show that about 20 GW can be generated in the core, for an effective viscosity of 1012 Pa.s, which is comparable to the effective viscosity estimated in water-saturated glacial tills on Earth. We will discuss the implications of this revisited tidal
Remembered Experiences and Revisit Intentions
DEFF Research Database (Denmark)
Barnes, Stuart; Mattsson, Jan; Sørensen, Flemming
2016-01-01
Tourism is an experience-intensive sector in which customers seek and pay for experiences above everything else. Remembering past tourism experiences is also crucial for an understanding of the present, including the predicted behaviours of visitors to tourist destinations. We adopt a longitudinal...... approach to memory data collection from psychological science, which has the potential to contribute to our understanding of tourist behaviour. In this study, we examine the impact of remembered tourist experiences in a safari park. In particular, using matched survey data collected longitudinally and PLS...... path modelling, we examine the impact of positive affect tourist experiences on the development of revisit intentions. We find that longer-term remembered experiences have the strongest impact on revisit intentions, more so than predicted or immediate memory after an event. We also find that remembered...
The Damped String Problem Revisited
Gesztesy, Fritz
2010-01-01
We revisit the damped string equation on a compact interval with a variety of boundary conditions and derive an infinite sequence of trace formulas associated with it, employing methods familiar from supersymmetric quantum mechanics. We also derive completeness and Riesz basis results (with parentheses) for the associated root functions under less smoothness assumptions on the coefficients than usual, using operator theoretic methods (rather than detailed eigenvalue and root function asymptotics) only.
Zuber, Jean-Bernard
2016-01-01
In this note, I revisit integrals over $\\SU(N)$ of the form $ \\int DU\\, U_{i_1j_1}\\cdots U_{i_pj_p}\\Ud_{k_1l_1}\\cdots \\Ud_{k_nl_n}$. While the case $p=n$ is well known, it seems that explicit expressions for $p=n+N$ had not appeared in the literature. Similarities and differences, in particular in the large $N$ limit, between the two cases are discussed
Star\\/Galaxy Separation Revisited Into the Zone of Avoidance
Naim, A
1997-01-01
The problem of automated separation of stars and galaxies on photographic plates is revisited with two goals in mind : First, to separate galaxies from everything else (as opposed to most previous work, in which galaxies were lumped together with all other non-stellar images). And second, to search optically for galaxies at low Galactic latitudes (an area that has been largely avoided in the past). This paper demonstrates how an artificial neural network can be trained to achieve both goals on Schmidt plates of the Digitised Sky Survey. Here I present the method while its application to large numbers of plates is deferred to a later paper. Analysis is also provided of the way in which the network operates and the results are used to counter claims that it is a complicated and incomprehensible tool.
Baladron, Javier; Fasoli, Diego; Faugeras, Olivier; Touboul, Jonathan
2012-05-31
We derive the mean-field equations arising as the limit of a network of interacting spiking neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number of populations and are represented either by the Hodgkin-Huxley model or by one of its simplified version, the FitzHugh-Nagumo model. The synapses between neurons are either electrical or chemical. The network is assumed to be fully connected. The maximum conductances vary randomly. Under the condition that all neurons' initial conditions are drawn independently from the same law that depends only on the population they belong to, we prove that a propagation of chaos phenomenon takes place, namely that in the mean-field limit, any finite number of neurons become independent and, within each population, have the same probability distribution. This probability distribution is a solution of a set of implicit equations, either nonlinear stochastic differential equations resembling the McKean-Vlasov equations or non-local partial differential equations resembling the McKean-Vlasov-Fokker-Planck equations. We prove the well-posedness of the McKean-Vlasov equations, i.e. the existence and uniqueness of a solution. We also show the results of some numerical experiments that indicate that the mean-field equations are a good representation of the mean activity of a finite size network, even for modest sizes. These experiments also indicate that the McKean-Vlasov-Fokker-Planck equations may be a good way to understand the mean-field dynamics through, e.g. a bifurcation analysis.Mathematics Subject Classification (2000): 60F99, 60B10, 92B20, 82C32, 82C80, 35Q80.
Vaccaro, S R
2014-11-01
The activation of a K^{+} channel sensor in two sequential stages during a voltage clamp may be described as the translocation of a Brownian particle in an energy landscape with two large barriers between states. A solution of the Smoluchowski equation for a square-well approximation to the potential function of the S4 voltage sensor satisfies a master equation and has two frequencies that may be determined from the forward and backward rate functions. When the higher-frequency terms have small amplitude, the solution reduces to the relaxation of a rate equation, where the derived two-state rate functions are dependent on the relative magnitude of the forward rates (α and γ) and the backward rates (β and δ) for each stage. In particular, the voltage dependence of the Hodgkin-Huxley rate functions for a K^{+} channel may be derived by assuming that the rate functions of the first stage are large relative to those of the second stage-α≫γ and β≫δ. For a Shaker IR K^{+} channel, the first forward and backward transitions are rate limiting (αchannel and a noninactivating Na^{+} ion channel is determined by the master equation for K^{+} channel activation and the ionic current equation when the Na^{+} channel activation time is small, and if β≪δ and α≪γ, the system may exhibit a small amplitude oscillation between spikes, or mixed-mode oscillation, in which the slow closed state modulates the K^{+} ion channel conductance in the membrane.
Vaccaro, S. R.
2014-11-01
The activation of a K+channel sensor in two sequential stages during a voltage clamp may be described as the translocation of a Brownian particle in an energy landscape with two large barriers between states. A solution of the Smoluchowski equation for a square-well approximation to the potential function of the S4 voltage sensor satisfies a master equation and has two frequencies that may be determined from the forward and backward rate functions. When the higher-frequency terms have small amplitude, the solution reduces to the relaxation of a rate equation, where the derived two-state rate functions are dependent on the relative magnitude of the forward rates (α and γ ) and the backward rates (β and δ ) for each stage. In particular, the voltage dependence of the Hodgkin-Huxley rate functions for a K+channel may be derived by assuming that the rate functions of the first stage are large relative to those of the second stage—α ≫γ and β ≫δ . For a Shaker IR K+ channel, the first forward and backward transitions are rate limiting (α <γ and δ ≪β ), and for an activation process with either two or three stages, the derived two-state rate functions also have a voltage dependence that is of a similar form to that determined for the squid axon. The potential variation generated by the interaction between a two-stage K+ ion channel and a noninactivating Na+ ion channel is determined by the master equation for K+channel activation and the ionic current equation when the Na+channel activation time is small, and if β ≪δ and α ≪γ , the system may exhibit a small amplitude oscillation between spikes, or mixed-mode oscillation, in which the slow closed state modulates the K+ ion channel conductance in the membrane.
Tagluk, M Emin; Tekin, Ramazan
2014-08-01
Action potentials (APs) in the form of very short pulses arise when the cell is excited by any internal or external stimulus exceeding the critical threshold of the membrane. During AP generation, the membrane potential completes its natural cycle through typical phases that can be formatted by ion channels, gates and ion concentrations, as well as the synaptic excitation rate. On the basis of the Hodgkin-Huxley cell model, a cortical network consistent with the real anatomic structure is realized with randomly interrelated small population of neurons to simulate a cerebral cortex segment. Using this model, we investigated the effects of Na(+) and K(+) ion concentrations on the outcome of this network in terms of regularity, phase locking, and synchronization. The results suggested that Na(+) concentration does slightly affect the amplitude but not considerably affects the other parameters specified by depolarization and repolarization. K(+) concentration significantly influences the form, regularity, and synchrony of the network-generated APs. No previous study dealing directly with the effects of both Na(+) and K(+) ion concentrations on regularity and synchronization of the simulated cortical network-generated APs, allowing for the comparison of results obtained using our methods, was encountered in the literature. The results, however, were consistent with those obtained through studies concerning resonance and synchronization from another perspective and with the information revealed through physiological and pharmacological experiments concerning changing ion concentrations or blocking ion channels. Our results demonstrated that the regularity and reliability of brain functions have a strong relationship with cellular ion concentrations, and suggested the management of the dynamic behavior of the cellular network with ion concentrations.
Indian Academy of Sciences (India)
Jalil Manafian; Mehrdad Lakestani
2015-07-01
An application of the (′/)-expansion method to search for exact solutions of nonlinear partial differential equations is analysed. This method is used for Burgers, Fisher, Huxley equations and combined forms of these equations. The (′/)-expansion method was used to construct periodic wave and solitary wave solutions of nonlinear evolution equations. This method is developed for searching exact travelling wave solutions of nonlinear partial differential equations. It is shown that the (′/)-expansion method, with the help of symbolic computation, provides a straightforward and powerful mathematical tool for solving nonlinear partial differential equations.
Rebelo, Maria Raquel de Gouveia Durão Pina
1999-01-01
A presente dissertação apresenta, num primeiro momento, um estudo dos estereótipos do Ameríndio - nomeadamente o Bom-Selvagem e o canibal feroz e amoral -, formados pela mente branca europeia e americana numa atitude de contraponto entre culturas. Este estudo, baseado em textos representativos de várias épocas, serve de base à deconstrucção satírica que aldous Huxley faz desses estereótipos e à subversão das categorias discursivas oposicionais nas quais eles assentam e que levaram à distinção...
Directory of Open Access Journals (Sweden)
William R.G. Loader
2011-06-01
Full Text Available This article revisited the issue of Jesus’ attitude towards the Torah on the basis of a critical discussion of the most recent extensive treatment of the theme by Meier in his A marginal Jew: Rethinking the historical Jesus: Volume four: Law and love (2009. It engaged Meier’s contribution in the light of contemporary research, concluding that, whilst Meier provided an erudite analysis, his thesis that Jesus’ teaching on divorce and oaths revoked Mosaic law did not convince, for it did not adequately consider the extent to which the contemporary interpretation of the Torah could encompass such radicalisation.
McLean's second variation formula revisited
Lê, Hông Vân; Vanžura, Jiří
2017-03-01
We revisit McLean's second variation formulas for calibrated submanifolds in exceptional geometries, and correct his formulas concerning associative submanifolds and Cayley submanifolds, using a unified treatment based on the (relative) calibration method and Harvey-Lawson's identities.
Institute of Scientific and Technical Information of China (English)
刘玉华; 张金良; 李留涛
2012-01-01
广义Burgers—Huxley方程是一个非常重要的模型，在流体力学、化学反应、生物工程、自动控制等领域有着广泛的应用．借助于有限差分、对角隐式Runge—Kutta-NystrSm（DIRKN），对广义Burgers·Huxley方程的精确解进行了数值模拟，由模拟的图形及误差可以看出本文的方法是有效的，但是若方程的非线性较强时，数值结果的误差相对较大．%The generalized Burgers-Huxley equation is an important model, it has wide applications in fluid mechanics, chemical reaction, bioengineering, automatic control, etc. In this paper, the exact solutions of the generalized Burgers-Huxley equation are numerically simulated using the finite difference method and diagonal implicit Runge-Kutta-Nystrom method. From the simulation figures and errors, the method used in this paper is efficient, if the nonlinearity is strong, the error becomes bigger.
Directory of Open Access Journals (Sweden)
Schwindling Jerome
2010-04-01
Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.
The power reinforcement framework revisited
DEFF Research Database (Denmark)
Nielsen, Jeppe; Andersen, Kim Normann; Danziger, James N.
2016-01-01
Whereas digital technologies are often depicted as being capable of disrupting long-standing power structures and facilitating new governance mechanisms, the power reinforcement framework suggests that information and communications technologies tend to strengthen existing power arrangements within...... public organizations. This article revisits the 30-yearold power reinforcement framework by means of an empirical analysis on the use of mobile technology in a large-scale programme in Danish public sector home care. It explores whether and to what extent administrative management has controlled decision......-dominated and centrally controlled technologies that were the main focus of the 1970s and 1980s studies. Yet this study concludes that there is general support for the reinforcement framework in the contemporary application of mobile technology in public sector home care....
Orthopaedic service lines-revisited.
Patterson, Cheryl
2008-01-01
This article revisits the application of orthopaedic service lines from early introduction and growth of this organizational approach in the 1980s, through the 1990s, and into the current decade. The author has experienced and worked in various service-line structures through these three decades, as well as the preservice-line era of 1970s orthopaedics. Past lessons learned during earlier phases and then current trends and analysis by industry experts are summarized briefly, with indication given of the future for service lines. Variation versus consistency of certain elements in service-line definitions and in operational models is discussed. Main components of service-line structures and typical processes are described briefly, along with a more detailed section on the service-line director/manager role. Current knowledge contained here will help guide the reader to more "out-of-the-box" thinking toward comprehensive orthopaedic centers of excellence.
FGF Signaling Transforms Non-neural Ectoderm into Neural Crest
Yardley, Nathan; García-Castro, Martín I.
2012-01-01
The neural crest arises at the border between the neural plate and the adjacent non-neural ectoderm. It has been suggested that both neural and non-neural ectoderm can contribute to the neural crest. Several studies have examined the molecular mechanisms that regulate neural crest induction in neuralized tissues or the neural plate border. Here, using the chick as a model system, we address the molecular mechanisms by which non-neural ectoderm generates neural crest. We report that in respons...
Bashkirtseva, Irina; Neiman, Alexander B.; Ryashko, Lev
2015-05-01
We study the stochastic dynamics of a Hodgkin-Huxley neuron model in a regime of coexistent stable equilibrium and a limit cycle. In this regime, noise may suppress periodic firing by switching the neuron randomly to a quiescent state. We show that at a critical value of the injected current, the mean firing rate depends weakly on noise intensity, while the neuron exhibits giant variability of the interspike intervals and spike count. To reveal the dynamical origin of this noise-induced effect, we develop the stochastic sensitivity analysis and use the Mahalanobis metric for this four-dimensional stochastic dynamical system. We show that the critical point of giant variability corresponds to the matching of the Mahalanobis distances from attractors (stable equilibrium and limit cycle) to a three-dimensional surface separating their basins of attraction.
Bashkirtseva, Irina; Neiman, Alexander B; Ryashko, Lev
2015-05-01
We study the stochastic dynamics of a Hodgkin-Huxley neuron model in a regime of coexistent stable equilibrium and a limit cycle. In this regime, noise may suppress periodic firing by switching the neuron randomly to a quiescent state. We show that at a critical value of the injected current, the mean firing rate depends weakly on noise intensity, while the neuron exhibits giant variability of the interspike intervals and spike count. To reveal the dynamical origin of this noise-induced effect, we develop the stochastic sensitivity analysis and use the Mahalanobis metric for this four-dimensional stochastic dynamical system. We show that the critical point of giant variability corresponds to the matching of the Mahalanobis distances from attractors (stable equilibrium and limit cycle) to a three-dimensional surface separating their basins of attraction.
Vonk, E.; Jain, L.C.; Veelenturf, L.P.J.
1995-01-01
Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas
Revisiting tourist behavior via destination brand worldness
Directory of Open Access Journals (Sweden)
Murat Kayak
2016-11-01
Full Text Available Taking tourists’ perspective rather than destination offerings as its core concept, this study introduces “perceived destination brand worldness” as a variable. Perceived destination brand worldness is defined as the positive perception that a tourist has of a country that is visited by tourists from all over the world. Then, the relationship between perceived destination brand worldness and intention to revisit is analyzed using partial least squares regression. This empirical study selects Taiwanese tourists as its sample, and the results show that perceived destination brand worldness is a direct predictor of intention to revisit. In light of these empirical findings and observations, practical and theoretical implications are discussed.
Gravity current jump conditions, revisited
Ungarish, Marius; Hogg, Andrew J.
2016-11-01
Consider the flow of a high-Reynolds-number gravity current of density ρc in an ambient fluid of density ρa in a horizontal channel z ∈ [ 0 , H ] , with gravity in - z direction. The motion is often modeled by a two-layer formulation which displays jumps (shocks) in the height of the interface, in particular at the leading front of the dense layer. Various theoretical models have been advanced to predict the dimensionless speed of the jump, Fr = U /√{g' h } ; g' , h are reduced gravity and jump height. We revisit this problem and using the Navier-Stokes equations, integrated over a control volume embedding the jump, derive balances of mass and momentum fluxes. We focus on understanding the closures needed to complete this model and we show the vital need to understand the pressure head losses over the jump, which we show can be related to the vorticity fluxes at the boundaries of the control volume. Our formulation leads to two governing equations for three dimensionless quantities. Closure requires one further assumption, depending on which we demonstrate that previous models for gravity current fronts and internal bores can be recovered. This analysis yield new insights into existing results, and also provides constraints for potential new formulae.
Leukemia and ionizing radiation revisited
Energy Technology Data Exchange (ETDEWEB)
Cuttler, J.M. [Cuttler & Associates Inc., Vaughan, Ontario (Canada); Welsh, J.S. [Loyola University-Chicago, Dept. or Radiation Oncology, Stritch School of Medicine, Maywood, Illinois (United States)
2016-03-15
A world-wide radiation health scare was created in the late 19508 to stop the testing of atomic bombs and block the development of nuclear energy. In spite of the large amount of evidence that contradicts the cancer predictions, this fear continues. It impairs the use of low radiation doses in medical diagnostic imaging and radiation therapy. This brief article revisits the second of two key studies, which revolutionized radiation protection, and identifies a serious error that was missed. This error in analyzing the leukemia incidence among the 195,000 survivors, in the combined exposed populations of Hiroshima and Nagasaki, invalidates use of the LNT model for assessing the risk of cancer from ionizing radiation. The threshold acute dose for radiation-induced leukemia, based on about 96,800 humans, is identified to be about 50 rem, or 0.5 Sv. It is reasonable to expect that the thresholds for other cancer types are higher than this level. No predictions or hints of excess cancer risk (or any other health risk) should be made for an acute exposure below this value until there is scientific evidence to support the LNT hypothesis. (author)
The mycorrhiza helper bacteria revisited.
Frey-Klett, P; Garbaye, J; Tarkka, M
2007-01-01
In natural conditions, mycorrhizal fungi are surrounded by complex microbial communities, which modulate the mycorrhizal symbiosis. Here, the focus is on the so-called mycorrhiza helper bacteria (MHB). This concept is revisited, and the distinction is made between the helper bacteria, which assist mycorrhiza formation, and those that interact positively with the functioning of the symbiosis. After considering some examples of MHB from the literature, the ecological and evolutionary implications of the relationships of MHB with mycorrhizal fungi are discussed. The question of the specificity of the MHB effect is addressed, and an assessment is made of progress in understanding the mechanisms of the MHB effect, which has been made possible through the development of genomics. Finally, clear evidence is presented suggesting that some MHB promote the functioning of the mycorrhizal symbiosis. This is illustrated for three critical functions of practical significance: nutrient mobilization from soil minerals, fixation of atmospheric nitrogen, and protection of plants against root pathogens. The review concludes with discussion of future research priorities regarding the potentially very fruitful concept of MHB.
Revisiting separation properties of convex fuzzy sets
Separation of convex sets by hyperplanes has been extensively studied on crisp sets. In a seminal paper separability and convexity are investigated, however there is a flaw on the definition of degree of separation. We revisited separation on convex fuzzy sets that have level-wise (crisp) disjointne...
The Faraday effect revisited: General theory
DEFF Research Database (Denmark)
Cornean, Horia Decebal; Nenciu, Gheorghe; Pedersen, Thomas Garm
This paper is the first in a series revisiting the Faraday effect, or more generally, the theory of electronic quantum transport/optical response in bulk media in the presence of a constant magnetic field. The independent electron approximation is assumed. For free electrons, the transverse...
The Faraday effect revisited: General theory
DEFF Research Database (Denmark)
Cornean, Horia Decebal; Nenciu, Gheorghe; Pedersen, Thomas Garm
2006-01-01
This paper is the first in a series revisiting the Faraday effect, or more generally, the theory of electronic quantum transport/optical response in bulk media in the presence of a constant magnetic field. The independent electron approximation is assumed. At zero temperature and zero frequency...
The Future of Engineering Education--Revisited
Wankat, Phillip C.; Bullard, Lisa G.
2016-01-01
This paper revisits the landmark CEE series, "The Future of Engineering Education," published in 2000 (available free in the CEE archives on the internet) to examine the predictions made in the original paper as well as the tools and approaches documented. Most of the advice offered in the original series remains current. Despite new…
Revisiting Basic Counseling Skills with Children
Van Velsor, Patricia
2004-01-01
Counseling with children can be challenging for counselors whose training focused on adult clients. The purpose of this article is to offer information to counselors seeking to improve their skills with children, revisiting a topic discussed in an earlier Journal of Counseling & Development article by P. Erdman and R. Lampe (1996). Examples of…
Revisiting three intellectual pillars of monetary policy
National Research Council Canada - National Science Library
Borio, Claudio
2016-01-01
... not. More specifically, I would like to revisit and question three deeply held beliefs that underpin current monetary policy received wisdom. The first belief is that it is appropriate to define equilibrium (or natural) rates as those consistent with output at potential and with stable prices (inflation) in any given period--the so-called Wi...
Revisiting the Regenerative Possibilities of Ortiz
Duques, Matthew
2004-01-01
The author of this article revisits Simon Ortiz's poem, "From Sand Creek," in which the latter can in so few words convey both the horrific tragedy of conquest and colonization, while at the same time find a space for possibility, a means for recovery that is never about forgetting but always occurs as a kind of recuperative remembering. Ortiz…
Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.
Yu, T; Sejnowski, T J; Cauwenberghs, G
2011-10-01
We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.
Energy Technology Data Exchange (ETDEWEB)
Chavarette, Fabio Roberto [Department of Mechanical Design, State University of Campinas, 13083-970 Campinas, SP (Brazil); State University of Sao Paulo at Rio Claro, C.P. 178, 13500-230 Rio Claro, SP (Brazil); Balthazar, Jose Manoel [Department of Mechanical Design, State University of Campinas, 13083-970 Campinas, SP (Brazil); State University of Sao Paulo at Rio Claro, C.P. 178, 13500-230 Rio Claro, SP (Brazil)], E-mail: jmbaltha@rc.unesp.br; Rafikov, Marat [Universidade Regional do Noroeste do Estado do Rio Grande do Sul 98700-000, C.P. 560, Ijui, RS (Brazil); Hermini, Helder Anibal [Department of Mechanical Design, State University of Campinas, 13083-970 Campinas, SP (Brazil)
2009-02-28
In this paper, we have studied the plasmatic membrane behavior using an electric circuit developed by Hodgkin and Huxley in 1952 and have dealt with the variation of the amount of time related to the potassium and sodium conductances in the squid axon. They developed differential equations for the propagation of electric signals; the dynamics of the Hodgkin-Huxley model have been extensively studied both from the view point of its their biological implications and as a test bed for numerical methods, which can be applied to more complex models. Recently, an irregular chaotic movement of the action potential of the membrane was observed for a number of techniques of control with the objective to stabilize the variation of this potential. This paper analyzes the non-linear dynamics of the Hodgkin-Huxley mathematical model, and we present some modifications in the governing equations of the system in order to make it a non-ideal one (taking into account that the energy source has a limited power supply). We also developed an optimal linear control design for the action potential of membranes. Here, we discuss the conditions that allow the use of control linear feedback for this kind of non-linear system.
Neural Induction, Neural Fate Stabilization, and Neural Stem Cells
Directory of Open Access Journals (Sweden)
Sally A. Moody
2002-01-01
Full Text Available The promise of stem cell therapy is expected to greatly benefit the treatment of neurodegenerative diseases. An underlying biological reason for the progressive functional losses associated with these diseases is the extremely low natural rate of self-repair in the nervous system. Although the mature CNS harbors a limited number of self-renewing stem cells, these make a significant contribution to only a few areas of brain. Therefore, it is particularly important to understand how to manipulate embryonic stem cells and adult neural stem cells so their descendants can repopulate and functionally repair damaged brain regions. A large knowledge base has been gathered about the normal processes of neural development. The time has come for this information to be applied to the problems of obtaining sufficient, neurally committed stem cells for clinical use. In this article we review the process of neural induction, by which the embryonic ectodermal cells are directed to form the neural plate, and the process of neural�fate stabilization, by which neural plate cells expand in number and consolidate their neural fate. We will present the current knowledge of the transcription factors and signaling molecules that are known to be involved in these processes. We will discuss how these factors may be relevant to manipulating embryonic stem cells to express a neural fate and to produce large numbers of neurally committed, yet undifferentiated, stem cells for transplantation therapies.
Revisiting the 1761 Transatlantic Tsunami
Baptista, Maria Ana; Wronna, Martin; Miranda, Jorge Miguel
2016-04-01
The tsunami catalogs of the Atlantic include two transatlantic tsunamis in the 18th century the well known 1st November 1755 and the 31st March 1761. The 31st March 1761 earthquake struck Portugal, Spain, and Morocco. The earthquake occurred around noontime in Lisbon alarming the inhabitants and throwing down ruins of the past 1st November 1755 earthquake. According to several sources, the earthquake was followed by a tsunami observed as far as Cornwall (United Kingdom), Cork (Ireland) and Barbados (Caribbean). The analysis of macroseismic information and its compatibility with tsunami travel time information led to a source area close to the Ampere Seamount with an estimated epicenter circa 34.5°N 13°W. The estimated magnitude of the earthquake was 8.5. In this study, we revisit the tsunami observations, and we include a report from Cadiz not used before. We use the results of the compilation of the multi-beam bathymetric data, that covers the area between 34°N - 38°N and 12.5°W - 5.5°W and use the recent tectonic map published for the Southwest Iberian Margin to select among possible source scenarios. Finally, we use a non-linear shallow water model that includes the discretization and explicit leap-frog finite difference scheme to solve the shallow water equations in the spherical or Cartesian coordinate to compute tsunami waveforms and tsunami inundation and check the results against the historical descriptions to infer the source of the event. This study received funding from project ASTARTE- Assessment Strategy and Risk Reduction for Tsunamis in Europe a collaborative project Grant 603839, FP7-ENV2013 6.4-3
基于HH模型的心肌细胞电模型%Electric Model of the Myocardial Cell Based on Hodgkin-Huxley Model
Institute of Scientific and Technical Information of China (English)
张莹; 李智
2012-01-01
A modeling and simulation methods of electrophysiological model of myocardial cells were proposed. Based on the Hodg- kin-Huxley model, equivalent circuit model of the rat's single cardiac muscle cell was built. Using fourth-order Rouge-Kutta algorithm, internal and external cardiac membrane ionic current and potential difference changes has been researched and analyzed. Making use of C Language, the program of the cardiac cell membrane was realized like equivalent circuit model, and the computer's simulation through Mat-lab software platform was realized. As a result, it obtained the result of simulation experience of electrophysiological model of cardiac muscle cell under every different kinds of stimulation.%提出了一种心肌细胞电生理模型的建模仿真方法.通过借助Hodgkin-Huxley模型对单个心肌细胞建立细胞膜的等效电路模型,利用四阶Rouge-Kutta算法,研究并分析了心肌细胞膜内外离子电流及电位差变化.然后用C语言完成了对细胞膜等效电路模型的编程,利用Matlab软件平台进行了计算机仿真,得到了心肌细胞电生理学模型在不同刺激下的仿真实验结果.
Iterative learning control of synchronization of Hodgkin-Huxley neurons%Hodgkin-Huxley神经元同步的迭代学习控制
Institute of Scientific and Technical Information of China (English)
邓斌; 王晓军; 王江; 李会艳
2014-01-01
由于神经元模型和参数具有不确定性,加大了许多控制算法的应用难度,而迭代学习控制不需要精确的数学模型,因此适合神经元网络同步的控制.针对Hodgkin-Huxley(HH)神经元的同步控制问题,提出了基于PI型迭代学习控制算法.对四种不同情况下主从神经元同步控制进行仿真,结果表明,施加控制后从神经元能够迅速跟踪主神经元的动力学行为.研究结果证实了该控制算法的可行性和有效性.
Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut
2015-08-01
We investigate the effects of time-periodic coupling strength on the temporal coherence or firing regularity of a scale-free network consisting of stochastic Hodgkin-Huxley (H-H) neurons. The temporal coherence exhibits a resonance-like behavior depending on the cell size or the channel noise intensity. The best temporal coherence requires an optimal channel noise intensity, and this coherence can be significantly increased by time-periodic coupling strength when its frequency matches the integer multiples of the intrinsic subthreshold oscillation frequency of H-H neuron. Particularly, we find the multiple-coherence resonance depending on frequency of time-periodic coupling strength at the optimal noise intensity. We also obtain a resonance-like dependence of temporal coherence on the amplitude of time-periodic coupling strength. Additionally, we investigate the effects of average degree on the temporal coherence and find that the temporal coherence exhibits a resonance-like behavior with respect to the network average degree, indicating that the best regularity requires an optimal average degree.
Revisiting the Diffusion Problem in a Capillary Tube Geometry
Sullivan, Eric
2012-01-01
The present work revisits the problem of modeling diffusion above a stagnant liquid interface in a capillary tube geometry. In this revisitation we elucidate a misconception found in the classical model proposed by Bird et. al. Furthermore, we propose alternative explanations for thermally forced diffusion and provide a description of natural convection in the absence of forcing terms.
Hyperinflation in Brazil, Israel, and Nicaragua revisited
Szybisz, M A; Szybisz, L.
2016-01-01
The aim of this work is to address the description of hyperinflation regimes in economy. The spirals of hyperinflation developed in Brazil, Israel, and Nicaragua are revisited. This new analysis of data indicates that the episodes occurred in Brazil and Nicaragua can be understood within the frame of the model available in the literature, which is based on a nonlinear feedback (NLF) characterized by an exponent $\\beta>0$. In the NLF model the accumulated consumer price index carries a finite ...
Spine revisited: Principles and parlance redefined
Directory of Open Access Journals (Sweden)
Kothari M
2005-01-01
Full Text Available A revised appreciation of the evolution and the nature of bone in general and of vertebrae in particular, allows revisiting the human spine to usher in some new principles and more rational parlance, that embody spine′s phylogeny, ontogeny, anatomy and physiology. Such an approach accords primacy to spine′s soft-tissues, and relegates to its bones a secondary place.
The Actinide Transition Revisited by Gutzwiller Approximation
Xu, Wenhu; Lanata, Nicola; Yao, Yongxin; Kotliar, Gabriel
2015-03-01
We revisit the problem of the actinide transition using the Gutzwiller approximation (GA) in combination with the local density approximation (LDA). In particular, we compute the equilibrium volumes of the actinide series and reproduce the abrupt change of density found experimentally near plutonium as a function of the atomic number. We discuss how this behavior relates with the electron correlations in the 5 f states, the lattice structure, and the spin-orbit interaction. Our results are in good agreement with the experiments.
Revisiting Cementoblastoma with a Rare Case Presentation.
Subramani, Vijayanirmala; Narasimhan, Malathi; Ramalingam, Suganya; Anandan, Soumya; Ranganathan, Subhashini
2017-01-01
Cementoblastoma is a rare benign odontogenic neoplasm which is characterized by the proliferation of cellular cementum. Diagnosis of cementoblastoma is challenging because of its protracted clinical, radiographic features, and bland histological appearance; most often cementoblastoma is often confused with other cementum and bone originated lesions. The aim of this article is to overview/revisit, approach the diagnosis of cementoblastoma, and also present a unique radiographic appearance of a cementoblastoma lesion associated with an impacted tooth.
Revisiting Cementoblastoma with a Rare Case Presentation
Directory of Open Access Journals (Sweden)
Vijayanirmala Subramani
2017-01-01
Full Text Available Cementoblastoma is a rare benign odontogenic neoplasm which is characterized by the proliferation of cellular cementum. Diagnosis of cementoblastoma is challenging because of its protracted clinical, radiographic features, and bland histological appearance; most often cementoblastoma is often confused with other cementum and bone originated lesions. The aim of this article is to overview/revisit, approach the diagnosis of cementoblastoma, and also present a unique radiographic appearance of a cementoblastoma lesion associated with an impacted tooth.
Standing and travelling waves in a spherical brain model: The Nunez model revisited
Visser, S.; Nicks, R.; Faugeras, O.; Coombes, S.
2017-06-01
The Nunez model for the generation of electroencephalogram (EEG) signals is naturally described as a neural field model on a sphere with space-dependent delays. For simplicity, dynamical realisations of this model either as a damped wave equation or an integro-differential equation, have typically been studied in idealised one dimensional or planar settings. Here we revisit the original Nunez model to specifically address the role of spherical topology on spatio-temporal pattern generation. We do this using a mixture of Turing instability analysis, symmetric bifurcation theory, centre manifold reduction and direct simulations with a bespoke numerical scheme. In particular we examine standing and travelling wave solutions using normal form computation of primary and secondary bifurcations from a steady state. Interestingly, we observe spatio-temporal patterns which have counterparts seen in the EEG patterns of both epileptic and schizophrenic brain conditions.
Energy Technology Data Exchange (ETDEWEB)
Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)
1996-12-31
The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.
Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...
Chung-Ming Kuan
2006-01-01
Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods.
Constructive neural network learning
Lin, Shaobo; Zeng, Jinshan; Zhang, Xiaoqin
2016-01-01
In this paper, we aim at developing scalable neural network-type learning systems. Motivated by the idea of "constructive neural networks" in approximation theory, we focus on "constructing" rather than "training" feed-forward neural networks (FNNs) for learning, and propose a novel FNNs learning system called the constructive feed-forward neural network (CFN). Theoretically, we prove that the proposed method not only overcomes the classical saturation problem for FNN approximation, but also ...
BIALEK, W; RIEKE, F; VANSTEVENINCK, RRD; WARLAND, D
1991-01-01
Traditional approaches to neural coding characterize the encoding of known stimuli in average neural responses. Organisms face nearly the opposite task - extracting information about an unknown time-dependent stimulus from short segments of a spike train. Here the neural code was characterized from
Generalized classifier neural network.
Ozyildirim, Buse Melis; Avci, Mutlu
2013-03-01
In this work a new radial basis function based classification neural network named as generalized classifier neural network, is proposed. The proposed generalized classifier neural network has five layers, unlike other radial basis function based neural networks such as generalized regression neural network and probabilistic neural network. They are input, pattern, summation, normalization and output layers. In addition to topological difference, the proposed neural network has gradient descent based optimization of smoothing parameter approach and diverge effect term added calculation improvements. Diverge effect term is an improvement on summation layer calculation to supply additional separation ability and flexibility. Performance of generalized classifier neural network is compared with that of the probabilistic neural network, multilayer perceptron algorithm and radial basis function neural network on 9 different data sets and with that of generalized regression neural network on 3 different data sets include only two classes in MATLAB environment. Better classification performance up to %89 is observed. Improved classification performances proved the effectivity of the proposed neural network.
BHQ revisited (2): Texture development
Kilian, Rüdiger; Heilbronner, Renée
2016-04-01
appears that grains can be unfavourably oriented for glide despite their c-axis direction falling in those positions which were used in the "classical" interpretation. Additionally, it turns out that grain-scale dispersion axes can be used to describe the kinematic behaviour in a more consistent way compared to the rotations axes obtained from intragranular misorientations in the range of 2-10°. The implications derived from the experimental data set will be compared to data obtained from natural quartz mylonites which formed in a comparable recrystallization regime. This is the companion poster to "BHQ revisited (I) looking at grain size" where the development of the dynamically recrystallized grain size is addressed. Reference cited: Heilbronner, R., and J. Tullis (2006), Evolution of c axis pole figures and grain size during dynamic recrystallization: Results from experimentally sheared quartzite, J. Geophys. Res., 111, B10202, doi:10.1029/2005JB004194.
Miftakhov, R N; Wingate, D L
1995-01-01
A mathematical model of the enteric nervous system (Auerbach's plexus) as a planar neural network has been developed, based on the actual morphological data of its organization. The network is composed of excitatory (cholinergic) and inhibitory (adrenergic) neurones interconnected by polysynaptic channels, formed of the geometrically non-uniform unmyelinated nerve axons. The synaptic zones are modelled as a three-compartment open pharmacokinetics system, i.e., presynaptic terminal, synaptic cleft and postsynaptic membrane where the pharmacokinetic mechanisms of electrochemical coupling are considered. All the chemical reactions of transformation of acetylcholine and adrenaline within them are described by first order Michaelis-Menten kinetics. The propagation of the electrical impulse along the pathways and in the vicinity of the nerve terminal is described by the modified Hodgkin-Huxley equations. The results of numerical simulation of the propagation of excitation within the neuronal chain, inhibitory feedback circuit, and a planar neuronal network under normal physiological conditions and after treatment with cholinergic/adrenergic agonists and antagonists are presented. The model predicts the dose-dependent influence of pharmacological agents on the neural network function.
Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks.
Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming
2017-01-01
In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.
Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks
Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming
2017-01-01
In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections. PMID:28197088
Neural induction and factors that stabilize a neural fate
Rogers, Crystal; Moody, Sally A.; Casey, Elena
2009-01-01
The neural ectoderm of vertebrates forms when the BMP signaling pathway is suppressed. Herein we review the molecules that directly antagonize extracellular BMP and the signaling pathways that further contribute to reduce BMP activity in the neural ectoderm. Downstream of neural induction, a large number of “neural fate stabilizing” (NFS) transcription factors are expressed in the presumptive neural ectoderm, developing neural tube, and ultimately in neural stem cells. Herein we review what i...
Consciousness and neural plasticity
DEFF Research Database (Denmark)
In contemporary consciousness studies the phenomenon of neural plasticity has received little attention despite the fact that neural plasticity is of still increased interest in neuroscience. We will, however, argue that neural plasticity could be of great importance to consciousness studies....... If consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather...... the relation between consciousness and brain functions. If consciousness is connected to specific brain structures (as a function or in identity) what happens to consciousness when those specific underlying structures change? It is therefore possible that the understanding and theories of neural plasticity can...
Performance of the Levenberg–Marquardt neural network approach in nuclear mass prediction
Zhang, Hai Fei; Hao Wang, Li; Yin, Jing Peng; Chen, Peng Hui; Zhang, Hong Fei
2017-04-01
Resorting to a neural network approach we refined several representative and sophisticated global nuclear mass models within the latest atomic mass evaluation (AME2012). In the training process, a quite robust algorithm named the Levenberg–Marquardt (LM) method is employed to determine the weights and biases of the neural network. As a result, this LM neural network approach demonstrates a very useful tool for further improving the accuracy of mass models. For a simple liquid drop formula the root mean square (rms) deviation between the predictions and the 2353 experimental known masses are sharply reduced from 2.455 MeV to 0.235 MeV, and for the other revisited mass models, the rms is remarkably improved by about 30%.
赫胥黎与达尔文主义及生态伦理学的创新%Huxley and His Innovation of Darwinism and Ecological Ethics
Institute of Scientific and Technical Information of China (English)
何毓德; 郎补俄
2012-01-01
赫胥黎对生物进化论作出划时代创新。他汲取古希腊赫拉克利特的直观辩证法,使康德宇宙整体发展观推陈出新。从人类发生学和人猿比较解剖学新视角,重新确定了人在生物界中的位置,使达尔文的人猿同祖论,从＂假说＂深化为科学的结论。他看到人类社会和生物进化的差别,纠正了社会达尔文主义的错误。他把猿与具有＂至善伦理＂的人和生物进化相统一,赋予人类保护生态系统义不容辞的社会责任。他由此成为生态伦理学说的开拓者。%Huxley made epoch-making innovations of biological evolution. He absorbed the visual dia- lectics of Heraclitus of ancient Greece and developed new ideas out of Kant＇s whole development view of the universe. He redefined the position of man in the biological world from the new perspective of the origin of human species and the comparative anatomy of human species and apes, and therefore turned Darwin＇s theory of human and ape evolving from the same origin from hypothesis to scientific conclusion. He perceived the evolution differences between human society and biological creatures, and corrected the mistakes of social Darwinism. He integrated apes, man who has ethics and biological evolution, granting human beings the social responsibility of protecting ecological systems. Thus he became a pioneer of ecological ethics.
Yao, Yuangen; Deng, Haiyou; Ma, Chengzhang; Yi, Ming; Ma, Jun
2017-01-01
Spiral waves are observed in the chemical, physical and biological systems, and the emergence of spiral waves in cardiac tissue is linked to some diseases such as heart ventricular fibrillation and epilepsy; thus it has importance in theoretical studies and potential medical applications. Noise is inevitable in neuronal systems and can change the electrical activities of neuron in different ways. Many previous theoretical studies about the impacts of noise on spiral waves focus an unbounded Gaussian noise and even colored noise. In this paper, the impacts of bounded noise and rewiring of network on the formation and instability of spiral waves are discussed in small-world (SW) network of Hodgkin-Huxley (HH) neurons through numerical simulations, and possible statistical analysis will be carried out. Firstly, we present SW network of HH neurons subjected to bounded noise. Then, it is numerically demonstrated that bounded noise with proper intensity σ, amplitude A, or frequency f can facilitate the formation of spiral waves when rewiring probability p is below certain thresholds. In other words, bounded noise-induced resonant behavior can occur in the SW network of neurons. In addition, rewiring probability p always impairs spiral waves, while spiral waves are confirmed to be robust for small p, thus shortcut-induced phase transition of spiral wave with the increase of p is induced. Furthermore, statistical factors of synchronization are calculated to discern the phase transition of spatial pattern, and it is confirmed that larger factor of synchronization is approached with increasing of rewiring probability p, and the stability of spiral wave is destroyed.
Yao, Yuangen; Deng, Haiyou; Ma, Chengzhang; Yi, Ming
2017-01-01
Spiral waves are observed in the chemical, physical and biological systems, and the emergence of spiral waves in cardiac tissue is linked to some diseases such as heart ventricular fibrillation and epilepsy; thus it has importance in theoretical studies and potential medical applications. Noise is inevitable in neuronal systems and can change the electrical activities of neuron in different ways. Many previous theoretical studies about the impacts of noise on spiral waves focus an unbounded Gaussian noise and even colored noise. In this paper, the impacts of bounded noise and rewiring of network on the formation and instability of spiral waves are discussed in small-world (SW) network of Hodgkin-Huxley (HH) neurons through numerical simulations, and possible statistical analysis will be carried out. Firstly, we present SW network of HH neurons subjected to bounded noise. Then, it is numerically demonstrated that bounded noise with proper intensity σ, amplitude A, or frequency f can facilitate the formation of spiral waves when rewiring probability p is below certain thresholds. In other words, bounded noise-induced resonant behavior can occur in the SW network of neurons. In addition, rewiring probability p always impairs spiral waves, while spiral waves are confirmed to be robust for small p, thus shortcut-induced phase transition of spiral wave with the increase of p is induced. Furthermore, statistical factors of synchronization are calculated to discern the phase transition of spatial pattern, and it is confirmed that larger factor of synchronization is approached with increasing of rewiring probability p, and the stability of spiral wave is destroyed. PMID:28129401
Tuckwell, Henry C; Ditlevsen, Susanne
2016-10-01
We consider a classical space-clamped Hodgkin-Huxley model neuron stimulated by synaptic excitation and inhibition with conductances represented by Ornstein-Uhlenbeck processes. Using numerical solutions of the stochastic model system obtained by an Euler method, it is found that with excitation only, there is a critical value of the steady-state excitatory conductance for repetitive spiking without noise, and for values of the conductance near the critical value, small noise has a powerfully inhibitory effect. For a given level of inhibition, there is also a critical value of the steady-state excitatory conductance for repetitive firing, and it is demonstrated that noise in either the excitatory or inhibitory processes or both can powerfully inhibit spiking. Furthermore, near the critical value, inverse stochastic resonance was observed when noise was present only in the inhibitory input process. The system of deterministic differential equations for the approximate first- and second-order moments of the model is derived. They are solved using Runge-Kutta methods, and the solutions are compared with the results obtained by simulation for various sets of parameters, including some with conductances obtained by experiment on pyramidal cells of rat prefrontal cortex. The mean and variance obtained from simulation are in good agreement when there is spiking induced by strong stimulation and relatively small noise or when the voltage is fluctuating at subthreshold levels. In the occasional spike mode sometimes exhibited by spinal motoneurons and cortical pyramidal cells, the assumptions underlying the moment equation approach are not satisfied. The simulation results show that noisy synaptic input of either an excitatory or inhibitory character or both may lead to the suppression of firing in neurons operating near a critical point and this has possible implications for cortical networks. Although suppression of firing is corroborated for the system of moment equations
Chaotic diagonal recurrent neural network
Institute of Scientific and Technical Information of China (English)
Wang Xing-Yuan; Zhang Yi
2012-01-01
We propose a novel neural network based on a diagonal recurrent neural network and chaos,and its structure andlearning algorithm are designed.The multilayer feedforward neural network,diagonal recurrent neural network,and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map.The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks.
Evolvable Neural Software System
Curtis, Steven A.
2009-01-01
The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.
Sloan Digital Sky Survey Photometric Calibration Revisited
Marriner, J.
2016-05-01
The Sloan Digital Sky Survey calibration is revisited to obtain the most accurate photometric calibration. A small but significant error is found in the flat-fielding of the Photometric telescope used for calibration. Two SDSS star catalogs are compared and the average difference in magnitude as a function of right ascension and declination exhibits small systematic errors in relative calibration. The photometric transformation from the SDSS Photometric Telescope to the 2.5 m telescope is recomputed and compared to synthetic magnitudes computed from measured filter bandpasses.
Polynomial chaotic inflation in supergravity revisited
Directory of Open Access Journals (Sweden)
Kazunori Nakayama
2014-10-01
Full Text Available We revisit a polynomial chaotic inflation model in supergravity which we proposed soon after the Planck first data release. Recently some issues have been raised in Ref. [12], concerning the validity of our polynomial chaotic inflation model. We study the inflaton dynamics in detail, and confirm that the inflaton potential is very well approximated by a polynomial potential for the parameters of our interest in any practical sense, and in particular, the spectral index and the tensor-to-scalar ratio can be estimated by single-field approximation. This justifies our analysis of the polynomial chaotic inflation in supergravity.
Seed dispersal effectiveness revisited: a conceptual review
Schupp, Eugene W.; JORDANO, Pedro; Gómez Reyes, José M.
2010-01-01
Growth in seed dispersal studies has been fast-paced since the seed disperser effec- tiveness (SDE) framework was developed 17 yr ago. Thus, the time is ripe to revisit the framework in light of accumulated new insight. Here, we first present an over- view of the framework, how it has been applied, and what we know and do not know. We then introduce the SDE landscape as the two-dimensional representa- tion of the possible combinations of the quantity and the quality of dispersal and with ele...
Sloan Digital Sky Survey Photometric Calibration Revisited
Energy Technology Data Exchange (ETDEWEB)
Marriner, John; /Fermilab
2012-06-29
The Sloan Digital Sky Survey calibration is revisited to obtain the most accurate photometric calibration. A small but significant error is found in the flat-fielding of the Photometric telescope used for calibration. Two SDSS star catalogs are compared and the average difference in magnitude as a function of right ascension and declination exhibits small systematic errors in relative calibration. The photometric transformation from the SDSS Photometric Telescope to the 2.5 m telescope is recomputed and compared to synthetic magnitudes computed from measured filter bandpasses.
Revisiting Fermat's Factorization for the RSA Modulus
Gupta, Sounak
2009-01-01
We revisit Fermat's factorization method for a positive integer $n$ that is a product of two primes $p$ and $q$. Such an integer is used as the modulus for both encryption and decryption operations of an RSA cryptosystem. The security of RSA relies on the hardness of factoring this modulus. As a consequence of our analysis, two variants of Fermat's approach emerge. We also present a comparison between the two methods' effective regions. Though our study does not yield a new state-of-the-art algorithm for integer factorization, we believe that it reveals some interesting observations that are open for further analysis.
Quantum scattering on a cone revisited
Barroso, V. S.; Pitelli, J. P. M.
2017-07-01
We revisit the scattering of quantum test particles on the conical (2 +1 )-dimensional spacetime and find the scattering amplitude as a function of the boundary conditions imposed at the apex of the cone. We show that the boundary condition is responsible for a purely analytical term in the scattering amplitude, in addition to those coming from purely topological effects. Since it is possible to have nonequivalent physical evolutions for the wave packet (each one corresponding to a different boundary condition), it seems crucial to have an observable quantity specifying which evolution has been prescribed.
Guessing Revisited: A Large Deviations Approach
Hanawal, Manjesh Kumar
2010-01-01
The problem of guessing a random string is revisited. A close relation between guessing and compression is first established. Then it is shown that if the sequence of distributions of the information spectrum satisfies the large deviation property with a certain rate function, then the limiting guessing exponent exists and is a scalar multiple of the Legendre-Fenchel dual of the rate function. Other sufficient conditions related to certain continuity properties of the information spectrum are briefly discussed. This approach highlights the importance of the information spectrum in determining the limiting guessing exponent. All known prior results are then re-derived as example applications of our unifying approach.
A Novel Phase Portrait to Understand Neuronal Excitability
Franci, Alessio; Seutin, Vincent; Sepulchre, Rodolphe
2011-01-01
Fifty years ago, Fitzugh introduced a phase portrait that became famous for a twofold reason: it captured in a physiological way the qualitative behavior of Hodgkin-Huxley model and it revealed the power of simple dynamical models to unfold complex firing patterns. To date, in spite of the enormous progresses in qualitative and quantitative neural modeling, this phase portrait has remained the core picture of neuronal excitability. Yet, a major difference between the neurophysiology of 1961 and of 2011 is the recognition of the prominent role of calcium channels in firing mechanisms. We show that including this extra current in Hodgkin-Huxley dynamics leads to a revision of Fitzugh-Nagumo phase portrait that affects in a fundamental way the reduced modeling of neural excitability. The revisited model considerably enlarges the modeling power of the original one. In particular, it captures essential electrophysiological signatures that otherwise require non-physiological alteration or considerable complexicatio...
Horton Revisited: African Traditional Thought and Western Science ...
African Journals Online (AJOL)
Horton Revisited: African Traditional Thought and Western Science. ... he refers to as the 'continuity thesis' according to which there are theoretical similarities between African traditional thought and modern Western science. ... Article Metrics.
Revisiting the importance of childhood activity | van Rensburg ...
African Journals Online (AJOL)
Revisiting the importance of childhood activity. ... There has been a drastic increase in documented childhood morbidity and mortality relating to poor nutrition and ... such as obesity, type 2 diabetes, high blood cholesterol and hypertension.
Biopsychosocial model in Depression revisited.
Garcia-Toro, Mauro; Aguirre, Iratxe
2007-01-01
There are two fundamental etiological perspectives about mental disorders; biomedical and psychosocial. The biopsychosocial model has claimed to integrate these two perspectives in a scientific way, signalling their interconnection and interdependence. To that end, it used a systemic conceptual framework, taking advantage of the possibilities which it offers to establish general principles for diverse systems, independently of their physical, biological or sociological nature. In recent years, drawing on the theory of systems, theories have been developing of the dynamic non-linear systems, applicable to networks of a large quantity of densely interconnected elements (also called complex systems), like the mind or the brain. We believe that this revised systemic conceptual framework can bring integrative ideas to apply to Depression, such as the "binding dysfunction" concept we use in this article. According to this, vulnerability or predisposition to Depression would be associated with the imbalance between activating and inhibiting interactions (between some cognitions and emotions at a mental level, and between certain neuronal groups at a cerebral level). Precipitating factors would imply the increase of the activation level over this pattern of cognitions and emotions, or over those neuronal systems. When stress goes beyond the vulnerability threshold an excessive positive feedback between cognitions and emotions would appear (and between groups of neurons) with insufficient inhibitory control to mitigate it, which would imply a mental/cerebral dissociation in dominions of different level of activation. As a consequence, the generation and dissolution of patterns of cerebral and mental activation will no longer have the dynamism and flexibility that permits an optimal interaction with the environment ("binding dysfunction"). Therefore, our hypothesis is that the person with Depression will suffer at a cerebral level a functional dissociation in neural
DEFF Research Database (Denmark)
Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik
1995-01-01
This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...
Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...
Ground Zero revisits shape outbreaks: Zika and beyond
Manrique, Pedro D; Johnson, Neil F
2016-01-01
During an infection outbreak, many people continue to revisit Ground Zero - such as the one square mile of Miami involved in the current Zika outbreak- for work, family or social reasons. Public health planning must account for the counterintuitive ways in which this human flow affects the outbreak's duration, severity and time-to-peak. Managing this flow of revisits can allow the outbreak's evolution to be tailored.
Coccolithophorids in polar waters: Wigwamma spp. revisited
DEFF Research Database (Denmark)
Thomsen, Helge Abildhauge; Østergaard, Jette B.; Heldal, Mikal
2013-01-01
A contingent of weakly calcified coccolithophorid genera and species were described from polar regions almost 40 years ago. In the interim period a few additional findings have been reported enlarging the realm of some of the species. The genus Wigwamma is revisited here with the purpose of provi......A contingent of weakly calcified coccolithophorid genera and species were described from polar regions almost 40 years ago. In the interim period a few additional findings have been reported enlarging the realm of some of the species. The genus Wigwamma is revisited here with the purpose...... of providing, based on additional sampling from both polar regions, an update on species morphology, life history events and biogeography that can serve as a reference for the future. A new genus, Pseudowigwamma gen. nov. is described to accommodate Wigwamma scenozonion, a species which critically deviates...... from a core group of five Wigwamma species in terms of coccolith morphology and life history events. Wigwamma armatura sp. nov. is described on the basis of material from the Weddell Sea, Antarctica. While fitting nicely into the Wigwamma generic concept, the species adds new dimensions to the overall...
Neural Networks: Implementations and Applications
Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.
1996-01-01
Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas
Neural Networks: Implementations and Applications
Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.
1996-01-01
Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas
... NICHD Research Information Clinical Trials Resources and Publications Neural Tube Defects (NTDs): Condition Information Skip sharing on social media links Share this: Page Content What are neural tube defects? Neural (pronounced NOOR-uhl ) tube defects are ...
DEFF Research Database (Denmark)
Hørning, Annette
1994-01-01
Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse.......Artiklen beskæftiger sig med muligheden for at anvende kunstige neurale net i forbindelse med datamatisk procession af naturligt sprog, specielt automatisk talegenkendelse....
Critical Branching Neural Networks
Kello, Christopher T.
2013-01-01
It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…
Consciousness and neural plasticity
DEFF Research Database (Denmark)
changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is...
Critical Branching Neural Networks
Kello, Christopher T.
2013-01-01
It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…
Chiel, Hillel J.; Thomas, Peter J.
2011-12-01
, the sun, earth and moon) proved to be far more difficult. In the late nineteenth century, Poincaré made significant progress on this problem, introducing a geometric method of reasoning about solutions to differential equations (Diacu and Holmes 1996). This work had a powerful impact on mathematicians and physicists, and also began to influence biology. In his 1925 book, based on his work starting in 1907, and that of others, Lotka used nonlinear differential equations and concepts from dynamical systems theory to analyze a wide variety of biological problems, including oscillations in the numbers of predators and prey (Lotka 1925). Although little was known in detail about the function of the nervous system, Lotka concluded his book with speculations about consciousness and the implications this might have for creating a mathematical formulation of biological systems. Much experimental work in the 1930s and 1940s focused on the biophysical mechanisms of excitability in neural tissue, and Rashevsky and others continued to apply tools and concepts from nonlinear dynamical systems theory as a means of providing a more general framework for understanding these results (Rashevsky 1960, Landahl and Podolsky 1949). The publication of Hodgkin and Huxley's classic quantitative model of the action potential in 1952 created a new impetus for these studies (Hodgkin and Huxley 1952). In 1955, FitzHugh published an important paper that summarized much of the earlier literature, and used concepts from phase plane analysis such as asymptotic stability, saddle points, separatrices and the role of noise to provide a deeper theoretical and conceptual understanding of threshold phenomena (Fitzhugh 1955, Izhikevich and FitzHugh 2006). The Fitzhugh-Nagumo equations constituted an important two-dimensional simplification of the four-dimensional Hodgkin and Huxley equations, and gave rise to an extensive literature of analysis. Many of the papers in this special issue build on tools
Seeing the unseen: Charles Bonnet syndrome revisited.
Nair, Aditya Gopinathan; Nair, Akshay Gopinathan; Shah, Bharat R; Gandhi, Rashmin Anilkumar
2015-09-01
Charles Bonnet syndrome (CBS) is a rare condition that encompasses three clinical features: complex visual hallucinations, ocular pathology causing visual deterioration, and preserved cognitive status. Common associated ocular pathologies include age-related macular degeneration, glaucoma, and cataracts. Several theories have been proposed to try to explain the visual hallucinations. However, the pathophysiology remains poorly understood, and treatment is largely based on anecdotal data. The lack of awareness of CBS among medical professionals often leads to inappropriate diagnosis and medication. In a country like India, where awareness of mental health is not widespread, cultural myths and stigma prevent patients from seeking professional help. Here we describe two cases of CBS and revisit different ocular morbidities that have been reported to occur in conjunction with CBS. Psychiatrists and ophthalmologists alike must be sensitive to this clinical condition to ensure prompt diagnosis and treatment.
ADHM Revisited: Instantons and Wilson Lines
Tong, David
2014-01-01
We revisit the well-studied D0-D4 system of D-branes and its relationship to the ADHM construction. It is well known that the D0-branes appear as instantons in the D4-brane worldvolume. We add a Wilson line to the D4-brane in the guise of an extended fundamental string and determine how this affects the D0-brane dynamics. As the D0-brane moves in the presence of the Wilson line, it experiences a Lorentz force, proportional to its Yang-Mills gauge connection. From the perspective of the D0-brane quantum mechanics, this force emerges through the ADHM construction of the self-dual gauge connection.
Elluminate Article: Revisiting Mega-Universities
Directory of Open Access Journals (Sweden)
Eugene Rubin
2006-06-01
Full Text Available The publisher of IRRODL, The Canadian Institute of Distance Education Research (CIDER, is pleased to link here to a series of eight online seminars that took place over Spring 2006, using Elluminate live e-learning and collaborative solutions. These interactive CIDER Sessions disseminate research emanating from Canada's vibrant DE research community, and we feel these archived recordings are highly relevant to many in the international distance education research community. To access these sessions, you must first download FREE software. Visit http://www.elluminate.com/support/ (Elluminate Support for details on how to download this FREE software. * Revisiting Mega-Universities Gene Rubin and Claudine SchWeber University of Maryland University College
Resolution of Reflection Seismic Data Revisited
DEFF Research Database (Denmark)
Hansen, Thomas Mejer; Mosegaard, Klaus; Zunino, Andrea
wavelength of the wavelet within the thin layer. Using a simple thin-layer parameterization Widess (1973) demonstrated that thin layers with thickness less that around λb/8 cannot be resolved from seismic data independent of the noise level. This has results since been widely adopted as a commonly accepted...... lower vertical resolution of reflection seismic data. In the following we will revisit think layer model and demonstrate that there is in practice no limit to the vertical resolution using the parameterization of Widess (1973), and that the vertical resolution is limited by the noise in the data....... In general, we discuss that the resolution of reflection seismic data is controlled by the noise level and the a priori information available...
Visual Object Tracking Performance Measures Revisited.
Čehovin, Luka; Leonardis, Aleš; Kristan, Matej
2016-03-01
The problem of visual tracking evaluation is sporting a large variety of performance measures, and largely suffers from lack of consensus about which measures should be used in experiments. This makes the cross-paper tracker comparison difficult. Furthermore, as some measures may be less effective than others, the tracking results may be skewed or biased toward particular tracking aspects. In this paper, we revisit the popular performance measures and tracker performance visualizations and analyze them theoretically and experimentally. We show that several measures are equivalent from the point of information they provide for tracker comparison and, crucially, that some are more brittle than the others. Based on our analysis, we narrow down the set of potential measures to only two complementary ones, describing accuracy and robustness, thus pushing toward homogenization of the tracker evaluation methodology. These two measures can be intuitively interpreted and visualized and have been employed by the recent visual object tracking challenges as the foundation for the evaluation methodology.
Post-Inflationary Gravitino Production Revisited
Ellis, John; Nanopoulos, Dimitri V; Olive, Keith A; Peloso, Marco
2016-01-01
We revisit gravitino production following inflation. As a first step, we review the standard calculation of gravitino production in the thermal plasma formed at the end of post-inflationary reheating when the inflaton has completely decayed. Next we consider gravitino production prior to the completion of reheating, assuming that the inflaton decay products thermalize instantaneously while they are still dilute. We then argue that instantaneous thermalization is in general a good approximation, and also show that the contribution of non-thermal gravitino production via the collisions of inflaton decay products prior to thermalization is relatively small. Our final estimate of the gravitino-to-entropy ratio is approximated well by a standard calculation of gravitino production in the post-inflationary thermal plasma assuming total instantaneous decay and thermalization at a time $t \\simeq 1.2/\\Gamma_\\phi$. Finally, in light of our calculations, we consider potential implications of upper limits on the gravitin...
Seasonal dating of Sappho's 'Midnight Poem' revisited
Cuntz, Manfred; Gurdemir, Levent; George, Martin
2016-04-01
Sappho was a Greek lyric poet who composed a significant array of pristine poetry. Although much of it has been lost, her reputation has endured thanks to numerous surviving fragments. One of her contributions includes the so-called 'Midnight Poem', which contains a line about the Pleiades, setting sometime before midnight, and supposedly observed from the island of Lesbos. This poem also refers to the setting of the Moon. Sappho's Midnight Poem thus represents a prime example of where ancient poetry and astronomy merge, and it also offers the possibility of seasonal dating. Previously, Herschberg and Mebius (1990) estimated that the poem was composed in late winter/early spring, a time frame that is not unusual for lyrics of an amorous nature. The aim of our paper is to revisit this earlier finding by using modern-day software. Our study confirms Herschberg and Mebius' result, but also conveys further information.
Revisiting R-invariant Direct Gauge Mediation
Chiang, Cheng-Wei; Ibe, Masahiro; Yanagida, Tsutomu T
2015-01-01
We revisit a special model of gauge mediated supersymmetry breaking, the "R-invariant direct gauge mediation." We pay particular attention to whether the model is consistent with the minimal model of the \\mu-term, i.e., a simple mass term of the Higgs doublets in the superpotential. Although the incompatibility is highlighted in view of the current experimental constraints on the superparticle masses and the observed Higgs boson mass, the minimal \\mu-term can be consistent with the R-invariant gauge mediation model via a careful choice of model parameters. We derive an upper limit on the gluino mass from the observed Higgs boson mass. We also discuss whether the model can explain the 3\\sigma excess of the Z+jets+$E_T^{\\rm miss}$ events reported by the ATLAS Collaboration.
Neutrino Dark Energy -- Revisiting the Stability Issue
Bjaelde, Ole Eggers; van de Bruck, Carsten; Hannestad, Steen; Mota, David F; Schrempp, Lily; Tocchini-Valentini, Domenico
2007-01-01
A coupling between a light scalar field and neutrinos has been widely discussed as a mechanism for linking (time varying) neutrino masses and the present energy density and equation of state of dark energy. However, it has been pointed out that the viability of this scenario in the non-relativistic neutrino regime is threatened by the strong growth of hydrodynamic perturbations associated with a negative adiabatic sound speed squared. In this paper we revisit the stability issue in the framework of linear perturbation theory in a model independent way. The criterion for the stability of a model is translated into a constraint on the scalar-neutrino coupling, which depends on the ratio of the energy densities in neutrinos and cold dark matter. We illustrate our results by providing meaningful examples both for stable and unstable models.
The Species Problem in Myxomycetes Revisited.
Walker, Laura M; Stephenson, Steven L
2016-08-01
Species identification in the myxomycetes (plasmodial slime molds or myxogastrids) poses particular challenges to researchers as a result of their morphological plasticity and frequent alteration between sexual and asexual life strategies. Traditionally, myxomycete morphology has been used as the primary method of species delimitation. However, with the increasing availability of genetic information, traditional myxomycete taxonomy is being increasingly challenged, and new hypotheses continue to emerge. Due to conflicts that sometimes occur between traditional and more modern species concepts that are based largely on molecular data, there is a pressing need to revisit the discussion surrounding the species concept used for myxomycetes. Biological diversity is being increasingly studied with molecular methods and data accumulates at ever-faster rates, making resolution of this matter urgent. In this review, currently used and potentially useful species concepts (biological, morphological, phylogenetic and ecological) are reviewed, and an integrated approach to resolve the myxomycete species problem is discussed. Copyright © 2016 Elsevier GmbH. All rights reserved.
Revisiting Hafemeister's science and society tests
Brecha, R. J.; Berney, R.; Craver, B.
2007-10-01
We revisit a series of papers on science and society issues by David Hafemeister in the 1970s and 1980s. The emphasis in the present work is on world oil production limits and some consequences of various possible scenarios for the near future. Some of the data and scenarios used by Hafemeister are updated for U.S. oil production in the past two decades, and extended to an analysis of a peak in world oil production in the future. We discuss some simple scenarios for future energy use patterns and look at the consequence of these scenarios as world oil production begins to decline. We also provide a list of resources for critical investigations of natural resource extraction and depletion patterns.
Revisiting gravitino dark matter in thermal leptogenesis
Ibe, Masahiro; Suzuki, Motoo; Yanagida, Tsutomu T.
2017-02-01
In this paper, we revisit the gravitino dark matter scenario in the presence of the bilinear R-parity violating interaction. In particular, we discuss a consistency with the thermal leptogenesis. For a high reheating temperature required for the thermal leptogenesis, the gravitino dark matter tends to be overproduced, which puts a severe upper limit on the gluino mass. As we will show, a large portion of parameter space of the gravitino dark matter scenario has been excluded by combining the constraints from the gravitino abundance and the null results of the searches for the superparticles at the LHC experiments. In particular, the models with the stau (and other charged slepton) NLSP has been almost excluded by the searches for the long-lived charged particles at the LHC unless the required reheating temperature is somewhat lowered by assuming, for example, a degenerated right-handed neutrino mass spectrum.
Revisiting gravitino dark matter in thermal leptogenesis
Ibe, Masahiro; Yanagida, Tsutomu T
2016-01-01
In this paper, we revisit the gravitino dark matter scenario in the presence of the bilinear $R$-parity violating interaction. In particular, we discuss a consistency with the thermal leptogenesis. For a high reheating temperature required for the thermal leptogenesis, the gravitino dark matter tends to be overproduced, which puts a severe upper limit on the gluino mass. As we will show, a large portion of parameter space of the gravitino dark matter scenario has been excluded by combining the constraints from the gravitino abundance and the null results of the searches for the superparticles at the LHC experiments. In particular, the models with the stau (and other charged slepton) NLSP has been almost excluded by the searches for the long-lived charged particles at the LHC unless the required reheating temperature is somewhat lowered by assuming, for example, a degenerated right-handed neutrino mass spectrum.
Neutrino dark energy. Revisiting the stability issue
Energy Technology Data Exchange (ETDEWEB)
Eggers Bjaelde, O.; Hannestad, S. [Aarhus Univ. (Denmark). Dept. of Physics and Astronomy; Brookfield, A.W. [Sheffield Univ. (United Kingdom). Dept. of Applied Mathematics and Dept. of Physics, Astro-Particle Theory and Cosmology Group; Van de Bruck, C. [Sheffield Univ. (United Kingdom). Dept. of Applied Mathematics, Astro-Particle Theory and Cosmology Group; Mota, D.F. [Heidelberg Univ. (Germany). Inst. fuer Theoretische Physik]|[Institute of Theoretical Astrophysics, Oslo (Norway); Schrempp, L. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Tocchini-Valentini, D. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Physics and Astronomy
2007-05-15
A coupling between a light scalar field and neutrinos has been widely discussed as a mechanism for linking (time varying) neutrino masses and the present energy density and equation of state of dark energy. However, it has been pointed out that the viability of this scenario in the non-relativistic neutrino regime is threatened by the strong growth of hydrodynamic perturbations associated with a negative adiabatic sound speed squared. In this paper we revisit the stability issue in the framework of linear perturbation theory in a model independent way. The criterion for the stability of a model is translated into a constraint on the scalar-neutrino coupling, which depends on the ratio of the energy densities in neutrinos and cold dark matter. We illustrate our results by providing meaningful examples both for stable and unstable models. (orig.)
Revisiting Lepton Flavour Universality in B Decays
Paradisi, Paride
2017-04-01
Lepton flavour universality (LFU) in B-decays is revisited by considering a class of semileptonic operators defined at a scale Λ above the electroweak scale v. The importance of quantum effects is emphasised [F. Feruglio, P. Paradisi and A. Pattori, arxiv:arXiv:1606.00524 [hep-ph], to appear in PRL]. We construct the low-energy effective Lagrangian taking into account the running effects from Λ down to v through the one-loop renormalization group equations (RGE) in the limit of exact electroweak symmetry and QED RGEs from v down to the 1 GeV scale. The most important quantum effects turn out to be the modification of the leptonic couplings of the vector boson Z and the generation of a purely leptonic effective Lagrangian. Large LFU breaking effects in Z and τ decays as well as visible lepton flavour violating (LFV) effects in τ decays are induced.
Dynamics of neural cryptography.
Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido
2007-05-01
Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.
Energy Technology Data Exchange (ETDEWEB)
Labrador, I.; Carrasco, R.; Martinez, L.
1996-07-01
This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The typical BDI (belief desire intention) model of agent is not efficiently computable and the strict logic expression is not easily applicable to the AUV (autonomous underwater vehicle) domain with uncertainties. In this paper, an AUV fuzzy neural BDI model is proposed. The model is a fuzzy neural network composed of five layers: input ( beliefs and desires) , fuzzification, commitment, fuzzy intention, and defuzzification layer. In the model, the fuzzy commitment rules and neural network are combined to form intentions from beliefs and desires. The model is demonstrated by solving PEG (pursuit-evasion game), and the simulation result is satisfactory.
Zhang, Baoyong; Lam, James; Xu, Shengyuan
2015-07-01
This paper revisits the problem of asymptotic stability analysis for neural networks with distributed delays. The distributed delays are assumed to be constant and prescribed. Since a positive-definite quadratic functional does not necessarily require all the involved symmetric matrices to be positive definite, it is important for constructing relaxed Lyapunov-Krasovskii functionals, which generally lead to less conservative stability criteria. Based on this fact and using two kinds of integral inequalities, a new delay-dependent condition is obtained, which ensures that the distributed delay neural network under consideration is globally asymptotically stable. This stability criterion is then improved by applying the delay partitioning technique. Two numerical examples are provided to demonstrate the advantage of the presented stability criteria.
Critical branching neural networks.
Kello, Christopher T
2013-01-01
It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical branching and, in doing so, simulates observed scaling laws as pervasive to neural and behavioral activity. These scaling laws are related to neural and cognitive functions, in that critical branching is shown to yield spiking activity with maximal memory and encoding capacities when analyzed using reservoir computing techniques. The model is also shown to account for findings of pervasive 1/f scaling in speech and cued response behaviors that are difficult to explain by isolable causes. Issues and questions raised by the model and its results are discussed from the perspectives of physics, neuroscience, computer and information sciences, and psychological and cognitive sciences.
DEFF Research Database (Denmark)
Krogh, Anders Stærmose; Riis, Søren Kamaric
1999-01-01
A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...
Neural Oscillators Programming Simplified
Directory of Open Access Journals (Sweden)
Patrick McDowell
2012-01-01
Full Text Available The neurological mechanism used for generating rhythmic patterns for functions such as swallowing, walking, and chewing has been modeled computationally by the neural oscillator. It has been widely studied by biologists to model various aspects of organisms and by computer scientists and robotics engineers as a method for controlling and coordinating the gaits of walking robots. Although there has been significant study in this area, it is difficult to find basic guidelines for programming neural oscillators. In this paper, the authors approach neural oscillators from a programmer’s point of view, providing background and examples for developing neural oscillators to generate rhythmic patterns that can be used in biological modeling and robotics applications.
Neural networks and graph theory
Institute of Scientific and Technical Information of China (English)
许进; 保铮
2002-01-01
The relationships between artificial neural networks and graph theory are considered in detail. The applications of artificial neural networks to many difficult problems of graph theory, especially NP-complete problems, and the applications of graph theory to artificial neural networks are discussed. For example graph theory is used to study the pattern classification problem on the discrete type feedforward neural networks, and the stability analysis of feedback artificial neural networks etc.
Carreira, Paulo J.F.; Rosa, Miguel A.; Neto, João Pedro; Costa, José Félix
1998-01-01
In the work of [Siegelmann 95] it was showed that Artificial Recursive Neural Networks have the same computing power as Turing machines. A Turing machine can be programmed in a proper high-level language - the language of partial recursive functions. In this paper we present the implementation of a compiler that directly translates high-level Turing machine programs to Artificial Recursive Neural Networks. The application contains a simulator that can be used to test the resulting networks. W...
Neural cryptography with feedback
Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido
2004-04-01
Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.
Svoboda, Karel
2016-01-01
Since the start of the new millennium, a method called two-photon microscopy has allowed scientists to peer farther into the brain than ever before. Our author, one of the pioneers in the development of this new technology, writes that "directly observing the dynamics of neural networks in an intact brain has become one of the holy grails of brain research." His article describes the advances that led to this remarkable breakthrough-one that is helping neuroscientists better understand neural networks.
1998-01-01
In the work of [Siegelmann 95] it was showed that Artificial Recursive Neural Networks have the same computing power as Turing machines. A Turing machine can be programmed in a proper high-level language - the language of partial recursive functions. In this paper we present the implementation of a compiler that directly translates high-level Turing machine programs to Artificial Recursive Neural Networks. The application contains a simulator that can be used to test the resulting networks. W...
Neural cryptography with feedback.
Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido
2004-04-01
Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.
Institute of Scientific and Technical Information of China (English)
于凯; 赵辉; 王红君; 岳有军
2009-01-01
本文以Hodgkin-Huxley(HH)为基础,分析外电场对神经细胞的作用机制,建立了极低电场下改进的HH模型.我们通过高维系统Hopf分岔存在性的代数判据,计算了(外部刺激电流)和(外部直流电场引起的跨膜电压)的单参数空间的Hopf分岔集,并给出了系统产生稳定周期解的参数区域,这将有助于从理论上揭示和解释电场致病的生物机理,为预防和治疗此类疾病提供理论依据.
Neural networks in seismic discrimination
Energy Technology Data Exchange (ETDEWEB)
Dowla, F.U.
1995-01-01
Neural networks are powerful and elegant computational tools that can be used in the analysis of geophysical signals. At Lawrence Livermore National Laboratory, we have developed neural networks to solve problems in seismic discrimination, event classification, and seismic and hydrodynamic yield estimation. Other researchers have used neural networks for seismic phase identification. We are currently developing neural networks to estimate depths of seismic events using regional seismograms. In this paper different types of network architecture and representation techniques are discussed. We address the important problem of designing neural networks with good generalization capabilities. Examples of neural networks for treaty verification applications are also described.
Ellis, John
2016-01-01
We revisit minimal supersymmetric SU(5) grand unification (GUT) models in which the soft supersymmetry-breaking parameters of the minimal supersymmetric Standard Model (MSSM) are universal at some input scale, $M_{in}$, above the supersymmetric gauge coupling unification scale, $M_{GUT}$. As in the constrained MSSM (CMSSM), we assume that the scalar masses and gaugino masses have common values, $m_0$ and $m_{1/2}$ respectively, at $M_{in}$, as do the trilinear soft supersymmetry-breaking parameters $A_0$. Going beyond previous studies of such a super-GUT CMSSM scenario, we explore the constraints imposed by the lower limit on the proton lifetime and the LHC measurement of the Higgs mass, $m_h$. We find regions of $m_0$, $m_{1/2}$, $A_0$ and the parameters of the SU(5) superpotential that are compatible with these and other phenomenological constraints such as the density of cold dark matter, which we assume to be provided by the lightest neutralino. Typically, these allowed regions appear for $m_0$ and $m_{1/...
Energy Technology Data Exchange (ETDEWEB)
P., Henry
2008-11-20
A recent article in which John Searle claims to refute dualism is examined from a scientific perspective. John Searle begins his recent article 'Dualism Revisited' by stating his belief that the philosophical problem of consciousness has a scientific solution. He then claims to refute dualism. It is therefore appropriate to examine his arguments against dualism from a scientific perspective. Scientific physical theories contain two kinds of descriptions: (1) Descriptions of our empirical findings, expressed in an every-day language that allows us communicate to each other our sensory experiences pertaining to what we have done and what we have learned; and (2) Descriptions of a theoretical model, expressed in a mathematical language that allows us to communicate to each other certain ideas that exist in our mathematical imaginations, and that are believed to represent, within our streams of consciousness, certain aspects of reality that we deem to exist independently of their being perceived by any human observer. These two parts of our scientific description correspond to the two aspects of our general contemporary dualistic understanding of the total reality in which we are imbedded, namely the empirical-mental aspect and the theoretical-physical aspect. The duality question is whether this general dualistic understanding of ourselves should be regarded as false in some important philosophical or scientific sense.
Revisiting the relaxation dynamics of isolated pyrrole
Energy Technology Data Exchange (ETDEWEB)
Montero, Raúl; Ovejas, Virginia; Fernández-Fernández, Marta; Longarte, Asier, E-mail: asier.longarte@ehu.es [Departamento de Química Física, Universidad del País Vasco (UPV/EHU), Apart. 644, 48080 Bilbao (Spain); Peralta Conde, Álvaro [Centro de Láseres Pulsados (CLPU), Edificio M3, Parque Científico, 37185 Villamayor (Spain)
2014-07-07
Herein, the interpretation of the femtosecond-scale temporal evolution of the pyrrole ion signal, after excitation in the 267–217 nm interval, recently published by our group [R. Montero, A. Peralta Conde, V. Ovejas, M. Fernández-Fernández, F. Castaño, J. R. Vázquez de Aldana, and A. Longarte, J. Chem. Phys.137, 064317 (2012)] is re-visited. The observation of a shift in the pyrrole{sup +} transient respect to zero delay reference, initially attributed to ultrafast dynamics on the πσ{sup *} type state (3s a{sub 1} ← π 1a{sub 2}), is demonstrated to be caused by the existence of pump + probe populated states, along the ionization process. The influence of these resonances in pump-prone ionization experiments, when multi-photon probes are used, and the significance of a proper zero-time reference, is discussed. The possibility of preparing the πσ{sup *} state by direct excitation is investigated by collecting 1 + 1 photoelectron spectra, at excitation wavelengths ranging from 255 to 219 nm. No conclusive evidences of ionization through this state are found.
Spin-orbit evolution of Mercury revisited
Noyelles, Benoit; Makarov, Valeri; Efroimsky, Michael
2013-01-01
Mercury is a peculiar case, in that it is locked into the 3:2 spin-orbit resonance. Its rotation period, 58 days, is exactly two thirds of its orbital period. It is accepted that the eccentricity of Mercury (0.206) favours the trapping into this resonance. More controversial is how the capture took place. A recent study by Makarov has shown that entrapment into this resonance is certain if the eccentricity is larger than 0.2, provided that we use a realistic tidal model, based on the Darwin-Kaula expansion of the tidal torque, including both the elastic rebound and anelastic creep of solids. We here revisit the scenario of Mercury's capture into the supersynchronous spin-orbit resonances. The study is based on a realistic model of tidal friction in solids, that takes into account the rheology and the self-gravitation of the planet. Developed in Efroimsky, it was employed by Makarov et al. to determine the likely spin state of the planet GJ581d, with its eccentricity evolution taken into account. It was also u...
[What mirror neurons have revealed: revisited].
Murata, Akira; Maeda, Kazutaka
2014-06-01
The first paper on mirror neurons was published in 1992. In the span of over two decades since then, much knowledge about the relationship between social cognitive function and the motor control system has been accumulated. Direct matching of visual actions and their corresponding motor representations is the most important functional property of mirror neuron. Many studies have emphasized intrinsic simulation as a core concept for mirror neurons. Mirror neurons are thought to play a role in social cognitive function. However, the function of mirror neurons in the macaque remains unclear, because such cognitive functions are limited or lacking in macaque monkeys. It is therefore important to discuss these neurons in the context of motor function. Rizzolatti and colleagues have stressed that the most important function of mirror neurons in macaques is recognition of actions performed by other individuals. I suggest that mirror neurons in the Macaque inferior pariental lobule might be correlated with body schema. In the parieto-premotor network, matching of corollary discharge and actual sensory feedback is an essential neuronal operation. Recently, neurons showing mirror properties were found in some cortical areas outside the mirror neuron system. The current work would revisit the outcomes of mirror neuron studies to discuss the function of mirror neurons in the monkey.
Revisiting the Anatomy of the Living Heart.
Mori, Shumpei; Spicer, Diane E; Anderson, Robert H
2016-01-01
An understanding of the complexity of cardiac anatomy is required by all who seek, in the setting of cardiac disease, to interpret the images confronting them. Although the mysteries of cardiac structure have been extensively addressed, significant gaps continue to exist between the descriptions provided by morphologists and by those working in the clinical setting. In part, this reflects the limitations in providing 3D visualization of such a complicated organ. Current 3D imaging technology now permits visualization of the cardiac components using datasets obtained in the living individual. These advances, furthermore, demonstrate the anatomy in the setting of the heart as imaged within the thorax. It has been failure to describe the heart as it lies within the thorax that remains a major deficiency of many morphologists relying on the dissecting room to provide the gold standard. Describing the heart in attitudinally appropriate fashion, a basic rule of clinical anatomy, creates the necessary bridges between anatomists and clinicians. The rapid progression of cardiac interventional techniques, furthermore, emphasizes the need to revisit cardiac anatomy using a multidisciplinary approach. In this review, therefore, we illustrate the advantages of an attitudinally correct approach to cardiac anatomy. We then focus on the morphology of the arterial roots, revealing the accuracy that can now be achieved by clinicians using datasets obtained during life.
Seed dispersal effectiveness revisited: a conceptual review.
Schupp, Eugene W; Jordano, Pedro; Gómez, José María
2010-10-01
Growth in seed dispersal studies has been fast-paced since the seed disperser effectiveness (SDE) framework was developed 17 yr ago. Thus, the time is ripe to revisit the framework in light of accumulated new insight. Here, we first present an overview of the framework, how it has been applied, and what we know and do not know. We then introduce the SDE landscape as the two-dimensional representation of the possible combinations of the quantity and the quality of dispersal and with elevational contours representing isoclines of SDE. We discuss the structure of disperser assemblages on such landscapes. Following this we discuss recent advances and ideas in seed dispersal in the context of their impacts on SDE. Finally, we highlight a number of emerging issues that provide insight into SDE. Overall, the SDE framework successfully captures the complexities of seed dispersal. We advocate an expanded use of the term dispersal encompassing the multiple recruitment stages from fruit to adult. While this entails difficulties in estimating SDE, it is a necessary expansion if we are to understand the central relevance of seed dispersal in plant ecology and evolution.
Hyperinflation in Brazil, Israel, and Nicaragua revisited
Szybisz, Martín A.; Szybisz, Leszek
2017-01-01
The aim of the present work is to address the description of hyperinflation regimens in economy. The spirals of hyperinflation developed in Brazil, Israel, and Nicaragua are revisited. This new analysis of data indicates that the episodes occurred in Brazil and Nicaragua can be understood within the frame of the model available in the literature, which is based on a nonlinear feedback (NLF) characterized by an exponent β > 0. In the NLF model the accumulated consumer price index carries a finite time singularity of the type 1 /(tc - t) (1 - β) / β determining a critical time tc at which the economy would crash. It is shown that in the case of Brazil the entire episode cannot be described with a unique set of parameters because the time series was strongly affected by a change of policy. This fact gives support to the "so called" Lucas critique, who stated that model's parameters usually change once policy changes. On the other hand, such a model is not able to provide any tc in the case of the weaker hyperinflation occurred in Israel. It is shown that in this case the fit of data yields β → 0. This limit leads to the linear feedback formulation which does not predict any tc. An extension for the NLF model is suggested.
Revisiting the cardiometabolic relevance of serum amylase
Directory of Open Access Journals (Sweden)
Munakata Hiromi
2011-10-01
Full Text Available Abstract Background The pancreas has dual functions as a digestive organ and as an endocrine organ, by secreting digestive enzymes and endocrine hormones. Some early studies have revealed that serum amylase levels are lower in individuals with chronic pancreatitis, severe long-term type 2 diabetes or type 1 diabetes. Regarding this issue, we recently reported that low serum amylase levels were associated with metabolic syndrome and diabetes in asymptomatic adults. In the light of this, we further investigated the fundamental relationship between serum amylase and cardiometabolic aspects by reanalyzing previous data which comprised subjects without diabetes treatment with oral hypoglycemic drugs or insulin (n = 2,344. Findings Serum amylase was inversely correlated with body mass index independently of age. Higher serum amylase levels were noted in older subjects aged 55 years old or more (n = 1,114 than in younger subjects (P P Conclusions Revisiting the cardiometabolic relevance of serum amylase may yield novel insight not only into glucose homeostasis and metabolic abnormalities related to obesity, but also possibly carbohydrate absorption in the gut.
Coal consumption and economic growth revisited
Energy Technology Data Exchange (ETDEWEB)
Wolde-Rufael, Yemane [135 Carnwath Road, London SW6 3HR (United Kingdom)
2010-01-15
This paper revisits the causal relationship between coal consumption and real GDP for six major coal consuming countries for the period 1965-2005 within a vector autoregressive (VAR) framework by including capital and labour as additional variables. Applying a modified version of the Granger causality test due to Toda and Yamamoto [Toda HY, Yamamoto T. Statistical inference in vector autoregressions with possibly integrated process. J Econom 1995;66:225-50], we found a unidirectional causality running from coal consumption to economic growth in India and Japan while the opposite causality running from economic growth to coal consumption was found in China and South Korea. In contrast there was a bi-directional causality running between economic growth and coal consumption in South Africa and the United States. Variance decomposition analysis seems to confirm our Granger causality results. The policy implication is that measures adopted to mitigate the adverse effects of coal consumption may be taken without harming economic growth in China and South Korea. In contrast, for the remaining four countries conservation measures can harm economic growth. (author)
Targeting Cancer Metabolism - Revisiting the Warburg Effects
Tran, Quangdon; Lee, Hyunji; Park, Jisoo; Kim, Seon-Hwan; Park, Jongsun
2016-01-01
After more than half of century since the Warburg effect was described, this atypical metabolism has been standing true for almost every type of cancer, exhibiting higher glycolysis and lactate metabolism and defective mitochondrial ATP production. This phenomenon had attracted many scientists to the problem of elucidating the mechanism of, and reason for, this effect. Several models based on oncogenic studies have been proposed, such as the accumulation of mitochondrial gene mutations, the switch from oxidative phosphorylation respiration to glycolysis, the enhancement of lactate metabolism, and the alteration of glycolytic genes. Whether the Warburg phenomenon is the consequence of genetic dysregulation in cancer or the cause of cancer remains unknown. Moreover, the exact reasons and physiological values of this peculiar metabolism in cancer remain unclear. Although there are some pharmacological compounds, such as 2-deoxy-D-glucose, dichloroacetic acid, and 3-bromopyruvate, therapeutic strategies, including diet, have been developed based on targeting the Warburg effect. In this review, we will revisit the Warburg effect to determine how much scientists currently understand about this phenomenon and how we can treat the cancer based on targeting metabolism. PMID:27437085
Energy Technology Data Exchange (ETDEWEB)
Ellis, John [King' s College London, Theoretical Physics and Cosmology Group, Department of Physics, London (United Kingdom); CERN, Theoretical Physics Department, Geneva (Switzerland); Evans, Jason L. [KIAS, School of Physics, Seoul (Korea, Republic of); Mustafayev, Azar; Nagata, Natsumi; Olive, Keith A. [University of Minnesota, William I. Fine Theoretical Physics Institute, School of Physics and Astronomy, Minneapolis, MN (United States)
2016-11-15
We revisit minimal supersymmetric SU(5) grand unification (GUT) models in which the soft supersymmetry-breaking parameters of the minimal supersymmetric Standard Model (MSSM) are universal at some input scale, M{sub in}, above the supersymmetric gauge-coupling unification scale, M{sub GUT}. As in the constrained MSSM (CMSSM), we assume that the scalar masses and gaugino masses have common values, m{sub 0} and m{sub 1/2}, respectively, at M{sub in}, as do the trilinear soft supersymmetry-breaking parameters A{sub 0}. Going beyond previous studies of such a super-GUT CMSSM scenario, we explore the constraints imposed by the lower limit on the proton lifetime and the LHC measurement of the Higgs mass, m{sub h}. We find regions of m{sub 0}, m{sub 1/2}, A{sub 0} and the parameters of the SU(5) superpotential that are compatible with these and other phenomenological constraints such as the density of cold dark matter, which we assume to be provided by the lightest neutralino. Typically, these allowed regions appear for m{sub 0} and m{sub 1/2} in the multi-TeV region, for suitable values of the unknown SU(5) GUT-scale phases and superpotential couplings, and with the ratio of supersymmetric Higgs vacuum expectation values tanβ
The Fractional Langevin Equation: Brownian Motion Revisited
Mainardi, Francesco
2008-01-01
We have revisited the Brownian motion on the basis of the fractional Langevin equation which turns out to be a particular case of the generalized Langevin equation introduced by Kubo on 1966. The importance of our approach is to model the Brownian motion more realistically than the usual one based on the classical Langevin equation, in that it takes into account also the retarding effects due to hydrodynamic backflow, i.e. the added mass and the Basset memory drag. On the basis of the two fluctuation-dissipation theorems and of the techniques of the Fractional Calculus we have provided the analytical expressions of the correlation functions (both for the random force and the particle velocity) and of the mean squared particle displacement. The random force has been shown to be represented by a superposition of the usual white noise with a "fractional" noise. The velocity correlation function is no longer expressed by a simple exponential but exhibits a slower decay, proportional to $t^{-3/2}$ as $t \\to \\infty...
The drive revisited: Mastery and satisfaction.
Denis, Paul
2016-06-01
Starting from the theory of the libido and the notions of the experience of satisfaction and the drive for mastery introduced by Freud, the author revisits the notion of the drive by proposing the following model: the drive takes shape in the combination of two currents of libidinal cathexis, one which takes the paths of the 'apparatus for obtaining mastery' (the sense-organs, motricity, etc.) and strives to appropriate the object, and the other which cathects the erotogenic zones and the experience of satisfaction that is experienced through stimulation in contact with the object. The result of this combination of cathexes constitutes a 'representation', the subsequent evocation of which makes it possible to tolerate for a certain period of time the absence of a satisfying object. On the basis of this conception, the author distinguishes the representations proper, vehicles of satisfaction, from imagos and traumatic images which give rise to excitation that does not link up with the paths taken by the drives. This model makes it possible to conciliate the points of view of the advocates of 'object-seeking' and of those who give precedence to the search for pleasure, and, further, to renew our understanding of object-relations, which can then be approached from the angle of their relations to infantile sexuality. Destructiveness is considered in terms of "mastery madness" and not in terms of the late Freudian hypothesis of the death drive.
Revisiting the argument from fetal potential
Directory of Open Access Journals (Sweden)
Manninen Bertha
2007-05-01
Full Text Available Abstract One of the most famous, and most derided, arguments against the morality of abortion is the argument from potential, which maintains that the fetus' potential to become a person and enjoy the valuable life common to persons, entails that its destruction is prima facie morally impermissible. In this paper, I will revisit and offer a defense of the argument from potential. First, I will criticize the classical arguments proffered against the importance of fetal potential, specifically the arguments put forth by philosophers Peter Singer and David Boonin, by carefully unpacking the claims made in these arguments and illustrating why they are flawed. Secondly, I will maintain that fetal potential is morally relevant when it comes to the morality of abortion, but that it must be accorded a proper place in the argument. This proper place, however, cannot be found until we first answer a very important and complex question: we must first address the issue of personal identity, and when the fetus becomes the type of being who is relevantly identical to a future person. I will illustrate why the question of fetal potential can only be meaningfully addressed after we have first answered the question of personal identity and how it relates to the human fetus.
Pair Production Constraints on Superluminal Neutrinos Revisited
Energy Technology Data Exchange (ETDEWEB)
Brodsky, Stanley J.; /SLAC; Gardner, Susan; /Kentucky U.
2012-02-16
We revisit the pair creation constraint on superluminal neutrinos considered by Cohen and Glashow in order to clarify which types of superluminal models are constrained. We show that a model in which the superluminal neutrino is effectively light-like can evade the Cohen-Glashow constraint. In summary, any model for which the CG pair production process operates is excluded because such timelike neutrinos would not be detected by OPERA or other experiments. However, a superluminal neutrino which is effectively lightlike with fixed p{sup 2} can evade the Cohen-Glashow constraint because of energy-momentum conservation. The coincidence involved in explaining the SN1987A constraint certainly makes such a picture improbable - but it is still intrinsically possible. The lightlike model is appealing in that it does not violate Lorentz symmetry in particle interactions, although one would expect Hughes-Drever tests to turn up a violation eventually. Other evasions of the CG constraints are also possible; perhaps, e.g., the neutrino takes a 'short cut' through extra dimensions or suffers anomalous acceleration in matter. Irrespective of the OPERA result, Lorentz-violating interactions remain possible, and ongoing experimental investigation of such possibilities should continue.
Scaling Relationships for Spherical Polymer Brushes Revisited.
Chen, Guang; Li, Hao; Das, Siddhartha
2016-06-16
In this short paper, we revisit the scaling relationships for spherical polymer brushes (SPBs), i.e., polymer brushes grafted to rigid, spherical particles. Considering that the brushes can be described to be encased in a series of hypothetical spherical blobs, we identify significant physical discrepancies in the model of Daoud and Cotton (Journal of Physics, 1982), which is considered to be the state of the art in scaling modeling of SPBs. We establish that the "brush" configuration of the polymer molecules forming the SPBs is possible only if the swelling ratio (which is the ratio of the end-to-end length of the blob-encased polymer segment to the corresponding coil-like polymer segment) is always less than unity-a notion that has been erroneously overlooked in the model of Daoud and Cotton. We also provide new scaling arguments that (a) establish this swelling (or more appropriately shrinking) ratio as a constant (less than unity) for the case of "good" solvent, (b) recover the scaling predictions for blob dimension and monomer number and monomer concentration distributions within the blob, and
Revisiting the Survival Mnemonic Effect in Children
Directory of Open Access Journals (Sweden)
Josefa N. S. Pand Eirada
2014-04-01
Full Text Available The survival processing paradigm is designed to explore the adaptive nature of memory functioning. The mnemonic advantage of processing information in fitness-relevant contexts, as has been demonstrated using this paradigm, is now well established, particularly in young adults; this phenomenon is often referred to as the “survival processing effect.” In the current experiment, we revisited the investigation of this effect in children and tested it in a new cultural group, using a procedure that differs from the existing studies with children. A group of 40 Portuguese children rated the relevance of unrelated words to a survival and a new moving scenario. This encoding task was followed by a surprise free-recall task. Akin to what is typically found, survival processing produced better memory performance than the control condition (moving. These data put on firmer ground the idea that a mnemonic tuning to fitness-relevant encodings is present early in development. The theoretical importance of this result to the adaptive memory literature is discussed, as well as potential practical implications of this kind of approach to the study of memory in children.
The problem Of muscle hypertrophy: Revisited.
Buckner, Samuel L; Dankel, Scott J; Mattocks, Kevin T; Jessee, Matthew B; Mouser, J Grant; Counts, Brittany R; Loenneke, Jeremy P
2016-12-01
In this paper we revisit a topic originally discussed in 1955, namely the lack of direct evidence that muscle hypertrophy from exercise plays an important role in increasing strength. To this day, long-term adaptations in strength are thought to be primarily contingent on changes in muscle size. Given this assumption, there has been considerable attention placed on programs designed to allow for maximization of both muscle size and strength. However, the conclusion that a change in muscle size affects a change in strength is surprisingly based on little evidence. We suggest that these changes may be completely separate phenomena based on: (1) the weak correlation between the change in muscle size and the change in muscle strength after training; (2) the loss of muscle mass with detraining, yet a maintenance of muscle strength; and (3) the similar muscle growth between low-load and high-load resistance training, yet divergent results in strength. Muscle Nerve 54: 1012-1014, 2016. © 2016 Wiley Periodicals, Inc.
Early-Transition Output Decline Revisited
Directory of Open Access Journals (Sweden)
Crt Kostevc
2016-05-01
Full Text Available In this paper we revisit the issue of aggregate output decline that took place in the early transition period. We propose an alternative explanation of output decline that is applicable to Central- and Eastern-European countries. In the first part of the paper we develop a simple dynamic general equilibrium model that builds on work by Gomulka and Lane (2001. In particular, we consider price liberalization, interpreted as elimination of distortionary taxation, as a trigger of the output decline. We show that price liberalization in interaction with heterogeneous adjustment costs and non-employment benefits lead to aggregate output decline and surge in wage inequality. While these patterns are consistent with actual dynamics in CEE countries, this model cannot generate output decline in all sectors. Instead sectors that were initially taxed even exhibit output growth. Thus, in the second part we consider an alternative general equilibrium model with only one production sector and two types of labor and distortion in a form of wage compression during the socialist era. The trigger for labor mobility and consequently output decline is wage liberalization. Assuming heterogeneity of workers in terms of adjustment costs and non-employment benefits can explain output decline in all industries.
Rule Extraction:Using Neural Networks or for Neural Networks?
Institute of Scientific and Technical Information of China (English)
Zhi-Hua Zhou
2004-01-01
In the research of rule extraction from neural networks, fidelity describes how well the rules mimic the behavior of a neural network while accuracy describes how well the rules can be generalized. This paper identifies the fidelity-accuracy dilemma. It argues to distinguish rule extraction using neural networks and rule extraction for neural networks according to their different goals, where fidelity and accuracy should be excluded from the rule quality evaluation framework, respectively.
Fuzzy Multiresolution Neural Networks
Ying, Li; Qigang, Shang; Na, Lei
A fuzzy multi-resolution neural network (FMRANN) based on particle swarm algorithm is proposed to approximate arbitrary nonlinear function. The active function of the FMRANN consists of not only the wavelet functions, but also the scaling functions, whose translation parameters and dilation parameters are adjustable. A set of fuzzy rules are involved in the FMRANN. Each rule either corresponding to a subset consists of scaling functions, or corresponding to a sub-wavelet neural network consists of wavelets with same dilation parameters. Incorporating the time-frequency localization and multi-resolution properties of wavelets with the ability of self-learning of fuzzy neural network, the approximation ability of FMRANN can be remarkable improved. A particle swarm algorithm is adopted to learn the translation and dilation parameters of the wavelets and adjusting the shape of membership functions. Simulation examples are presented to validate the effectiveness of FMRANN.
Introduction to Artificial Neural Networks
DEFF Research Database (Denmark)
Larsen, Jan
1999-01-01
The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....
Revisiting Earth's radial seismic structure using a Bayesian neural network approach
de Wit, R.W.L.
2015-01-01
The gross features of seismic observations can be explained by relatively simple spherically symmetric (1-D) models of wave velocities, density and attenuation, which describe the Earth's average(radial) structure. 1-D earth models are often used as a reference for studies on Earth's thermo-chemical
Revisiting Earth's radial seismic structure using a Bayesian neural network approach
de Wit, R.W.L.
2015-01-01
The gross features of seismic observations can be explained by relatively simple spherically symmetric (1-D) models of wave velocities, density and attenuation, which describe the Earth's average(radial) structure. 1-D earth models are often used as a reference for studies on Earth's thermo-chemical
Revisiting the problem of audio-based hit song prediction using convolutional neural networks
Yang, Li-Chia; Chou, Szu-Yu; Liu, Jen-Yu; Yang, Yi-Hsuan; Chen, Yi-an
2017-01-01
Being able to predict whether a song can be a hit has impor- tant applications in the music industry. Although it is true that the popularity of a song can be greatly affected by exter- nal factors such as social and commercial influences, to which degree audio features computed from musical signals (whom we regard as internal factors) can predict song popularity is an interesting research question on its own. Motivated by the recent success of deep learning techniques, we attempt to ex- tend...
Revisiting the Role of Communication in Adolescent Intimate Partner Violence
Messinger, Adam M.; Rickert, Vaughn I.; Fry, Deborah A.; Lessel, Harriet; Davidson, Leslie L.
2012-01-01
A growing literature suggests that communication strategies can promote or inhibit intimate partner violence (IPV). Research on communication is still needed on a group ripe for early IPV intervention: high school-aged adolescents. This article revisits our previous analyses of young female reproductive clinic patients (Messinger, Davidson, &…
The role of brand destination experience in determining revisit intention
DEFF Research Database (Denmark)
Mattsson, Jan; Barnes, Stuart; Sørensen, Flemming
experience, which provides a more holistic and unified view of the brand destination. The research uses a logistic regression model to determine the role of satisfaction and brand experience in determining revisit intentions. The study also examines differences among subgroups and four brand experience sub...
Keep Moving! Revisiting Thumbnails for Mobile Video Retrieval
W. Hürst; C.G.M. Snoek; W.J. Spoel; M. Tomin
2010-01-01
Motivated by the increasing popularity of video on handheld devices and the resulting importance for effective video retrieval, this paper revisits the relevance of thumbnails in a mobile video retrieval setting. Our study indicates that users are quite able to handle and assess small thumbnails on
Antidote for Zero Tolerance: Revisiting a "Reclaiming" School.
Farner, Conrad D.
2002-01-01
Reports on a revisit to the Frank Lloyd Wright Middle School, which implemented strategies to deal with disciplinary problems. The school continues to progress towards creating the type of reclaiming environment necessary to ensure the needs of all students. Strategies used include alternatives to zero tolerance policy; smaller teams of students;…
The Polarized Structure Function $g_{2} A Lattice Study Revisited
Göckeler, M; Kürzinger, W; Oelrich, H; Rakow, P; Schierholz, G
1999-01-01
A recent lattice calculation of the spin-dependent structure function g_2 is revisited. It has been recognized that the twist-three operator, which gives rise to d_2, mixes non-perturbatively with operators of lower dimensions under renormalization. This changes the results substantially.
Pockets of Participation: Revisiting Child-Centred Participation Research
Franks, Myfanwy
2011-01-01
This article revisits the theme of the clash of interests and power relations at work in participatory research which is prescribed from above. It offers a possible route toward solving conflict between adult-led research carried out by young researchers, funding requirements and organisational constraints. The article explores issues of…
Assesment of mucoadhesion using small deformation rheology revisited
DEFF Research Database (Denmark)
Harloff-Helleberg, Stine; Vissing, Karina Juul; Nielsen, Hanne Mørck
2017-01-01
This work revisits the commonly used approach to assess mucoadhesion in drug delivery by small deformation rheology. The results show that biosimilar mucus serves as a more predictive mucus model system when compared to mucin suspensions. Data is fitted including error propagation, different from...
Bohr’s ‘Light and Life’ revisited
Nussenzveig, H. M.
2015-11-01
I revisit Niels Bohr’s famous 1932 ‘Light and Life’ lecture, confronting it with current knowledge. Topics covered include: life origin and evolution, quantum mechanics and life, brain and mind, consciousness and free will, and light as a tool for biology, with special emphasis on optical tweezers and their contributions to biophysics. Specialized knowledge of biology is not assumed.
Revisiting the Role of Communication in Adolescent Intimate Partner Violence
Messinger, Adam M.; Rickert, Vaughn I.; Fry, Deborah A.; Lessel, Harriet; Davidson, Leslie L.
2012-01-01
A growing literature suggests that communication strategies can promote or inhibit intimate partner violence (IPV). Research on communication is still needed on a group ripe for early IPV intervention: high school-aged adolescents. This article revisits our previous analyses of young female reproductive clinic patients (Messinger, Davidson, &…
Intramolecular Amide Hydrolysis in N-Methylmaleamic Acid Revisited
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The intramolecular amide hydrolysis of N-methylmaleamic acid have been revisited by use of density functional theory and inclusion of solvent effects. The results indicate that concerted reaction mechanism is favored over stepwise reaction mechanism. This is in agreement with the previous theoretical study. Sovlent effects have significant influence on the reaction barrier.
Coccolithophores in Polar Waters: Papposphaera arctica HET and HOL revisited
DEFF Research Database (Denmark)
Thomsen, Helge Abildhauge; Heldal, Mikal; Østergaard, Jette B.
2016-01-01
It has been generally accepted based on the finding of combination coccospheres in field samples that Turrisphaera arctica and Papposphaera sarion are alternate life-cycle phases of a single species. However, while recently revisiting P. sarion it became evident that the Turrisphaera phase of thi...
Dynamics of Shape Fluctuations of Quasi-spherical Vesicles Revisited
DEFF Research Database (Denmark)
Miao, L.; Lomholt, Michael Andersen; Kleis, J.
2002-01-01
In this paper, the dynamics of spontaneous shape fluctuations of a single, giant quasi-spherical vesicle formed from a single lipid species is revisited theoretically. A coherent physical theory for the dynamics is developed based on a number of fundamental principles and considerations, and a sy...
Pockets of Participation: Revisiting Child-Centred Participation Research
Franks, Myfanwy
2011-01-01
This article revisits the theme of the clash of interests and power relations at work in participatory research which is prescribed from above. It offers a possible route toward solving conflict between adult-led research carried out by young researchers, funding requirements and organisational constraints. The article explores issues of…
Revisiting Mental Simulation in Language Comprehension: Six Replication Attempts
R.A. Zwaan (Rolf); D. Pecher (Diane)
2012-01-01
textabstractThe notion of language comprehension as mental simulation has become popular in cognitive science. We revisit some of the original empirical evidence for this. Specifically, we attempted to replicate the findings from earlier studies that examined the mental simulation of object orientat
Revisiting the Trust Effect in Urban Elementary Schools
Adams, Curt M.; Forsyth, Patrick B.
2013-01-01
More than a decade after Goddard, Tschannen-Moran, and Hoy (2001) found that collective faculty trust in clients predicts student achievement in urban elementary schools, we sought to identify a plausible link for this relationship. Our purpose in revisiting the trust effect was twofold: (1) to test the main effect of collective faculty trust on…
Educational Administration and the Management of Knowledge: 1980 Revisited
Bates, Richard
2013-01-01
This paper revisits the thesis of a 1980 paper that suggested a new approach to educational administration based upon the New Sociology of Education. In particular it updates answers to the six key questions asked by that paper: what counts as knowledge; how is what counts as knowledge organised; how is what counts as knowledge transmitted; how is…
The Importance of Being a Complement: CED Effects Revisited
Jurka, Johannes
2010-01-01
This dissertation revisits subject island effects (Ross 1967, Chomsky 1973) cross-linguistically. Controlled acceptability judgment studies in German, English, Japanese and Serbian show that extraction out of specifiers is consistently degraded compared to extraction out of complements, indicating that the Condition on Extraction domains (CED,…
Revisiting Constructivist Teaching Methods in Ontario Colleges Preparing for Accreditation
Schultz, Rachel A.
2015-01-01
At the time of writing, the first community colleges in Ontario were preparing for transition to an accreditation model from an audit system. This paper revisits constructivist literature, arguing that a more pragmatic definition of constructivism effectively blends positivist and interactionist philosophies to achieve both student centred…
Educational Administration and the Management of Knowledge: 1980 Revisited
Bates, Richard
2013-01-01
This paper revisits the thesis of a 1980 paper that suggested a new approach to educational administration based upon the New Sociology of Education. In particular it updates answers to the six key questions asked by that paper: what counts as knowledge; how is what counts as knowledge organised; how is what counts as knowledge transmitted; how is…
Moral Judgment Development across Cultures: Revisiting Kohlberg's Universality Claims
Gibbs, John C.; Basinger, Karen S.; Grime, Rebecca L.; Snarey, John R.
2007-01-01
This article revisits Kohlberg's cognitive developmental claims that stages of moral judgment, facilitative processes of social perspective-taking, and moral values are commonly identifiable across cultures. Snarey [Snarey, J. (1985). "The cross-cultural universality of social-moral development: A critical review of Kohlbergian research."…
Faraday effect revisited: sum rules and convergence issues
DEFF Research Database (Denmark)
Cornean, Horia; Nenciu, Gheorghe
2010-01-01
This is the third paper of a series revisiting the Faraday effect. The question of the absolute convergence of the sums over the band indices entering the Verdet constant is considered. In general, sum rules and traces per unit volume play an important role in solid-state physics, and they give...
Generalized Adaptive Artificial Neural Networks
Tawel, Raoul
1993-01-01
Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.
DEFF Research Database (Denmark)
Hansen, Lars Kai; Salamon, Peter
1990-01-01
We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....
Interval probabilistic neural network.
Kowalski, Piotr A; Kulczycki, Piotr
2017-01-01
Automated classification systems have allowed for the rapid development of exploratory data analysis. Such systems increase the independence of human intervention in obtaining the analysis results, especially when inaccurate information is under consideration. The aim of this paper is to present a novel approach, a neural networking, for use in classifying interval information. As presented, neural methodology is a generalization of probabilistic neural network for interval data processing. The simple structure of this neural classification algorithm makes it applicable for research purposes. The procedure is based on the Bayes approach, ensuring minimal potential losses with regard to that which comes about through classification errors. In this article, the topological structure of the network and the learning process are described in detail. Of note, the correctness of the procedure proposed here has been verified by way of numerical tests. These tests include examples of both synthetic data, as well as benchmark instances. The results of numerical verification, carried out for different shapes of data sets, as well as a comparative analysis with other methods of similar conditioning, have validated both the concept presented here and its positive features.
Revisiting Narcolepsy: The Practical Diagnosis and Mythology
Directory of Open Access Journals (Sweden)
Vernon M Neppe
2016-02-01
: This might deprive many in the narcolepsy population of their essential life-sustaining treatment, even though they might have definite clinical features plus the gene expression, and often, already, response to wakefulness drugs. c Third, clinical evaluations must be standardized. At this stage, we, at the PNI b2 apply modifications of the Epworth Sleepiness Scale in conjunction with the Fatigue Severity Scale, and the Neppe Narcolepsy Questionnaire, as fundamental ways to evaluate narcolepsy clinically. These historical rankings and screens combined with proper HLA screening may be adequate for more than 90% of diagnoses. d Fourth, the comorbidities of narcolepsy might include psychosis, anxiety, depression, impaired functioning, and seizure phenomena. These may reflect multifactorial etiologies: some of these may be linked with narcolepsy, and others unassociated. I suggest a new model of hypocretin deficiency being slightly down-stream from the actual cause of narcolepsycataplexy. This accentuates the need for proposing two new terms, namely “primary narcolepsy” for the most common narcolepsy condition that appears to be hypothalamically linked to an auto-immune process involving hypocretin, and “symptomatic narcolepsy” due to infectious or tumor or trauma events involving the hypocretin / reticular activating system/ hypothalamus. On the others hand, some b “PNI” refers to the Pacific Neuropsychiatric Institute in Seattle, WA. “We” is used here to include application at the PNI; “we” is also used generically, for example, in broader recognitions of symptoms by researchers. Revisiting Narcolepsy: The Practical Diagnosis and Mythology 2/30 Copyright: ©2016 Neppe Citation: Neppe VM (2016 Revisiting Narcolepsy: The Practical Diagnosis and Mythology. J Psychol Clin Psychiatry 5(3: 00287. DOI: 10.15406/ jpcpy.2016.05.00287 old classifications have used the previous terms “Type 1 Narcolepsy” for narcolepsy with cataplexy, and “Type 2
Neural dynamics based on the recognition of neural fingerprints
Directory of Open Access Journals (Sweden)
José Luis eCarrillo-Medina
2015-03-01
Full Text Available Experimental evidence has revealed the existence of characteristic spiking features in different neural signals, e.g. individual neural signatures identifying the emitter or functional signatures characterizing specific tasks. These neural fingerprints may play a critical role in neural information processing, since they allow receptors to discriminate or contextualize incoming stimuli. This could be a powerful strategy for neural systems that greatly enhances the encoding and processing capacity of these networks. Nevertheless, the study of information processing based on the identification of specific neural fingerprints has attracted little attention. In this work, we study (i the emerging collective dynamics of a network of neurons that communicate with each other by exchange of neural fingerprints and (ii the influence of the network topology on the self-organizing properties within the network. Complex collective dynamics emerge in the network in the presence of stimuli. Predefined inputs, i.e. specific neural fingerprints, are detected and encoded into coexisting patterns of activity that propagate throughout the network with different spatial organization. The patterns evoked by a stimulus can survive after the stimulation is over, which provides memory mechanisms to the network. The results presented in this paper suggest that neural information processing based on neural fingerprints can be a plausible, flexible and powerful strategy.
Directory of Open Access Journals (Sweden)
M.E. Marshall
1981-09-01
Full Text Available Neural tube defects refer to any defect in the morphogenesis of the neural tube, the most common types being spina bifida and anencephaly. Spina bifida has been recognised in skeletons found in north-eastern Morocco and estimated to have an age of almost 12 000 years. It was also known to the ancient Greek and Arabian physicians who thought that the bony defect was due to the tumour. The term spina bifida was first used by Professor Nicolai Tulp of Amsterdam in 1652. Many other terms have been used to describe this defect, but spina bifida remains the most useful general term, as it describes the separation of the vertebral elements in the midline.
Gupta, S; Gupta, Sanjay
2002-01-01
This paper initiates the study of quantum computing within the constraints of using a polylogarithmic ($O(\\log^k n), k\\geq 1$) number of qubits and a polylogarithmic number of computation steps. The current research in the literature has focussed on using a polynomial number of qubits. A new mathematical model of computation called \\emph{Quantum Neural Networks (QNNs)} is defined, building on Deutsch's model of quantum computational network. The model introduces a nonlinear and irreversible gate, similar to the speculative operator defined by Abrams and Lloyd. The precise dynamics of this operator are defined and while giving examples in which nonlinear Schr\\"{o}dinger's equations are applied, we speculate on its possible implementation. The many practical problems associated with the current model of quantum computing are alleviated in the new model. It is shown that QNNs of logarithmic size and constant depth have the same computational power as threshold circuits, which are used for modeling neural network...
DEFF Research Database (Denmark)
Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten
2007-01-01
maintained their neurogenic potential throughout 77 days of propagation, while the ability of anterior NTS to generate neurons severely declined from day 40. The present procedure describes isolation and long-term expansion of forebrain SVZ tissue with potential preservation of the endogenous cellular......By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue......-spheres (NTS) in EGF and FGF2 containing medium. The spheres were cut into quarters when passaged every 10-15th day, avoiding mechanical or enzymatic dissociation in order to minimize cellular trauma and preserve intercellular contacts. For analysis of regional differences within the forebrain SVZ, NTS were...
Kass, Robert E; Brown, Emery N
2014-01-01
Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.
Directory of Open Access Journals (Sweden)
Kapil Nahar
2012-12-01
Full Text Available An artificial neural network is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information.The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons working in unison to solve specific problems.Ann’s, like people, learn by example.
Neural networks for triggering
Energy Technology Data Exchange (ETDEWEB)
Denby, B. (Fermi National Accelerator Lab., Batavia, IL (USA)); Campbell, M. (Michigan Univ., Ann Arbor, MI (USA)); Bedeschi, F. (Istituto Nazionale di Fisica Nucleare, Pisa (Italy)); Chriss, N.; Bowers, C. (Chicago Univ., IL (USA)); Nesti, F. (Scuola Normale Superiore, Pisa (Italy))
1990-01-01
Two types of neural network beauty trigger architectures, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment. The efficiencies for B's and rejection of background obtained are encouraging. If hardware tests are successful, the electron identification architecture will be tested in the 1991 run of CDF. 10 refs., 5 figs., 1 tab.
Coupled Neural Associative Memories
Karbasi, Amin; Salavati, Amir Hesam; Shokrollahi, Amin
2013-01-01
We propose a novel architecture to design a neural associative memory that is capable of learning a large number of patterns and recalling them later in presence of noise. It is based on dividing the neurons into local clusters and parallel plains, very similar to the architecture of the visual cortex of macaque brain. The common features of our proposed architecture with those of spatially-coupled codes enable us to show that the performance of such networks in eliminating noise is drastical...
Directory of Open Access Journals (Sweden)
Kapil Nahar
2012-12-01
Full Text Available An artificial neural network is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons working in unison to solve specific problems. Ann’s, like people, learn by example.
Compressing Convolutional Neural Networks
Chen, Wenlin; Wilson, James T.; Tyree, Stephen; Weinberger, Kilian Q.; Chen, Yixin
2015-01-01
Convolutional neural networks (CNN) are increasingly used in many areas of computer vision. They are particularly attractive because of their ability to "absorb" great quantities of labeled data through millions of parameters. However, as model sizes increase, so do the storage and memory requirements of the classifiers. We present a novel network architecture, Frequency-Sensitive Hashed Nets (FreshNets), which exploits inherent redundancy in both convolutional layers and fully-connected laye...
Artificial neural network modelling
Samarasinghe, Sandhya
2016-01-01
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .
Institute of Scientific and Technical Information of China (English)
POO; Mu-Ming
2010-01-01
One of the properties of the nervous system is the use-dependent plasticity of neural circuits.The structure and function of neural circuits are susceptible to changes induced by prior neuronal activity,as reflected by short-and long-term modifications of synaptic efficacy and neuronal excitability.Regarded as the most attractive cellular mechanism underlying higher cognitive functions such as learning and memory,activity-dependent synaptic plasticity has been in the spotlight of modern neuroscience since 1973 when activity-induced long-term potentiation(LTP) of hippocampal synapses was first discovered.Over the last 10 years,Chinese neuroscientists have made notable contributions to the study of the cellular and molecular mechanisms of synaptic plasticity,as well as of the plasticity beyond synapses,including activity-dependent changes in intrinsic neuronal excitability,dendritic integration functions,neuron-glia signaling,and neural network activity.This work highlight some of these significant findings.
The Stern-Gerlach experiment revisited
Schmidt-Böcking, Horst; Schmidt, Lothar; Lüdde, Hans Jürgen; Trageser, Wolfgang; Templeton, Alan; Sauer, Tilman
2016-12-01
experimental example for such directional quantization in scattering processes is shown. Last not least, the early history of the "almost" discovery of the electron spin in the SGE is revisited.
The significance test controversy revisited the fiducial Bayesian alternative
Lecoutre, Bruno
2014-01-01
The purpose of this book is not only to revisit the “significance test controversy,”but also to provide a conceptually sounder alternative. As such, it presents a Bayesian framework for a new approach to analyzing and interpreting experimental data. It also prepares students and researchers for reporting on experimental results. Normative aspects: The main views of statistical tests are revisited and the philosophies of Fisher, Neyman-Pearson and Jeffrey are discussed in detail. Descriptive aspects: The misuses of Null Hypothesis Significance Tests are reconsidered in light of Jeffreys’ Bayesian conceptions concerning the role of statistical inference in experimental investigations. Prescriptive aspects: The current effect size and confidence interval reporting practices are presented and seriously questioned. Methodological aspects are carefully discussed and fiducial Bayesian methods are proposed as a more suitable alternative for reporting on experimental results. In closing, basic routine procedures...
The contact of elastic regular wavy surfaces revisited
Yastrebov, Vladislav A
2014-01-01
We revisit the classic problem of an elastic solid with a two-dimensional wavy surface squeezed against an elastic flat half-space from infinitesimal to full contact. Through extensive numerical calculations and analytic derivations, we discover previously overlooked transition regimes. These are seen in particular in the evolution with applied load of the contact area and perimeter, the mean pressure and the probability density of contact pressure. These transitions are correlated with the contact area shape, which is affected by long range elastic interactions between contacting zones. Our analysis has implications for general random rough surfaces, as similar local transitions occur continuously at detached areas or coalescing contact zones. A key result is the deduction of the probability density of contact pressure at full contact. We discover that there is a non-zero probability of null contact pressures, which might suggest revisiting the conditions necessary for applying Persson's model at partial con...
Zero-frequency magnetic fluctuations in homogeneous cosmic plasma revisited
Caruso, Francisco
2011-01-01
Magnetic fluctuations in a non-magnetized gaseous plasma is revisited and calculated without approximations, based on the fluctuation-dissipation theorem. It is argued that the present results are qualitative and quantitative different form previous one based on the same theorem. In particular, it is shown that it is not correct that the spectral intensity does not vary sensitively with $k_{cut}$. Also the simultaneous dependence of this intensity on the plasma and on the collisional frequencies are discussed.
Zero-frequency magnetic fluctuations in homogeneous cosmic plasma revisited
Caruso, Francisco; Oguri, Vitor
2011-01-01
Magnetic fluctuations in a non-magnetized gaseous plasma is revisited and calculated without approximations, based on the fluctuation-dissipation theorem. It is argued that the present results are qualitative and quantitative different form previous one based on the same theorem. In particular, it is shown that it is not correct that the spectral intensity does not vary sensitively with $k_{cut}$. Also the simultaneous dependence of this intensity on the plasma and on the collisional frequenc...
Ligature-induced peri-implantitis in minipigs revisited
Stübinger, Stefan; Bucher, Ramon; Kronen, Peter W; Schlottig, Falko; von Rechenberg, Brigitte
2016-01-01
Aim: The ligature-induced defect model still remains the model of first choice to experimentally investigate the cause, effect and treatment approaches of periimplantitis. It was the aim of the present in-vivo trail to revisit the ligature-induced peri-implantitis minipig model regarding its current scientific value and ethical justification in implant research. Materials and methods: Six minipigs were used for the analysis of peri-implant hard and soft tissue structures. Animals were rand...
Discussion of "Computational Electrocardiography: Revisiting Holter ECG Monitoring".
Baumgartner, Christian; Caiani, Enrico G; Dickhaus, Hartmut; Kulikowski, Casimir A; Schiecke, Karin; van Bemmel, Jan H; Witte, Herbert
2016-08-01
This article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper "Computational Electrocardiography: Revisiting Holter ECG Monitoring" written by Thomas M. Deserno and Nikolaus Marx. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of Deserno and Marx. In subsequent issues the discussion can continue through letters to the editor.
Indoor air and human health revisited: A recent IAQ symposium
Energy Technology Data Exchange (ETDEWEB)
Gammage, R.B.
1994-12-31
Indoor Air and Human Health Revisited was a speciality symposium examining the scientific underpinnings of sensory and sensitivity effects, allergy and respiratory disease, neurotoxicity and cancer. An organizing committee selected four persons to chain the sessions and invite experts to give state-of-the-art presentations that will be published as a book. A summary of the presentations is made and some critical issues identified.
Topological Twisted Sigma Model with H-flux Revisited
Energy Technology Data Exchange (ETDEWEB)
Chuang, Wu-yen
2006-08-18
In this paper we revisit the topological twisted sigma model with H-flux. We explicitly expand and then twist the worldsheet Lagrangian for bi-Hermitian geometry. we show that the resulting action consists of a BRST exact term and pullback terms, which only depend on one of the two generalized complex structures and the B-field. We then discuss the topological feature of the model.
Hospital revisit rate after a diagnosis of conversion disorder.
Merkler, Alexander E; Parikh, Neal S; Chaudhry, Simriti; Chait, Alanna; Allen, Nicole C; Navi, Babak B; Kamel, Hooman
2016-04-01
To estimate the hospital revisit rate of patients diagnosed with conversion disorder (CD). Using administrative data, we identified all patients discharged from California, Florida and New York emergency departments (EDs) and acute care hospitals between 2005 and 2011 with a primary discharge diagnosis of CD. Patients discharged with a primary diagnosis of seizure or transient global amnesia (TGA) served as control groups. Our primary outcome was the rate of repeat ED visits and hospital admissions after initial presentation. Poisson regression was used to compare rates between diagnosis groups while adjusting for demographic characteristics. We identified 7946 patients discharged with a primary diagnosis of CD. During a mean follow-up of 3.0 (±1.6) years, patients with CD had a median of three (IQR, 1-9) ED or inpatient revisits, compared with 0 (IQR, 0-2) in patients with TGA and 3 (IQR, 1-7) in those with seizures. Revisit rates were 18.25 (95% CI, 18.10 to 18.40) visits per 100 patients per month in those with CD, 3.90 (95% CI, 3.84 to 3.95) in those with TGA and 17.78 (95% CI, 17.75 to 17.81) in those with seizures. As compared to CD, the incidence rate ratio for repeat ED visits or hospitalisations was 0.89 (95% CI, 0.86 to 0.93) for seizure disorder and 0.32 (95% CI 0.31 to 0.34) for TGA. CD is associated with a substantial hospital revisit rate. Our findings suggest that CD is not an acute, time-limited response to stress, but rather that CD is a manifestation of a broader pattern of chronic neuropsychiatric disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Radiative Corrections to Neutrino Deep Inelastic Scattering Revisited
Arbuzov, A B; Kalinovskaya, L V
2005-01-01
Radiative corrections to neutrino deep inelastic scattering are revisited. One-loop electroweak corrections are re-calculated within the automatic SANC system. Terms with mass singularities are treated including higher order leading logarithmic corrections. Scheme dependence of corrections due to weak interactions is investigated. The results are implemented into the data analysis of the NOMAD experiment. The present theoretical accuracy in description of the process is discussed.
EGOTIATION IS THE NEW NEGOTIATION: THE CONCEPT OF NEGOTIATION REVISITED
Katarzyna Jagodzinska
2016-01-01
The definition of negotiation has already been broadly examined in literature and varies from one author to another. However, there does not exist a complete conceptualization, which would grasp all the essential constituents of negotiation. This article aims to fill this niche by revisiting the concept of negotiation and broadening it by the elusive element that, if not properly addressed, too often causes negotiations to fail: the ego factor.Consequently, this paper introduces the novel ...
N Level System with RWA and Analytical Solutions Revisited
Fujii, K; Kato, R; Wada, Y; Fujii, Kazuyuki; Higashida, Kyoko; Kato, Ryosuke; Wada, Yukako
2003-01-01
In this paper we consider a model of an atom with n energy levels interacting with n(n-1)/2 external (laser) fields which is a natural extension of two level system, and assume the rotating wave approximation (RWA) from the beginning. We revisit some construction of analytical solutions (which correspond to Rabi oscillations) of the model in the general case and examine it in detail in the case of three level system.
New Families in the Stable Homotopy of Spheres Revisited
Institute of Scientific and Technical Information of China (English)
LIN Jin Kun
2002-01-01
This paper constructs a new family in the stable homotopy of spheres πt-6S representedby hngoγ3 ∈ E26,t in the Adams spectral sequence which revisits the bn-1g0γ3-elements ∈πt-7S con-structed in [3], where t = 2pn(p- 1) +6(p2 + p+ 1)(p- 1) and p ≥ 7 is a prime, n ≥ 4.
Trimaran Resistance Artificial Neural Network
2011-01-01
11th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 Trimaran Resistance Artificial Neural Network Richard...Trimaran Resistance Artificial Neural Network 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e... Artificial Neural Network and is restricted to the center and side-hull configurations tested. The value in the parametric model is that it is able to
[Artificial neural networks in Neurosciences].
Porras Chavarino, Carmen; Salinas Martínez de Lecea, José María
2011-11-01
This article shows that artificial neural networks are used for confirming the relationships between physiological and cognitive changes. Specifically, we explore the influence of a decrease of neurotransmitters on the behaviour of old people in recognition tasks. This artificial neural network recognizes learned patterns. When we change the threshold of activation in some units, the artificial neural network simulates the experimental results of old people in recognition tasks. However, the main contributions of this paper are the design of an artificial neural network and its operation inspired by the nervous system and the way the inputs are coded and the process of orthogonalization of patterns.
Memorability: A stimulus-driven perceptual neural signature distinctive from memory.
Bainbridge, Wilma A; Dilks, Daniel D; Oliva, Aude
2017-04-01
A long-standing question in neuroscience is how perceptual processes select stimuli for encoding and later retrieval by memory processes. Using a functional magnetic resonance imaging study with human participants, we report the discovery of a global, stimulus-driven processing stream that we call memorability. Memorability automatically tags the statistical distinctiveness of stimuli for later encoding, and shows separate neural signatures from both low-level perception (memorability shows no signal in early visual cortex) and classical subsequent memory based on individual memory. Memorability and individual subsequent memory show dissociable neural substrates: first, memorability effects consistently emerge in the medial temporal lobe (MTL), whereas individual subsequent memory effects emerge in the prefrontal cortex (PFC). Second, memorability effects remain consistent even in the absence of memory (i.e., for forgotten images). Third, the MTL shows higher correlations with memorability-based patterns, while the PFC shows higher correlations with individual memory voxels patterns. Taken together, these results support a reformulated framework of the interplay between perception and memory, with the MTL determining stimulus statistics and distinctiveness to support later memory encoding, and the PFC comparing stimuli to specific individual memories. As stimulus memorability is a confound present in many previous memory studies, these findings should stimulate a revisitation of the neural streams dedicated to perception and memory. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Clique-Based Neural Associative Memories with Local Coding and Precoding.
Mofrad, Asieh Abolpour; Parker, Matthew G; Ferdosi, Zahra; Tadayon, Mohammad H
2016-08-01
Techniques from coding theory are able to improve the efficiency of neuroinspired and neural associative memories by forcing some construction and constraints on the network. In this letter, the approach is to embed coding techniques into neural associative memory in order to increase their performance in the presence of partial erasures. The motivation comes from recent work by Gripon, Berrou, and coauthors, which revisited Willshaw networks and presented a neural network with interacting neurons that partitioned into clusters. The model introduced stores patterns as small-size cliques that can be retrieved in spite of partial error. We focus on improving the success of retrieval by applying two techniques: doing a local coding in each cluster and then applying a precoding step. We use a slightly different decoding scheme, which is appropriate for partial erasures and converges faster. Although the ideas of local coding and precoding are not new, the way we apply them is different. Simulations show an increase in the pattern retrieval capacity for both techniques. Moreover, we use self-dual additive codes over field [Formula: see text], which have very interesting properties and a simple-graph representation.
Directory of Open Access Journals (Sweden)
J. Reyes-Reyes
2000-01-01
Full Text Available In this paper, an adaptive technique is suggested to provide the passivity property for a class of partially known SISO nonlinear systems. A simple Dynamic Neural Network (DNN, containing only two neurons and without any hidden-layers, is used to identify the unknown nonlinear system. By means of a Lyapunov-like analysis the new learning law for this DNN, guarantying both successful identification and passivation effects, is derived. Based on this adaptive DNN model, an adaptive feedback controller, serving for wide class of nonlinear systems with an a priori incomplete model description, is designed. Two typical examples illustrate the effectiveness of the suggested approach.
Highly Accurate Multi-layer Perceptron Neural Network for Air Data System
Directory of Open Access Journals (Sweden)
H. S. Krishna
2009-11-01
Full Text Available The error backpropagation multi-layer perceptron algorithm is revisited. This algorithm is used to train and validate two models of three-layer neural networks that can be used to calibrate a 5-hole pressure probe. This paper addresses Occam's Razor problem as it describes the adhoc training methodology applied to improve accuracy and sensitivity. The trained outputs from 5-4-3 feed-forward network architecture with jump connection are comparable to second decimal digit (~0.05 accuracy, hitherto unreported in literature.Defence Science Journal, 2009, 59(6, pp.670-674, DOI:http://dx.doi.org/10.14429/dsj.59.1574
Mechanisms of brain evolution: regulation of neural progenitor cell diversity and cell cycle length.
Borrell, Victor; Calegari, Federico
2014-09-01
In the last few years, several studies have revisited long-held assumptions in the field of brain development and evolution providing us with a fundamentally new vision on the mechanisms controlling its size and shape, hence function. Among these studies, some described hitherto unforeseeable subtypes of neural progenitors while others reinterpreted long-known observations about their cell cycle in alternative new ways. Most remarkably, this knowledge combined has allowed the generation of mammalian model organisms in which brain size and folding has been selectively increased giving us the means to understand the mechanisms underlying the evolution of the most complex and sophisticated organ. Here we review the key findings made in this area and make a few conjectures about their evolutionary meaning including the likelihood of Martians conquering our planet.
Tagliaferri, Roberto; Longo, Giuseppe; Milano, Leopoldo; Acernese, Fausto; Barone, Fabrizio; Ciaramella, Angelo; De Rosa, Rosario; Donalek, Ciro; Eleuteri, Antonio; Raiconi, Giancarlo; Sessa, Salvatore; Staiano, Antonino; Volpicelli, Alfredo
2003-01-01
In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large astronomical databases which is foreseen in the framework of the astrophysical virtual observatory and national virtual observatory projects, is, however, posing unprecedented data mining and visualization problems which will find a rather natural and user friendly answer in artificial intelligence tools based on NNs, fuzzy sets or genetic algorithms. This review is aimed to both astronomers (who often have little knowledge of the methodological background) and computer scientists (who often know little about potentially interesting applications), and therefore will be structured as follows: after giving a short introduction to the subject, we shall summarize the methodological background and focus our attention on some of the most interesting fields of application, namely: object extraction and classification, time series analysis, noise identification, and data mining. Most of the original work described in the paper has been performed in the framework of the AstroNeural collaboration (Napoli-Salerno).
Heiden, Uwe
1980-01-01
The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica ted throughout the text. However, they are not explored in de tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be havior of neurons or neuron pools. In this respect the essay is writt...
Koulakov, Alexei
Olfaction is the final frontier of our senses - the one that is still almost completely mysterious to us. Despite extensive genetic and perceptual data, and a strong push to solve the neural coding problem, fundamental questions about the sense of smell remain unresolved. Unlike vision and hearing, where relatively straightforward relationships between stimulus features and neural responses have been foundational to our understanding sensory processing, it has been difficult to quantify the properties of odorant molecules that lead to olfactory percepts. In a sense, we do not have olfactory analogs of ``red'', ``green'' and ``blue''. The seminal work of Linda Buck and Richard Axel identified a diverse family of about 1000 receptor molecules that serve as odorant sensors in the nose. However, the properties of smells that these receptors detect remain a mystery. I will review our current understanding of the molecular properties important to the olfactory system. I will also describe a theory that explains how odorant identity can be preserved despite substantial changes in the odorant concentration.
Kennis, M.
2016-01-01
The aim of this thesis was to gain more insight in the neural network alterations that may underlie PTSD and trauma-focused therapy outcome. To investigate TheNeural Web of War brain scans of healthy civilians (n=26), and veterans with (n=58) and without (n=29) PTSD were assessed. Structural and fun
The Neural Support Vector Machine
Wiering, Marco; van der Ree, Michiel; Embrechts, Mark; Stollenga, Marijn; Meijster, Arnold; Nolte, A; Schomaker, Lambertus
2013-01-01
This paper describes a new machine learning algorithm for regression and dimensionality reduction tasks. The Neural Support Vector Machine (NSVM) is a hybrid learning algorithm consisting of neural networks and support vector machines (SVMs). The output of the NSVM is given by SVMs that take a
Neural Networks for Optimal Control
DEFF Research Database (Denmark)
Sørensen, O.
1995-01-01
Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....
The Neural Support Vector Machine
Wiering, Marco; van der Ree, Michiel; Embrechts, Mark; Stollenga, Marijn; Meijster, Arnold; Nolte, A; Schomaker, Lambertus
2013-01-01
This paper describes a new machine learning algorithm for regression and dimensionality reduction tasks. The Neural Support Vector Machine (NSVM) is a hybrid learning algorithm consisting of neural networks and support vector machines (SVMs). The output of the NSVM is given by SVMs that take a centr
Neural Networks for Optimal Control
DEFF Research Database (Denmark)
Sørensen, O.
1995-01-01
Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....
VOLTAGE COMPENSATION USING ARTIFICIAL NEURAL NETWORK
African Journals Online (AJOL)
VOLTAGE COMPENSATION USING ARTIFICIAL NEURAL NETWORK: A CASE STUDY OF RUMUOLA DISTRIBUTION NETWORK. ... The artificial neural networks controller engaged to controlling the dynamic voltage ... Article Metrics.
Medical diagnosis using neural network
Kamruzzaman, S M; Siddiquee, Abu Bakar; Mazumder, Md Ehsanul Hoque
2010-01-01
This research is to search for alternatives to the resolution of complex medical diagnosis where human knowledge should be apprehended in a general fashion. Successful application examples show that human diagnostic capabilities are significantly worse than the neural diagnostic system. This paper describes a modified feedforward neural network constructive algorithm (MFNNCA), a new algorithm for medical diagnosis. The new constructive algorithm with backpropagation; offer an approach for the incremental construction of near-minimal neural network architectures for pattern classification. The algorithm starts with minimal number of hidden units in the single hidden layer; additional units are added to the hidden layer one at a time to improve the accuracy of the network and to get an optimal size of a neural network. The MFNNCA was tested on several benchmarking classification problems including the cancer, heart disease and diabetes. Experimental results show that the MFNNCA can produce optimal neural networ...
Neural fields theory and applications
Graben, Peter; Potthast, Roland; Wright, James
2014-01-01
With this book, the editors present the first comprehensive collection in neural field studies, authored by leading scientists in the field - among them are two of the founding-fathers of neural field theory. Up to now, research results in the field have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. Starting with a tutorial for novices in neural field studies, the book comprises chapters on emergent patterns, their phase transitions and evolution, on stochastic approaches, cortical development, cognition, robotics and computation, large-scale numerical simulations, the coupling of neural fields to the electroencephalogram and phase transitions in anesthesia. The intended readership are students and scientists in applied mathematics, theoretical physics, theoretical biology, and computational neuroscience. Neural field theory and its applications have a long-standing tradition in the mathematical and computational ...
Topological entropy of catalytic sets: Hypercycles revisited
Sardanyés, Josep; Duarte, Jorge; Januário, Cristina; Martins, Nuno
2012-02-01
The dynamics of catalytic networks have been widely studied over the last decades because of their implications in several fields like prebiotic evolution, virology, neural networks, immunology or ecology. One of the most studied mathematical bodies for catalytic networks was initially formulated in the context of prebiotic evolution, by means of the hypercycle theory. The hypercycle is a set of self-replicating species able to catalyze other replicator species within a cyclic architecture. Hypercyclic organization might arise from a quasispecies as a way to increase the informational containt surpassing the so-called error threshold. The catalytic coupling between replicators makes all the species to behave like a single and coherent evolutionary multimolecular unit. The inherent nonlinearities of catalytic interactions are responsible for the emergence of several types of dynamics, among them, chaos. In this article we begin with a brief review of the hypercycle theory focusing on its evolutionary implications as well as on different dynamics associated to different types of small catalytic networks. Then we study the properties of chaotic hypercycles with error-prone replication with symbolic dynamics theory, characterizing, by means of the theory of topological Markov chains, the topological entropy and the periods of the orbits of unimodal-like iterated maps obtained from the strange attractor. We will focus our study on some key parameters responsible for the structure of the catalytic network: mutation rates, autocatalytic and cross-catalytic interactions.
Risk of hospitalisation after early-revisit in the emergency department.
Cozzi, Giorgio; Ghirardo, Sergio; Fiorese, Ilaria; Proietti, Ilaria; Monasta, Lorenzo; Minute, Marta; Barbi, Egidio; Calligaris, Lorenzo
2017-09-01
Early-revisits are frequent in the paediatric emergency department (ED) setting, but few data are available about early-revisited patients. The aim of this study was to investigate the hospitalisation rate of a population of early-revisited patients and to detect if an early-revisited patient was at risk of a more severe disease. Between June 2014 and January 2015, we conducted a retrospective cohort study, considering all patients presented to the ED of a tertiary level children's hospital in Italy. We selected all patients who were revisited within 72 h from the initial visit (study cohort), while all other patients accessed in the same period were considered the control cohort. The two cohorts were compared for age, gender, triage category, hospitalisation rate, diagnosis at admission and hospital length of stay. In the study period, we reviewed 10 750 visits, of which 430 (4%) were unplanned revisits for the same chief complaint within 72 h from the initial visit. Hospitalisation rate of early-revisited patients was significantly higher compared to control patients (8.4 vs. 2.9%). Hospitalisation rate increases in parallel with the number of revisits, but in many cases, it was not directly related to a worst triage category, neither to a longer hospital length of stay. Early revisited patients in the ED had a significantly higher risk of hospitalisation, but this risk was only partially related to their clinical conditions. © 2017 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).
L'Empire ottoman revisité The Ottoman Empire revisited
Directory of Open Access Journals (Sweden)
Krikor Beledian
2012-05-01
Full Text Available L'Empire ottoman dans l'œuvre monumentale d’Hagop Sirouni (Djololian, Turquie 1890-Bucarest 1973, une image qui fascine et déchire. Poète, prosateur, théoricien de la littérature et historien, exilé en Roumanie en 1923, Sirouni édite la revue Nawasart (1924-25 et d'autres publications littéraires en langues arménienne et/ou roumaine. Arrêté en 1944 et condamné à dix ans de camp sibérien, Sirouni retourne à Bucarest au début des années cinquante. Obsédé par la nostalgie d'un pays perdu et hanté par l'épouvante des années 1915-1918, Sirouni entreprend l'évocation de la fin de l'Empire dans des récits et des pièces de théâtre des années vingt et trente. Il fait de l'art une modalité de la survie. Mais cette écriture se mue progressivement en mémoires et en reconstitution historique (Constantinople et son rôle, quatre volumes, comme si le regard tourné vers l'origine se refusait désormais les charmes de la fiction et de l'autobiographie pour s'adonner à un examen apparemment plus distancé, à une appropriation plus critique de la naissance et de la mort de l'Empire. Le récit historique se substitue au récit littéraire. On a parlé souvent d'un renoncement à la littérature, en ce qui concerne ce revirement. Et pourtant, l'Empire ottoman revisité dans ses archives ne cesse pas moins d'être l'objet désiré dont l'image fascine et déchire l'exilé doublement persécuté que fut Sirouni.This lecture is dedicated to the monumental works of Hagop Sirouni (Djololian, Turkey 1890-Bucarest 1973, a poet, novelist, litterary theorist and historian. Send in exile in Romania in 1923, he edited the periodical press « Nawasart » (1924-25 and other litterary publications in armenian and/or roumanian. Arrested in 1944 and condemned in a ten year sentence in a Siberian camp, Sirouni returns in Bucharest at the beginning of the fifties. Obsessed by the nostalgia of a country lost and haunted by the terror that came
Neural correlates of consciousness.
Negrao, B L; Viljoen, M
2009-11-01
A basic understanding of consciousness and its neural correlates is of major importance for all clinicians, especially those involved with patients with altered states of consciousness. In this paper it is shown that consciousness is dependent on the brainstem and thalamus for arousal; that basic cognition is supported by recurrent electrical activity between the cortex and the thalamus at gamma band frequencies; aand that some kind of working memory must, at least fleetingly, be present for awareness to occur. The problem of cognitive binding and the role of attention are briefly addressed and it shown that consciousness depends on a multitude of subconscious processes. Although these processes do not represent consciousness, consciousness cannot exist without them.
Neural Darwinism and consciousness.
Seth, Anil K; Baars, Bernard J
2005-03-01
Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.
Directory of Open Access Journals (Sweden)
Tal eGonen
2014-11-01
Full Text Available Motivation is a key neurobehavioral concept underlying adaptive responses to environmental incentives and threats. As such, dysregulation of motivational processes may be critical in the formation of abnormal behavioral patterns/tendencies. According to the long standing model of the Reinforcement Sensitivity Theory (RST, motivation behaviors are driven by three neurobehavioral systems mediating the sensitivity to punishment, reward or goal-conflict. Corresponding to current neurobehavioral theories in psychiatry, this theory links abnormal motivational drives to abnormal behavior; viewing depression and mania as two abnormal extremes of reward driven processes leading to either under or over approach tendencies, respectively. We revisit the RST framework in the context of bipolar disorder (BD and challenge this concept by suggesting that dysregulated interactions of both punishment and reward related processes better account for the psychological and neural abnormalities observed in BD. We further present an integrative model positing that the three parallel motivation systems currently proposed by the RST model, can be viewed as subsystems in a large-scale neurobehavioral network of motivational decision making.
Gonen, Tal; Sharon, Haggai; Pearlson, Godfrey; Hendler, Talma
2014-01-01
Motivation is a key neurobehavioral concept underlying adaptive responses to environmental incentives and threats. As such, dysregulation of motivational processes may be critical in the formation of abnormal behavioral patterns/tendencies. According to the long standing model of the Reinforcement Sensitivity Theory (RST), motivation behaviors are driven by three neurobehavioral systems mediating the sensitivity to punishment, reward or goal-conflict. Corresponding to current neurobehavioral theories in psychiatry, this theory links abnormal motivational drives to abnormal behavior; viewing depression and mania as two abnormal extremes of reward driven processes leading to either under or over approach tendencies, respectively. We revisit the RST framework in the context of bipolar disorder (BD) and challenge this concept by suggesting that dysregulated interactions of both punishment and reward related processes better account for the psychological and neural abnormalities observed in BD. We further present an integrative model positing that the three parallel motivation systems currently proposed by the RST model, can be viewed as subsystems in a large-scale neurobehavioral network of motivational decision making.
Artificial Neural Network Analysis System
2007-11-02
Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis
Cooperating attackers in neural cryptography.
Shacham, Lanir N; Klein, Einat; Mislovaty, Rachel; Kanter, Ido; Kinzel, Wolfgang
2004-06-01
A successful attack strategy in neural cryptography is presented. The neural cryptosystem, based on synchronization of neural networks by mutual learning, has been recently shown to be secure under different attack strategies. The success of the advanced attacker presented here, called the "majority-flipping attacker," does not decay with the parameters of the model. This attacker's outstanding success is due to its using a group of attackers which cooperate throughout the synchronization process, unlike any other attack strategy known. An analytical description of this attack is also presented, and fits the results of simulations.
Small-angle scattering theory revisited: Photocurrent and spatial localization
DEFF Research Database (Denmark)
Basse, N.P.; Zoletnik, S.; Michelsen, Poul
2005-01-01
In this paper theory on collective scattering measurements of electron density fluctuations in fusion plasmas is revisited. We present the first full derivation of the expression for the photocurrent beginning at the basic scattering concepts. Thereafter we derive detailed expressions for the auto...... laser based two-volume collective scattering instrument for spatially localized turbulence measurements,"Rev. Sci. Instrum. 72, 2579-2592 (2001)].......- and crosspower spectra obtained from measurements. These are discussed and simple simulations made to elucidate the physical meaning of the findings. In this context, the known methods of obtaining spatial localization are discussed and appraised. Where actual numbers are applied, we utilize quantities from two...
Non linear evolution: revisiting the solution in the saturation region
Contreras, Carlos; Meneses, Rodrigo
2014-01-01
In this paper we revisit the problem of the solution to Balitsky-Kovchegov equation deeply in the saturation domain. We find that solution has the form of Levin-Tuchin solution but it depends on variable $\\bar{z} = \\ln(r^2 Q^2_s) + \\mbox{Const}$ and the value of $\\mbox{Const}$ is calculated in this paper. We propose the solution for full BFKL kernel at large $z$ in the entire kinematic region that satisfies the McLerram-Venugopalan initial condition
Revisiting reflexology: Concept, evidence, current practice, and practitioner training
Embong, Nurul Haswani; Soh, Yee Chang; Ming, Long Chiau; Wong, Tin Wui
2015-01-01
Reflexology is basically a study of how one part of the human body relates to another part of the body. Reflexology practitioners rely on the reflexes map of the feet and hands to all the internal organs and other human body parts. They believe that by applying the appropriate pressure and massage certain spots on the feet and hands, all other body parts could be energized and rejuvenated. This review aimed to revisit the concept of reflexology and examine its effectiveness, practices, and th...
Sampling the equilibrium: the j-walking algorithm revisited
Rimas, Zilvinas
2016-01-01
The j-walking Monte-Carlo algorithm is revisited and updated to study the equilibrium properties of a system exhibiting broken ergodicity. The updated algorithm is tested on the Ising model and applied to the lattice-gas model for sorption in aerogel at low temperatures, when dynamics of the system is critically slowed down. It is demonstrated that the updated j-walking simulations are able to produce equilibrium isotherm which are typically hidden by the hysteresis effect within the standard single-flip simulations.
Premises, principles, and practices in qualitative research: revisiting the foundations.
Charmaz, Kathy
2004-09-01
In this keynote address, the author focuses on what we bring to qualitative inquiry and how we conduct our research. What we do, why we do it, and how we do it remain contested issues. She proposes that we look at our methodological premises anew, revisit our principles, and revise our practices. Throughout this address, she draws on Goffman's methodological insights to provide a foundation for reassessing qualitative inquiry. She argues that researchers can build on Goffman's ideas to strengthen their methodological practices and research products. Last, she counters current institutional scrutiny of qualitative inquiry and suggests unacknowledged benefits of this work.
Closed-set-based Discovery of Representative Association Rules Revisited
Balcázar, José L
2010-01-01
The output of an association rule miner is often huge in practice. This is why several concise lossless representations have been proposed, such as the "essential" or "representative" rules. We revisit the algorithm given by Kryszkiewicz (Int. Symp. Intelligent Data Analysis 2001, Springer-Verlag LNCS 2189, 350-359) for mining representative rules. We show that its output is sometimes incomplete, due to an oversight in its mathematical validation, and we propose an alternative complete generator that works within only slightly larger running times.
Revisiting a classic: the Parker-Moffatt problem
Pezzi, O; Servidio, S; Valentini, F; Vasconez, C L; Yang, Y; Malara, F; Matthaeus, W H; Veltri, P
2016-01-01
The interaction of two colliding Alfv\\'en wave packets is here described by means of magnetohydrodynamics (MHD) and hybrid kinetic numerical simulations. The MHD evolution revisits the theoretical insights described by Moffatt, Parker, Kraichnan, Chandrasekhar and Els\\"asser in which the oppositely propagating large amplitude wave packets interact for a finite time, initiating turbulence. However, the extension to include compressive and kinetic effects, while maintaining the gross characteristics of the simpler classic formulation, also reveals intriguing features which go beyond the pure MHD treatment.
Revisiting a Classic: The Parker–Moffatt Problem
Pezzi, O.; Parashar, T. N.; Servidio, S.; Valentini, F.; Vásconez, C. L.; Yang, Y.; Malara, F.; Matthaeus, W. H.; Veltri, P.
2017-01-01
The interaction of two colliding Alfvén wave packets is described here by means of magnetohydrodynamics (MHD) and hybrid kinetic numerical simulations. The MHD evolution revisits the theoretical insights described by Moffatt, Parker, Kraichnan, Chandrasekhar, and Elsässer in which the oppositely propagating large-amplitude wave packets interact for a finite time, initiating turbulence. However, the extension to include compressive and kinetic effects, while maintaining the gross characteristics of the simpler classic formulation, also reveals intriguing features that go beyond the pure MHD treatment.
A control center design revisited: learning from users’ appropriation
DEFF Research Database (Denmark)
Souza da Conceição, Carolina; Cordeiro, Cláudia
2014-01-01
This paper aims to present the lessons learned during a control center design project by revisiting another control center from the same company designed two and a half years before by the same project team. In light of the experience with the first project and its analysis, the designers...... and researchers had important feedback already used to suggest changes for the second project. The opportunity to learn from a previous project was unique, but the knowledge gotten out of it shows the importance of having this feedback from project to project instead of just ‘repeating’ previously used design...
Morphogenetic movements in the neural plate and neural tube: mouse.
Massarwa, R'ada; Ray, Heather J; Niswander, Lee
2014-01-01
The neural tube (NT), the embryonic precursor of the vertebrate brain and spinal cord, is generated by a complex and highly dynamic morphological process. In mammals, the initially flat neural plate bends and lifts bilaterally to generate the neural folds followed by fusion of the folds at the midline during the process of neural tube closure (NTC). Failures in any step of this process can lead to neural tube defects (NTDs), a common class of birth defects that occur in approximately 1 in 1000 live births. These severe birth abnormalities include spina bifida, a failure of closure at the spinal level; craniorachischisis, a failure of NTC along the entire body axis; and exencephaly, a failure of the cranial neural folds to close which leads to degeneration of the exposed brain tissue termed anencephaly. The mouse embryo presents excellent opportunities to explore the genetic basis of NTC in mammals; however, its in utero development has also presented great challenges in generating a deeper understanding of how gene function regulates the cell and tissue behaviors that drive this highly dynamic process. Recent technological advances are now allowing researchers to address these questions through visualization of NTC dynamics in the mouse embryo in real time, thus offering new insights into the morphogenesis of mammalian NTC.
Revisiting the Logan plot to account for non-negligible blood volume in brain tissue
National Research Council Canada - National Science Library
Schain, Martin; Fazio, Patrik; Mrzljak, Ladislav; Amini, Nahid; Al-Tawil, Nabil; Fitzer-Attas, Cheryl; Bronzova, Juliana; Landwehrmeyer, Bernhard; Sampaio, Christina; Halldin, Christer; Varrone, Andrea
2017-01-01
.... The bias extent depends on the amount of radioactivity in the blood vessels. In this study, we seek to revisit the well-established Logan plot and derive alternative formulations that provide estimation of distribution volume ratios (DVRs...
HOBBES AND LOCKE REVISITED: ON UNDERSTANDING, NATURE AND THE SOVEREIGN IN THE 21st CENTURY
National Research Council Canada - National Science Library
David Tneh Cheng Eng
2015-01-01
This paper would revisit Hobbes and Locke's work, namely Leviathan and The Essay Concerning Human Understanding so as to reconnect the work of the two philosophers to the present reading of politics and philosophy...
Complex-Valued Neural Networks
Hirose, Akira
2012-01-01
This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...
Artificial intelligence: Deep neural reasoning
Jaeger, Herbert
2016-10-01
The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471
Logic Mining Using Neural Networks
Sathasivam, Saratha
2008-01-01
Knowledge could be gained from experts, specialists in the area of interest, or it can be gained by induction from sets of data. Automatic induction of knowledge from data sets, usually stored in large databases, is called data mining. Data mining methods are important in the management of complex systems. There are many technologies available to data mining practitioners, including Artificial Neural Networks, Regression, and Decision Trees. Neural networks have been successfully applied in wide range of supervised and unsupervised learning applications. Neural network methods are not commonly used for data mining tasks, because they often produce incomprehensible models, and require long training times. One way in which the collective properties of a neural network may be used to implement a computational task is by way of the concept of energy minimization. The Hopfield network is well-known example of such an approach. The Hopfield network is useful as content addressable memory or an analog computer for s...
Neural correlates of consciousness reconsidered.
Neisser, Joseph
2012-06-01
It is widely accepted among philosophers that neuroscientists are conducting a search for the neural correlates of consciousness, or NCC. Chalmers (2000) conceptualized this research program as the attempt to correlate the contents of conscious experience with the contents of representations in specific neural populations. A notable claim on behalf of this interpretation is that the neutral language of "correlates" frees us from philosophical disputes over the mind/body relation, allowing the science to move independently. But the experimental paradigms and explanatory canons of neuroscience are not neutral about the mechanical relation between consciousness and the brain. I argue that NCC research is best characterized as an attempt to locate a causally relevant neural mechanism and not as an effort to identify a discrete neural representation, the content of which correlates with some actual experience. It might be said that the first C in "NCC" should stand for "causes" rather than "correlates."
Neural Networks in Control Applications
DEFF Research Database (Denmark)
Sørensen, O.
The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...
Neural Networks in Control Applications
DEFF Research Database (Denmark)
Sørensen, O.
examined, and it appears that considering 'normal' neural network models with, say, 500 samples, the problem of over-fitting is neglible, and therefore it is not taken into consideration afterwards. Numerous model types, often met in control applications, are implemented as neural network models....... - Control concepts including parameter estimation - Control concepts including inverse modelling - Control concepts including optimal control For each of the three groups, different control concepts and specific training methods are detailed described.Further, all control concepts are tested on the same......The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...
Neural communication in posttraumatic growth.
Anders, Samantha L; Peterson, Carly K; James, Lisa M; Engdahl, Brian; Leuthold, Arthur C; Georgopoulos, Apostolos P
2015-07-01
Posttraumatic growth (PTG), or positive psychological changes following exposure to traumatic events, is commonly reported among trauma survivors. In the present study, we examined neural correlates of PTG in 106 veterans with PTSD and 193 veteran controls using task-free magnetoencephalography (MEG), diagnostic interviews and measures of PTG, and traumatic event exposure. Global synchronous neural interactions (SNIs) were significantly modulated downward with increasing PTG scores in controls (p = .005), but not in veterans with PTSD (p = .601). This effect was primarily characterized by negative slopes in local neural networks, was strongest in the medial prefrontal cortex, and was much stronger and more extensive in the control than the PTSD group. The present study complements previous research highlighting the role of neural adaptation in healthy functioning.
Neural components of altruistic punishment
Directory of Open Access Journals (Sweden)
Emily eDu
2015-02-01
Full Text Available Altruistic punishment, which occurs when an individual incurs a cost to punish in response to unfairness or a norm violation, may play a role in perpetuating cooperation. The neural correlates underlying costly punishment have only recently begun to be explored. Here we review the current state of research on the neural basis of altruism from the perspectives of costly punishment, emphasizing the importance of characterizing elementary neural processes underlying a decision to punish. In particular, we emphasize three cognitive processes that contribute to the decision to altruistically punish in most scenarios: inequity aversion, cost-benefit calculation, and social reference frame to distinguish self from others. Overall, we argue for the importance of understanding the neural correlates of altruistic punishment with respect to the core computations necessary to achieve a decision to punish.
Modular, Hierarchical Learning By Artificial Neural Networks
Baldi, Pierre F.; Toomarian, Nikzad
1996-01-01
Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.
A Study on Associative Neural Memories
B.D.C.N.Prasad; P. E. S. N. Krishna Prasad; Sagar Yeruva; P Sita Rama Murty
2011-01-01
Memory plays a major role in Artificial Neural Networks. Without memory, Neural Network can not be learned itself. One of the primary concepts of memory in neural networks is Associative neural memories. A survey has been made on associative neural memories such as Simple associative memories (SAM), Dynamic associative memories (DAM), Bidirectional Associative memories (BAM), Hopfield memories, Context Sensitive Auto-associative memories (CSAM) and so on. These memories can be applied in vari...
Neural Network Communications Signal Processing
1994-08-01
Technical Information Report for the Neural Network Communications Signal Processing Program, CDRL A003, 31 March 1993. Software Development Plan for...track changing jamming conditions to provide the decoder with the best log- likelihood ratio metrics at a given time. As part of our development plan we...Artificial Neural Networks (ICANN-91) Volume 2, June 24-28, 1991, pp. 1677-1680. Kohonen, Teuvo, Raivio, Kimmo, Simula, Oli, Venta , 011i, Henriksson
Serotonin, neural markers, and memory
Alfredo eMeneses
2015-01-01
Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The i...
What are artificial neural networks?
DEFF Research Database (Denmark)
Krogh, Anders
2008-01-01
Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...
Flexibility of neural stem cells
Directory of Open Access Journals (Sweden)
Eumorphia eRemboutsika
2011-04-01
Full Text Available Embryonic cortical neural stem cells are self-renewing progenitors that can differentiate into neurons and glia. We generated neurospheres from the developing cerebral cortex using a mouse genetic model that allows for lineage selection and found that the self-renewing neural stem cells are restricted to Sox2 expressing cells. Under normal conditions, embryonic cortical neurospheres are heterogeneous with regard to Sox2 expression and contain astrocytes, neural stem cells and neural progenitor cells sufficiently plastic to give rise to neural crest cells when transplanted into the hindbrain of E1.5 chick and E8 mouse embryos. However, when neurospheres are maintained under lineage selection, such that all cells express Sox2, neural stem cells maintain their Pax6+ cortical radial glia identity and exhibit a more restricted fate in vitro and after transplantation. These data demonstrate that Sox2 preserves the cortical identity and regulates the plasticity of self-renewing Pax6+ radial glia cells.
Revisiting the Decision of Death in Hurst v. Florida.
Cooke, Brian K; Ginory, Almari; Zedalis, Jennifer
2016-12-01
The United States Supreme Court has considered the question of whether a judge or a jury must make the findings necessary to support imposition of the death penalty in several notable cases, including Spaziano v. Florida (1984), Hildwin v. Florida (1989), and Ring v. Arizona (2002). In 2016, the U.S. Supreme Court revisited the subject in Hurst v. Florida Florida Statute § 921.141 allows the judge, after weighing aggravating and mitigating circumstances, to enter a sentence of life imprisonment or death. Before Hurst, Florida's bifurcated sentencing proceedings included an advisory sentence from jurors and a separate judicial hearing without juror involvement. In Hurst, the Court revisited the question of whether Florida's capital sentencing scheme violates the Sixth Amendment, which requires a jury, not a judge, to find each fact necessary to impose a sentence of death in light of Ring In an eight-to-one decision, the Court reversed the judgment of the Florida Supreme Court, holding that the Sixth Amendment requires a jury to find the aggravating factors necessary for imposing the death penalty. The role of Florida juries in capital sentencing proceedings was thereby elevated from advisory to determinative. We examine the Court's decision and offer commentary regarding this shift from judge to jury in the final imposition of the death penalty and the overall effect of this landmark case.
Review - Revisiting Rituals in a Changing Tibetan World
Directory of Open Access Journals (Sweden)
Christina Kilby
2013-12-01
Full Text Available Review of: Katia Buffetrille (ed. 2012. Revisiting Rituals in a Changing Tibetan World. Leiden: Brill. Volume 31 in Brill's Tibetan Studies Library. Featuring Buddhist ritual life in its diverse manifestations across the Tibetan Plateau, this volume engages the task of defining 'ritual' by analyzing moments of ritual change. Whether political regime change, technological innovation, or social upheaval, external catalysts of religious transformation have been prominently visible in the Tibetan cultural world since the mid-twentieth century. This volume takes up the sociopolitical shifts of the recent period as a call to investigate how rituals change under fire, thereby furthering our understanding of the relationship between ritual structures and the historical contexts in which they find expression. Ritual's intertwinement with political events, symbols, and attitudes is the resounding theme presented herein, as each chapter makes efforts to disambiguate the complex causes and contours of ritual change in a particular case study. Several chapters seek to distinguish deep structural transformation in ritual from the harnessing of ritual elements for single instances of political or social action. Others debate the ambiguous role of spaces, practices, or ideas that are employed in ritual but also in political or economic contexts. Finally, each chapter challenges in some way the polarization of ritual conservatism and the 'invention of tradition' (Ranger and Hobsbawm 1983. Revisiting Rituals is an edited collection of conference papers...
Recurrent neural collective classification.
Monner, Derek D; Reggia, James A
2013-12-01
With the recent surge in availability of data sets containing not only individual attributes but also relationships, classification techniques that take advantage of predictive relationship information have gained in popularity. The most popular existing collective classification techniques have a number of limitations-some of them generate arbitrary and potentially lossy summaries of the relationship data, whereas others ignore directionality and strength of relationships. Popular existing techniques make use of only direct neighbor relationships when classifying a given entity, ignoring potentially useful information contained in expanded neighborhoods of radius greater than one. We present a new technique that we call recurrent neural collective classification (RNCC), which avoids arbitrary summarization, uses information about relationship directionality and strength, and through recursive encoding, learns to leverage larger relational neighborhoods around each entity. Experiments with synthetic data sets show that RNCC can make effective use of relationship data for both direct and expanded neighborhoods. Further experiments demonstrate that our technique outperforms previously published results of several collective classification methods on a number of real-world data sets.
Understanding Neural Networks for Machine Learning using Microsoft Neural Network Algorithm
National Research Council Canada - National Science Library
Nagesh Ramprasad
2016-01-01
.... In this research, focus is on the Microsoft Neural System Algorithm. The Microsoft Neural System Algorithm is a simple implementation of the adaptable and popular neural networks that are used in the machine learning...
The holographic neural network: Performance comparison with other neural networks
Klepko, Robert
1991-10-01
The artificial neural network shows promise for use in recognition of high resolution radar images of ships. The holographic neural network (HNN) promises a very large data storage capacity and excellent generalization capability, both of which can be achieved with only a few learning trials, unlike most neural networks which require on the order of thousands of learning trials. The HNN is specially designed for pattern association storage, and mathematically realizes the storage and retrieval mechanisms of holograms. The pattern recognition capability of the HNN was studied, and its performance was compared with five other commonly used neural networks: the Adaline, Hamming, bidirectional associative memory, recirculation, and back propagation networks. The patterns used for testing represented artificial high resolution radar images of ships, and appear as a two dimensional topology of peaks with various amplitudes. The performance comparisons showed that the HNN does not perform as well as the other neural networks when using the same test data. However, modification of the data to make it appear more Gaussian distributed, improved the performance of the network. The HNN performs best if the data is completely Gaussian distributed.
Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.
Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu
2016-07-14
This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.
Neural network regulation driven by autonomous neural firings
Cho, Myoung Won
2016-07-01
Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.
Multigradient for Neural Networks for Equalizers
Directory of Open Access Journals (Sweden)
Chulhee Lee
2003-06-01
Full Text Available Recently, a new training algorithm, multigradient, has been published for neural networks and it is reported that the multigradient outperforms the backpropagation when neural networks are used as a classifier. When neural networks are used as an equalizer in communications, they can be viewed as a classifier. In this paper, we apply the multigradient algorithm to train the neural networks that are used as equalizers. Experiments show that the neural networks trained using the multigradient noticeably outperforms the neural networks trained by the backpropagation.
Neural recording and modulation technologies
Chen, Ritchie; Canales, Andres; Anikeeva, Polina
2017-01-01
In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.
Selective Manipulation of Neural Circuits.
Park, Hong Geun; Carmel, Jason B
2016-04-01
Unraveling the complex network of neural circuits that form the nervous system demands tools that can manipulate specific circuits. The recent evolution of genetic tools to target neural circuits allows an unprecedented precision in elucidating their function. Here we describe two general approaches for achieving circuit specificity. The first uses the genetic identity of a cell, such as a transcription factor unique to a circuit, to drive expression of a molecule that can manipulate cell function. The second uses the spatial connectivity of a circuit to achieve specificity: one genetic element is introduced at the origin of a circuit and the other at its termination. When the two genetic elements combine within a neuron, they can alter its function. These two general approaches can be combined to allow manipulation of neurons with a specific genetic identity by introducing a regulatory gene into the origin or termination of the circuit. We consider the advantages and disadvantages of both these general approaches with regard to specificity and efficacy of the manipulations. We also review the genetic techniques that allow gain- and loss-of-function within specific neural circuits. These approaches introduce light-sensitive channels (optogenetic) or drug sensitive channels (chemogenetic) into neurons that form specific circuits. We compare these tools with others developed for circuit-specific manipulation and describe the advantages of each. Finally, we discuss how these tools might be applied for identification of the neural circuits that mediate behavior and for repair of neural connections.
VLSI implementation of neural networks.
Wilamowski, B M; Binfet, J; Kaynak, M O
2000-06-01
Currently, fuzzy controllers are the most popular choice for hardware implementation of complex control surfaces because they are easy to design. Neural controllers are more complex and hard to train, but provide an outstanding control surface with much less error than that of a fuzzy controller. There are also some problems that have to be solved before the networks can be implemented on VLSI chips. First, an approximation function needs to be developed because CMOS neural networks have an activation function different than any function used in neural network software. Next, this function has to be used to train the network. Finally, the last problem for VLSI designers is the quantization effect caused by discrete values of the channel length (L) and width (W) of MOS transistor geometries. Two neural networks were designed in 1.5 microm technology. Using adequate approximation functions solved the problem of activation function. With this approach, trained networks were characterized by very small errors. Unfortunately, when the weights were quantized, errors were increased by an order of magnitude. However, even though the errors were enlarged, the results obtained from neural network hardware implementations were superior to the results obtained with fuzzy system approach.
Neural networks and statistical learning
Du, Ke-Lin
2014-01-01
Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...
Principles of neural information processing
Seelen, Werner v
2016-01-01
In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...
Neural substrates of semantic memory.
Hart, John; Anand, Raksha; Zoccoli, Sandra; Maguire, Mandy; Gamino, Jacque; Tillman, Gail; King, Richard; Kraut, Michael A
2007-09-01
Semantic memory is described as the storage of knowledge, concepts, and information that is common and relatively consistent across individuals (e.g., memory of what is a cup). These memories are stored in multiple sensorimotor modalities and cognitive systems throughout the brain (e.g., how a cup is held and manipulated, the texture of a cup's surface, its shape, its function, that is related to beverages such as coffee, and so on). Our ability to engage in purposeful interactions with our environment is dependent on the ability to understand the meaning and significance of the objects and actions around us that are stored in semantic memory. Theories of the neural basis of the semantic memory of objects have produced sophisticated models that have incorporated to varying degrees the results of cognitive and neural investigations. The models are grouped into those that are (1) cognitive models, where the neural data are used to reveal dissociations in semantic memory after a brain lesion occurs; (2) models that incorporate both cognitive and neuroanatomical information; and (3) models that use cognitive, neuroanatomic, and neurophysiological data. This review highlights the advances and issues that have emerged from these models and points to future directions that provide opportunities to extend these models. The models of object memory generally describe how category and/or feature representations encode for object memory, and the semantic operations engaged in object processing. The incorporation of data derived from multiple modalities of investigation can lead to detailed neural specifications of semantic memory organization. The addition of neurophysiological data can potentially provide further elaboration of models to include semantic neural mechanisms. Future directions should incorporate available and newly developed techniques to better inform the neural underpinning of semantic memory models.
Gospel, culture and mission: Revisiting an enduring problem
Directory of Open Access Journals (Sweden)
O.U. Kalu
1998-08-01
Full Text Available Gospel, culture and mission: Revisiting an enduring problem This article reflects on the 1996 Conference on World Mission and Evangelism. The relation between gospel, culture and mission is considered, especially from an Africa perspective, but not reserved to it in application. Apart from considering the problem of appropriate terminology to express the intricacies concerning the subject, a deeper search is conducted into the complex relationship between the believer, his mission to, and his distancing from divergent cultural sources and manifestations. Emerging perspectives are considered, which help to formulate mission strategies and historic viewpoints and attitudes. Knowledge of these perspectives is essential for a more responsible answering to the call made to all believers.
Revisiting time reversal and holography with spacetime transformations
Bacot, Vincent; Eddi, Antonin; Fink, Mathias; Fort, Emmanuel
2015-01-01
Wave control is usually performed by spatially engineering the properties of a medium. Because time and space play similar roles in wave propagation, manipulating time boundaries provides a complementary approach. Here, we experimentally demonstrate the relevance of this concept by introducing instantaneous time mirrors. We show with water waves that a sudden change of the effective gravity generates time-reversed waves that refocus at the source. We generalize this concept for all kinds of waves introducing a universal framework which explains the effect of any time disruption on wave propagation. We show that sudden changes of the medium properties generate instant wave sources that emerge instantaneously from the entire space at the time disruption. The time-reversed waves originate from these "Cauchy sources" which are the counterpart of Huygens virtual sources on a time boundary. It allows us to revisit the holographic method and introduce a new approach for wave control.
Gadsup of Papua New Guinea revisited: a three decade view.
Leininger, M
1993-01-01
The purpose of this article is to share some highlights of the author's revisits to Papua New Guinea covering three decades (1962-1992) with focus on the Gadsup of the Eastern Highlands of New Guinea. In addition, some recent developments in the country are covered as well as special visits with members of the Papua New Guinea Nurses Association. A comparative analysis of the world view, social structure, and related factors is made with respect to the theory of Culture Care Diversity and Univers-ality with two Gadsup villages. In general, the researcher found limited progress and beneficial health care changes in the two villages. Rascalism with violence was discovered which had cultural functions to redress some of the socioeconomic inequities and dissatisfactions of the indigenous people. Major tenets of the Culture Care theory were supported with the Gadsup, especially related to diverse forms, meanings, and lifestyle processes.
Downlink Transmission of Short Packets: Framing and Control Information Revisited
DEFF Research Database (Denmark)
Trillingsgaard, Kasper Fløe; Popovski, Petar
2017-01-01
Cellular wireless systems rely on frame-based transmissions. The frame design is conventionally based on heuristics, consisting of a frame header and a data part. The frame header contains control information that provides pointers to the messages within the data part. In this paper, we revisit...... the principles of frame design and show the impact of the new design in scenarios that feature short data packets, which are central to various 5G and Internet of Things applications. We~treat framing for downlink transmission in an AWGN broadcast channel with $K$ users, where the sizes of the messages...... to the users are random variables. Using approximations from finite blocklength information theory, we establish a framework in which a message to a given user is not necessarily encoded as a single packet, but may be grouped with messages to other users and benefit from the improved efficiency of longer codes...
Shuttle entry guidance revisited using nonlinear geometric methods
Mease, Kenneth D.; Kremer, Jean-Paul
1994-11-01
The entry guidance law for the space shuttle orbiter is revisited using nonlinear geometric methods. The shuttle guidance concept is to track a reference drag trajectory that has been designed to lead a specified range and velocity. It is shown that the approach taken in the original derivation of the shuttle entry guidance has much in common with the more recently developed feedback linearization method of differential geometric control. Using the feedback linearization method, however, an alternative, potentially superior, guidance law was formulated. Comparing the two guidance laws based performance domains in state space, taking into account the nonlinear dynamics, the alternative guidance law achieves the desired performance over larger domains in state space; the stability domain of the laws are similar. With larger operating domain for the shuttle or some other entry vehicle, the alternative guidance law should be considered.
Revisiting Neoclassical Growth Theory: A Survey in the Literature
Directory of Open Access Journals (Sweden)
Mayank GUPTA
2015-03-01
Full Text Available Abstract During the second half of the twentieth century economists have build newer models of economic growth that consider policy influences of growth and divergent outcomes among countries. These models addresses issues concerning economic growth, operation of financial markets, trade policy, government expenditures, and taxation. In this essay we have revisited the interdependence of political and economic institutions, taking the neoclassical growth model of Solow (1956 as a point of departure, which maintains that long run economic growth can be explained by capital accumulation, population growth and technological progress. We first discuss the evolution of the neoclassical school of economics in a historical context, and the role of various institutions in engendering economic growth. Subsequently the role of government spending, political stability, property rights and special interest groups (SIG's affect economic growth have been discussed, and how these institutions can explain different countries to grow at divergent rates and achieve different levels of wealth.
Revisiting manufacturing strategy: contributions towards a new construct
Directory of Open Access Journals (Sweden)
Eliciane Maria da Silva
2008-07-01
Full Text Available This paper aims at revisiting and systematizing the literature on manufacturing strategy. Although this is a well consolidated theme broadly discussed in the last fifty years, manufacturing strategy practice grew on importance recently due to a more competitive environment the companies find themselves in. The review carried has systematized the existing literature into six lines of research dealing with competitive priorities, structural and infrastructural decision, best practices, performance indicators, production strategy formulation and generic manufacturing strategies. This article shows that four out of the six research areas are still receiving attention. A new construct which represents a global view of the lines of research mentioned is proposed. Gaps in the research field and suggestions for future works are described. Keywords: manufacturing strategy, content, formulation of manufacturing strategy, competitive priorities, best practices, performance indicators.
Revisiting world energy intensity convergence for regional differences
Energy Technology Data Exchange (ETDEWEB)
Liddle, Brantley [Centre for Strategic Economic Studies, Victoria University, Melbourne, VIC 8001 (Australia)
2010-10-15
World convergence in energy intensity is revisited using two new large data sets: a 111-country sample spanning 1971-2006, and a 134-country sample spanning 1990-2006. Both data sets confirm continued convergence. However, the larger data set, which adds the former Soviet Union republics and additional Balkan countries, indicates greater convergence over its more recent time-frame. Further investigation of geographical differences reveals that the OECD and Eurasian countries have shown considerable, continued convergence, while the Sub-Saharan African countries have converged amongst themselves, but at a slower rate than the OECD and Eurasian countries; by contrast, Latin American and Caribbean and Middle East and North African countries have exhibited no convergence to divergence in energy intensity. (author)
Revisiting Estrogen: Efficacy and Safety for Postmenopausal Bone Health
Directory of Open Access Journals (Sweden)
Sandra M. Sacco
2010-01-01
Full Text Available The rapid decline in endogenous estrogen production that occurs during menopause is associated with significant bone loss and increased risk for fragility fracture. While hormone therapy (HT is an effective means to re-establish endogenous estrogen levels and reduce the risk of future fracture, its use can be accompanied by undesirable side effects such as stroke and breast cancer. In this paper, we revisit the issue of whether HT can be both safe and effective for the prevention of postmenopausal bone loss by examining standard and alternative doses and formulations of HT. The aim of this paper is to continue the dialogue regarding the benefits and controversies of HT with the goal of encouraging the dissemination of-up-to date evidence that may influence how HT is viewed and prescribed.
Revisiting the Performance of MACD and RSI Oscillators
Directory of Open Access Journals (Sweden)
Terence Tai-Leung Chong
2014-02-01
Full Text Available Chong and Ng (2008 find that the Moving Average Convergence–Divergence (MACD and Relative Strength Index (RSI rules can generate excess return in the London Stock Exchange. This paper revisits the performance of the two trading rules in the stock markets of five other OECD countries. It is found that the MACD(12,26,0 and RSI(21,50 rules consistently generate significant abnormal returns in the Milan Comit General and the S&P/TSX Composite Index. In addition, the RSI(14,30/70 rule is also profitable in the Dow Jones Industrials Index. The results shed some light on investors’ belief in these two technical indicators in different developed markets.
Neuroticism and vigilance revisited: A transcranial doppler investigation.
Mandell, Arielle R; Becker, Alexandra; VanAndel, Aaron; Nelson, Andrew; Shaw, Tyler H
2015-11-01
Selecting for vigilance assignments remains an important factor in human performance research. The current study revisits the potential relationship between vigilance performance and trait neuroticism, in light of two possible theories. The first theory suggests that neuroticism impairs vigilance performance by competing for available resources. The second theory, attentional control theory, posits that high neuroticism can result in similar or superior performance levels due to the allocation of compensatory effort. In the present study, Transcranial Doppler Sonography was used to investigate the neurophysiological underpinnings of neuroticism during a 12-min abbreviated vigilance task. Performance results were not modified by level of neuroticism, but high neuroticism was associated with higher initial CBFV levels and a greater CBFV decrement over time. These findings indicate that participants higher in neuroticism recruited additional cognitive resources in order to achieve similar performance, suggesting that there is more of an effect on processing efficiency than effectiveness.
Grid generation: Algebraic and partial differential equations techniques revisited
Soni, Bharat K.
A systematic procedure for grid generation which can provide compuational grids for a wide range of geometries related to internal/external flow configuration is developed by combining the best features of algebraic and elliptic grid generation systems. The algebraic and elliptic grid generation system are well developed in the literature. A revisit to these techniques is given in this paper in view of economy and efficiency of the grid generation process. A technique to automatically calculate slopes and twist vectors required in hermite transfinite interpolation is developed. The weighted transfinite interpolation is combined with automatically created Bezier, B-spline curves, and Non-Uniform Rational B-spline (NURB) curves to generate well-distributed, smooth and near orthogonal grid patches (sub-blocks). A novel approach to evaluate control functions for elliptic generation systems is developed. This approach allows a quick refinement utilizing elliptic system. Computational examples are presented to demonstrate the success of these methodologies.
Revisiting constraints on uplifts to de Sitter vacua
Bizet, Nana Cabo
2016-01-01
We revisit the issue of uplifting the potential to de Sitter (dS) vacua in type IIB flux compactifications of Kachru, Kallosh, Linde and Trivedi (KKLT). We shed light on some tension between two constraints on dS vacua in type IIB string theory. One is the well-known and much-discussed constraint which leads to the no-go theorem that can in principle be evaded. The other follows from 4-dimensional Einstein's equations, which has, however, been much less discussed in connection with the former constraint. In addition to the challenges previously posed, it is suggested that the uplifting scenarios, in particular, obstruct the evasion of the no-go theorem more strongly than one might have assumed.
Revisiting Johnson and Jackson boundary conditions for granular flows
Energy Technology Data Exchange (ETDEWEB)
Li, Tingwen; Benyahia, Sofiane
2012-07-01
In this article, we revisit Johnson and Jackson boundary conditions for granular flows. The oblique collision between a particle and a flat wall is analyzed by adopting the classic rigid-body theory and a more realistic semianalytical model. Based on the kinetic granular theory, the input parameter for the partial-slip boundary conditions, specularity coefficient, which is not measurable in experiments, is then interpreted as a function of the particle-wall restitution coefficient, the frictional coefficient, and the normalized slip velocity at the wall. An analytical expression for the specularity coefficient is suggested for a flat, frictional surface with a low frictional coefficient. The procedure for determining the specularity coefficient for a more general problem is outlined, and a working approximation is provided.
Revisiting the scattering greenhouse effect of CO2 ice clouds
Kitzmann, Daniel
2016-01-01
Carbon dioxide ice clouds are thought to play an important role for cold terrestrial planets with thick CO2 dominated atmospheres. Various previous studies showed that a scattering greenhouse effect by carbon dioxide ice clouds could result in a massive warming of the planetary surface. However, all of these studies only employed simplified two-stream radiative transfer schemes to describe the anisotropic scattering. Using accurate radiative transfer models with a general discrete ordinate method, this study revisits this important effect and shows that the positive climatic impact of carbon dioxide clouds was strongly overestimated in the past. The revised scattering greenhouse effect can have important implications for the early Mars, but also for planets like the early Earth or the position of the outer boundary of the habitable zone.
Energy in synthetic fertilizers and pesticides: Revisited. Final project report
Energy Technology Data Exchange (ETDEWEB)
Bhat, M.G.; English, B.C.; Turhollow, A.F.; Nyangito, H.O. [Tennessee Univ., Knoxville, TN (United States). Dept. of Agricultural Economics and Rural Sociology
1994-01-01
Agricultural chemicals that are derived from fossil-fuels are the major energy intensive inputs in agriculture. Growing scarcity of the world`s fossil resources stimulated research and development of energy-efficient technology for manufacturing these chemicals in the last decade. The purpose of this study is to revisit the energy requirements of major plant nutrients and pesticides. The data from manufacturers energy survey conducted by The Fertilizer Institute are used to estimate energy requirements of fertilizers. Energy estimates for pesticides are developed from consulting previously published literature. The impact of technical innovation in the fertilizer industry to US corn, cotton, soybean and wheat producers is estimated in terms of energy-saving.
Revisiting a Classic Study of the Molecular Clock.
Robinson, Lauren M; Boland, Joseph R; Braverman, John M
2016-03-01
A constant rate of molecular evolution among homologous proteins and across lineages is known as the molecular clock. This concept has been useful for estimating divergence times. Here, we revisit a study by Richard Dickerson (J Mol Evol 1:26-45, 1971), wherein he provided striking visual evidence for a constant rate of amino acid changes among various evolutionary branch points. Dickerson's study is commonly cited as support of the molecular clock and a figure from it is often reproduced in textbooks. Since its publication, however, there have been updates made to dates of common ancestors based on the fossil record that should be considered. Additionally, collecting the accession numbers and carefully outlining Dickerson's methods serves as a resource to students of the molecular clock hypothesis.
Revisiting the thermodynamic relations in AdS /CMT models
Hyun, Seungjoon; Park, Sang-A.; Yi, Sang-Heon
2017-03-01
Motivated by the recent unified approach to the Smarr-like relation of anti-de Sitter (AdS) planar black holes in conjunction with the quasilocal formalism on conserved charges, we revisit the quantum statistical and thermodynamic relations of hairy AdS planar black holes. By extending the previous results, we identify the hairy contribution in the bulk and show that the holographic computation can be improved so that it is consistent with the bulk computation. We argue that the first law can be retained in its universal form and that the relation between the on-shell renormalized Euclidean action and its free energy interpretation in gravity may also be undeformed even with the hairy contribution in hairy AdS black holes.
EGOTIATION IS THE NEW NEGOTIATION: THE CONCEPT OF NEGOTIATION REVISITED
Directory of Open Access Journals (Sweden)
Katarzyna Jagodzinska
2016-04-01
Full Text Available The definition of negotiation has already been broadly examined in literature and varies from one author to another. However, there does not exist a complete conceptualization, which would grasp all the essential constituents of negotiation. This article aims to fill this niche by revisiting the concept of negotiation and broadening it by the elusive element that, if not properly addressed, too often causes negotiations to fail: the ego factor.Consequently, this paper introduces the novel concept of egotiation. The new conceptual framework provides a straightforward and user-friendly reference that can be used when preparing for a negotiation or at any time during a negotiation to help better understand all the dynamics behind the negotiation process.Furthermore, this article unravels what negotiation really is based on the responses collected from a multicultural audience, and shows how these results align with the novel concept of negotiation.
Revisiting the Design of a Fusion Development Facility
Chan, V. S.; Stambaugh, R. D.; Garofalo, A. M.; Smith, J. P.; Wong, C. P. C.
2009-11-01
A Fusion Development Facility (FDF) is proposed to make possible a DEMO of the ARIES-AT type as the next step after ITER. The mission of the FDF should be to carry forward advanced tokamak physics and enable development of fusion nuclear science and technology. We have added more realism to the initial FDF concept [1] including inner and outer gaps from the plasma to the first wall; an improved estimate of the inboard/outboard blanket/shield thickness to protect the magnets/insulators; control coil positions; and realistic divertor geometry. Optimizing the mix of heating and current drive power has high leverage on the operating power. We have also revisited the assumed impurity fraction and the density profile peakedness. 8pt [1] R.D. Stambaugh, et al., Bull. Am. Phys. Soc. 53, 259 (2008).
Online haemodiafiltration: definition, dose quantification and safety revisited.
Tattersall, James E; Ward, Richard A
2013-03-01
The general objective assigned to the EUropean DIALlysis (EUDIAL) Working Group by the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) was to enhance the quality of dialysis therapies in Europe in the broadest possible sense. Given the increasing interest in convective therapies, the Working Group has started by focusing on haemodiafiltration (HDF) therapies. Several reports suggest that those therapies potentially improve the outcomes for end-stage renal disease patients. Europe is the leader in the field, having introduced the concept of ultra-purity for water and dialysis fluids and with notified bodies of the European Community having certified water treatment systems and online HDF machines. The prevalence of online HDF-treated patients is steadily increasing in Europe, averaging 15%. A EUDIAL consensus conference was held in Paris on 13 October 2011 to revisit terminology, safety and efficacy of online HDF. This is the first report of the expert group arising from that conference.
Impulsive Spot Heating and Thermal Explosion of Interstellar Grains Revisited
Ivlev, A V; Vasyunin, A; Caselli, P
2015-01-01
The problem of impulsive heating of dust grains in cold, dense interstellar clouds is revisited theoretically, with the aim to better understand leading mechanisms of the explosive desorption of icy mantles. It is rigorously shown that if the heating of a reactive medium occurs within a sufficiently localized spot (e.g., heating of mantles by cosmic rays), then the subsequent thermal evolution is characterized by a single dimensionless number $\\lambda$. This number identifies a bifurcation between two distinct regimes: When $\\lambda$ exceeds a critical value (threshold), the heat equation exhibits the explosive solution, i.e., the thermal (chemical) explosion is triggered. Otherwise, thermal diffusion causes the deposited heat to spread over the entire grain -- this regime is commonly known as the whole-grain heating. The theory allows us to find a critical combination of the physical parameters that govern the explosion of icy mantles due to impulsive spot heating. In particular, the calculations suggest tha...
Quantum computing in neural networks
Gralewicz, P
2004-01-01
According to the statistical interpretation of quantum theory, quantum computers form a distinguished class of probabilistic machines (PMs) by encoding n qubits in 2n pbits. This raises the possibility of a large-scale quantum computing using PMs, especially with neural networks which have the innate capability for probabilistic information processing. Restricting ourselves to a particular model, we construct and numerically examine the performance of neural circuits implementing universal quantum gates. A discussion on the physiological plausibility of proposed coding scheme is also provided.
Neural Decoder for Topological Codes
Torlai, Giacomo; Melko, Roger G.
2017-07-01
We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.
The neural cell adhesion molecule
DEFF Research Database (Denmark)
Berezin, V; Bock, E; Poulsen, F M
2000-01-01
During the past year, the understanding of the structure and function of neural cell adhesion has advanced considerably. The three-dimensional structures of several of the individual modules of the neural cell adhesion molecule (NCAM) have been determined, as well as the structure of the complex...... between two identical fragments of the NCAM. Also during the past year, a link between homophilic cell adhesion and several signal transduction pathways has been proposed, connecting the event of cell surface adhesion to cellular responses such as neurite outgrowth. Finally, the stimulation of neurite...
Visual Grouping by Neural Oscillators
Yu, Guoshen
2008-01-01
Distributed synchronization is known to occur at several scales in the brain, and has been suggested as playing a key functional role in perceptual grouping. State-of-the-art visual grouping algorithms, however, seem to give comparatively little attention to neural synchronization analogies. Based on the framework of concurrent synchronization of dynamic systems, simple networks of neural oscillators coupled with diffusive connections are proposed to solve visual grouping problems. Multi-layer algorithms and feedback mechanisms are also studied. The same algorithm is shown to achieve promising results on several classical visual grouping problems, including point clustering, contour integration and image segmentation.
Antenna analysis using neural networks
Smith, William T.
1992-01-01
Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern
Plant Growth Models Using Artificial Neural Networks
Bubenheim, David
1997-01-01
In this paper, we descrive our motivation and approach to devloping models and the neural network architecture. Initial use of the artificial neural network for modeling the single plant process of transpiration is presented.
Ocean wave forecasting using recurrent neural networks
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.; Prabaharan, N.
, merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off...